In‑House versus Outsourced Training: An Analytical Study of Cost

and Productivity at Rourkela Steel Plant, Odisha

Shyama Charan Dwivedi

, Vivek Bajpai

and Prabodh Kr. Mohanty

Department of Commerce and Management, Dr. CV Raman University, Kargi Road, Kota, Bilaspur, Chattisgarh, India

Director HR, Odisha Hydro Power Corporation Ltd. Bhubaneswar, Odisha, India

Keywords: Training, Development, In‑House Training, Outsourced Training, Employee Productivity, Cost Management,

Steel Industry, Rourkela Steel Plant.

Abstract: The efficacy of training and development in the steel sector is essential for enhancing workforce capabilities,

productivity, and cost efficiency. This study examines the necessity, obstacles, and effects of in-house and

outsourced training at Rourkela Steel Plant (RSP), Odisha. Data were obtained from 470 individuals,

comprising executives, supervisors, and operational staff, utilizing a descriptive and diagnostic research

approach. The research assesses attitudes towards training (H01), the influence of training type on cost-

effectiveness and productivity (H02), and the presence of skill deficiencies among employees (H03). Results

from ANOVA and Structural Equation Modeling (SEM) indicate that executives possess a more positive

opinion of training, whereas operational workers identify more significant skill deficiencies (p < 0.001). In-

house training demonstrated superior cost- effectiveness (M = 80.00, SD = 8.00) and enhanced productivity

(M = 75.00, SD = 10.00) in comparison to outsourced training (M = 70.00, SD = 10.00; M = 68.00, SD =

12.00, respectively). The findings demonstrate that structured internal training models produce superior

performance results, whereas outsourced training is crucial for acquiring specialized skills. The report

advocates for a hybrid training methodology, tailored competency-based training programs, and the

incorporation of technology-enhanced learning solutions to address skill deficiencies and enhance labor

efficiency.

1 INTRODUCTION

Training and development are fundamental to

contemporary organizational management,

profoundly impacting employee performance,

productivity, and overall organizational

competitiveness. Organizations are progressively

acknowledging the strategic importance of training to

equip employees with vital skills, hence improving

their task performance, adaptability to technological

advancements, and competitiveness in global

marketplaces (Diamantidis et al., 2019). Efficient

training programs directly promote employee

engagement, job satisfaction, skill development, and

productivity, thereby providing enduring value to the

firm (Chhabra, 2021).

1.1 Definitions of Fundamental

Concepts

In-house training refers to development activity that

is carried out within an organization, using internal

personnel, expertise, and facilities. It gives

enterprises greater control over the training process,

ensuring that it is aligned with the organization’s

goals, keeping proprietary information confidential,

and allowing changes and delivery of content to be

customized (Ulrich, 1996).

One such solution is outsourced training, which

means employing and leveraging external providers

that are equipped in both the creation and deliverance

of training material that allows organizations to have

access to specialized expertise, reduced operating

costs, and rapid responsiveness to changing training

needs and emerging technologies (Shih & Chiang,

2011).

1.2 Emergence and Growing

Preference for Outsourcing

Rapid technology change, heightened global

competition and more complex market dynamics

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Charan Dwivedi, S., Bajpai, V. and Kr. Mohanty, P.

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SHouse versus Outsourced Training: An Analytical Study of Cost and Productivity at Rourkela Steel Plant, Odisha.

DOI: 10.5220/0013906000004919

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies (ICRDICCT‘25 2025) - Volume 3, pages

802-810

ISBN: 978-989-758-777-1

has accelerated the global and Indian trend toward

outsourcing training functions in the last few years.

Especially in areas where technology is evolving

quickly, outsourcing training has proven to be a

strategic move because the skills needed are often too

specific for a firm to internalize. Besides, external

trainers tend to be equipped with the relevant

experience and backend technologies to show robust

training solutions, which helps reduce time and

associated costs for enterprises (Elmuti & Kathawala,

2000 & Galanaki, 2008). India's steel industry is an

important sector that plays a significant role in the

economy. The Rourkela Steel Plant (RSP), one of the

steel giants in India, faces significant challenges in

the training and development of its workforce due to

rapid technological changes and competitive

pressures. Hence, understanding in-house and

outsourced training needs, efficiency and external

barriers at RSP is essential for enhancing

productivity, cost-effectiveness and sustainability of

the firm (Chhabra, 2021). This current study aims to

study the training needs and related challenges faced

by the Rourkela Steel Plant and provide valuable

insights towards the effective balancing and strategic

switching of training methodologies

1.3 Significance of the Study

The rationale for a significant contribution comes

from the analysis of strategic management policies of

in-house or outsourced training delivery, or the

production vs. productivity cost management policy

in Rourkela Steel Plant to identify the impact on

training productivity at the firm level. These results

aim to provide meaningful information that can

improve training approaches, utilize resources, and

increase overall organizational success.

2 RELATED WORKS

2.1 Perceptions of Training and

Development in the Steel Industry

Effects of training and development programs on

employee performance and organizational

performance. According to the research, employees

see training as a key investment that helps in career

advancement and boosts job satisfaction. Steel

industry built in structured training programs lead to

continual skill development, which ensures smoother

work and higher quality work (Jehanzeb, 2013).

Heraty, N. (1992). asserts that companies in very

competitive sectors, including steel manufacture,

regard training as a crucial instrument for sustaining

a competitive advantage. The research indicated that

organizations prioritizing staff development saw

enhanced operational efficiency and diminished

attrition rates. Practitioners acknowledged the

enduring advantages of ongoing skill enhancement,

hence strengthening a favorable view of training

programs.

Shaheen (2019) examined the efficacy of

competency frameworks within the manufacturing

industry. Their findings indicated that structured

training programs in the steel industry effectively

address skill shortages, enhancing employee

adaptability to technological changes. Practitioners

recognized the necessity for ongoing education,

particularly in light of automation and changing

industry norms.

Aguinis (2009) emphasized the psychological

advantages of training, such as enhanced job

satisfaction, motivation, and engagement. The

research indicated that personnel in technical sectors,

including steel manufacture, linked training

initiatives to professional advancement and economic

security. This favorable perception led to increased

participation rates in development projects.

SamGnanakkan (2010) investigated the impact of

organizational commitment on employees'

perceptions of training. Results demonstrated that

steel industry professionals were more inclined to

participate in training when bolstered by managerial

support and incentives. A robust learning culture

resulted in enhanced productivity and

elevated retention rates.

Thirkell et al., (2014) found numerous hurdles in

the implementation of effective training programs

inside steel businesses. Although employees

acknowledged the advantages, the survey revealed

that resource limitations, insufficient time, and

antiquated training methodologies occasionally

impeded the perceived efficacy of training programs.

Nevertheless, practitioners maintained a positive

outlook regarding the contribution of training to skill

enhancement and operational efficiency.

2.2 Impact of In-House and

Outsourced Training on Cost-

Effectiveness and Employee

Productivity

A recent study by William, B., & Okafor, C (2024)

analyzed the effects of outsourcing human resources

functions, including training, on cost efficiency and

production. The study revealed that outsourced

training alleviates internal resource limitations and

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enables organizations to utilize specialized skills and

cutting-edge technologies. The study indicated that

outsourcing is only cost- effective in the short term,

but in-house training promotes long-term cost

stability and staff integration.

Namadi, S (2023) examined the effects of

strategic outsourcing on corporate cost management

and operational efficiency. The research indicated

that outsourcing training increases profitability by

lowering administrative expenses and facilitating

access to external experts. Nevertheless, the research

warned that excessive dependence on external

training may result in workforce reliance on outside

consultants, so constraining internal knowledge

retention.

Brewster, C., & Mayrhofer, W (2012) analysed

the effects of in-house versus outsourced training

methodologies on company cost structures. The

research indicated that in-house training programs are

30% more cost-efficient over time owing to reduce

per-employee training expenses. Conversely,

outsourced training provides flexibility, albeit at an

elevated per-session expense, rendering it suitable for

short-term specialized instruction.

Noe (2017) conducted an extensive assessment of

training and staff development, emphasizing that

organizations that invest in organized in-house

training programs experience a 15% increase in

productivity. The research highlighted that model

training must correspond with company objectives to

optimize cost-effectiveness and staff productivity.

Kavanagh, M. J., & Thite, M (2009) analysed the

advantages and disadvantages of outsourcing training

services. Their findings indicate that although

outsourced training decreases initial expenses, it may

not consistently correspond with company-specific

processes and culture, resulting in diminished

employee engagement and knowledge retention.

Sharma, P., & Mishra, K (2019) explored the

correlation between training methodologies and

employee productivity within the manufacturing

sector. Their research determined that a hybrid model

integrating internal and external training enhances

educational results and cost- effectiveness. They

advised organizations to allocate resources for in-

house training for fundamental skills while

outsourcing training for sophisticated technical

advancements.

2.3 Skill Gaps between Job

Requirements and Existing

Competencies in the Steel Industry

Fareri et al., 2023 examined the developing digital

skill deficiencies in the manufacturing industry,

highlighting the necessity for workforce reskilling to

improve energy efficiency. The study emphasizes

that digital transformation necessitates new

competences, and numerous steelworkers lack

expertise in data analytics, automation, and AI-driven

technologies. The results indicate that training

programs should incorporate digital literacy to meet

changing industrial demands.

Antonazzo, L., & Stroud, D (2023) analysed the

European steel sector's reaction to talent deficiencies

resulting from Industry 4.0 innovations. The research

revealed that conventional training methodologies do

not meet emerging competency demands, especially

in robotics, automation, and intelligent industrial

systems. The study emphasizes that vocational

education and industry collaborations are essential in

closing the skills gap.

Akyazi et al., (2024) examined the impact of

Industry 4.0 on the evolving skill requirements of the

workforce in the steel industry. The research

highlighted that conventional mechanical abilities are

inadequate, as the sector today requires proficiency in

cyber-physical systems, the Internet of Things, and

predictive maintenance. The study recommends the

creation of a sector-specific database to monitor and

evaluate skill deficiencies.

Antonazzo et al., (2024) examined the evolving

competency environment in steel manufacturing,

emphasizing the increasing significance of soft skills,

digital literacy, and problem-solving capabilities. The

researchers discovered that the present workforce

frequently lacks interdisciplinary expertise, hindering

adaptability to integrated and automated

manufacturing processes. The document advocates

for the development of new skill creation

mechanisms to improve worker adaptability.

Akyazi et al., (2022) examined future skill

demands in European manufacturing and delineated

abilities essential for sustainable industrial

operations.

The results indicate that understanding of

sustainability is becoming essential; nonetheless, the

majority of existing personnel are uninformed about

green manufacturing, circular economy concepts, and

energy-efficient technologies. The study advocates

for the integration of sustainability-oriented courses

into workforce training programs.

Maldonado-Mariscal et al., (2023) analysed skills

intelligence systems in steel manufacturing and

underscored the necessity for improved labour

planning.

The research contends that organizations need to

utilize AI-driven training analytics to detect

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competency deficiencies in real-time and execute

focused upskilling initiatives.

2.4 Objectives and Hypotheses

2.4.1 Objectives

To investigate the need and challenges of in-house

and outsourced training at Rourkela Steel Plant

(RSP).

2.4.2 Hypotheses

H01: Practitioners in the steel industry possess a

positive perception towards training and development

activities.

H02: In-house and outsourced training significantly

impact the cost-effectiveness and productivity of

employees.

H03: There exists a significant skill gap between job

requirements and existing competencies among

employees at RSP.

3 METHODOLOGY

3.1 Research Design

This study adopts a blend of descriptive and

diagnostic research methodologies to investigate and

evaluate the training procedures of Rourkela Steel

Plant (RSP). Using descriptive study methodology,

existing training techniques, problems, and employee

attitudes about the effectiveness of training are clearly

defined. The diagnostic method provides a global

view on the factors impacting productivity and cost-

effectiveness of in-house and outsourced training.

3.2 Study Population

The target population is the employees of Rourkela

Steel Plant, Odisha, including Human Resource

executives, HODs of training and development,

supervisors as well as operational- level employees.

These groups together represent multiple hierarchical

levels and roles responsible for implementing

techniques and deploying labs; consequently, they

provide a breadth of insight related to training

effectiveness and its impact on organizational

productivity and cost effectuation.

3.3 Sampling and Sample Size

A total of 470 respondents will participate in the

study, categorized as follows:

1. Executives (50 respondents): Senior HR

executives and managers overseeing training

decisions.

2. Training & Development Heads (20

respondents): Personnel directly

responsible for designing and supervising

training activities.

3. Employees (Supervisory and operational

staff; 400 respondents): Individuals

directly engaged in daily operational

activities and receiving training, thus

capable of providing frontline feedback

regarding the effectiveness of training

interventions.

3.4 Sampling Techniques

Use a mixed method sampling approach using

stratified random sampling with purposive sampling

techniques. Adequate representation across diverse

job roles and hierarchical levels as well adds to the

generalizability through stratified random sampling.

Data was collected using a purposive sampling

method, to select as potential interviewees two HR

executives and heads of training with in-depth

knowledge of training policies, practices, and

outcomes.

Data collected through a structured questionnaire

tailored specifically to different respondent

categories. The questionnaire measures employee

perceptions, satisfaction, and attitudes towards in-

house versus outsourced training practices.

3.5 Data Analysis Tools

The data collected will be analysed using descriptive

statistics, reliability and validity analysis, parametric

and non-parametric tests, and hypothesis testing

using SPSS and SEM. These tools will summarize

demographic details, ensure questionnaire reliability

and validity, and test theoretical models and

hypotheses using AMOS software for structural

equation modelling.

4 DATA ANALYSIS

4.1 (H01) Perception towards Training

and Development

The descriptive statistics and ANOVA results

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SHouse versus Outsourced Training: An Analytical Study of Cost and Productivity at Rourkela Steel Plant, Odisha

805

demonstrated that Executives (M = 4.20, SD = 0.50)

had a more positive perception of training

effectiveness compared to Supervisors (M = 3.80, SD

= 0.60) and Operational Staff (M = 3.50, SD = 0.70).

Table 1 shows the Descriptive Statistics of

Perceptions Towards Training and Development.

Significance levels: p < 0.05

ANOVA test (F = 18.02, p < 0.001) confirmed

statistically significant differences in training

perception among job roles. The results suggest that

higher-level executives recognize training as a

strategic tool, whereas operational staff might view it

as an imposed requirement. Table 2 shows the

ANOVA Results.

Table 1: Descriptive statistics of perceptions towards training and development. (Source: author).

Job Role N Mean Std. Deviation

Executives 50 4.20 0.50

Supervisors 100 3.80 0.60

erational Staff 320 3.50 0.70

Total 470 3.68 0.68

Table 2: ANOVA results. (Source: Author).

Source Sum of Squares df Mean Square

Sig. (p-value)

Between Groups 14.23

7.115 18.02 0.000***

Within Grou

s 183.92 467 0.394

Total 198.15 469

Table 3: Descriptive statistics for training methods. (Source: author).

Training Type N

Productivity

Mean

Productivity

Std. Dev

Cost-Effectiveness

Mean

Cost-Effectiveness

Std. Dev

In-House 235 75.00 10.00 80.00 8.00

Outsource

235 68.00 12.00 70.00 10.00

Total 470 71.50 11.00 75.00 9.00

4.2 Hypothesis 2 (H02): In-House and

Outsourced Training Significantly

Impact Cost and Productivity

among Employees

Table 1 presents the descriptive data for In-House and

Outsourced training techniques, indicating that In-

House training yields superior outcomes. The average

Productivity score for In-House training is 75.00 (SD

= 10.00), whereas for Outsourced training it is 68.00

(SD = 12.00), signifying enhanced staff efficiency.

In-House training exhibits superior cost-

effectiveness, with a mean of 80.00 (SD = 8.00)

compared to 70.00 (SD = 10.00) for Outsourced

training. The aggregate mean ratings (71.50 for

Productivity, 75.00 for Cost- Effectiveness)

substantiate the overall superiority of In-House

training. The findings indicate that In-House training

facilitates organization-specific skill enhancement,

resulting in increased production and cost efficiency,

hence rendering it a more successful training

technique.

Table 3 shows the Descriptive Statistics for

Training Methods. Table 4 shows the Independent

Samples t-Test Results.

Table 4: Independent samples t-Test results. (Source:

author).

Test t-Statistic p-Value (Sig.)

Independent t-

Test for

Productivit

6.94 0.000***

Independent t-

Test for Cost-

Effectiveness

10.13 0.000***

Significance levels: p < 0.05

The independent t-test results indicate a

significant difference in mean productivity and cost-

effectiveness scores between employees trained via

in-house training and those trained via outsourced

training (p<0.001p < 0.001). In-house training yields

higher productivity (M=75.00M = 75.00) and cost-

effectiveness (M=80.00M = 80.00) compared to

outsourced training (M=68.00M = 68.00, M=70.00M

= 70.00, respectively).

Figure 1 shows the Structural

Equation Modelling (SEM) Analysis.

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Figure 1: Structural Equation Modelling (SEM) analysis

Table 5: Structural Equation Model (SEM) regression

analysis for productivity. (Source: author)

Predictor

Variable

Coefficient

(B)

Std.

Error

Statisti

p-Value

Intercept 68.19 0.695 98.08

0.000**

Training

Type (1 =

In-House, 0

Outsourced)

6.82 0.983 6.94

0.000**

Table 6: Structural Equation Model (SEM) regression

analysis for cost effectiveness. (Source: author)

Predictor Variable

Coeffi

cient

(B)

Std. Error t- Statistic p-Value

Intercept 71.24 0.581 122.70 0.000***

Training

Type

In-House,

Outsourced)

8.32 0.821 10.13 0.000***

The data indicates that Training Type

significantly affects both Productivity and Cost-

Effectiveness. In-house training enhances

productivity by an average of 6.82 points relative to

outsourced training, with a highly significant p-value

(p < 0.001). Furthermore, in-house training improves

cost-effectiveness by 8.32 points, rendering it a more

economically advantageous choice for enterprises (p

< 0.001). The elevated R² values indicate that

Training Type has a more robust correlation with

Cost-Effectiveness than with Productivity.

Training Type accounts for 18.0% of the variance

in Cost-Effectiveness, indicating a significant

influence, however it explains just 9.3% of the

variance in Productivity, implying that other factors

may enhance productivity. The graphical SEM

portrayal corroborates these findings, demonstrating

a much-pronounced direct effect of Training Type on

Cost-Effectiveness. This indicates that firms

choosing in-house training experience substantial

cost reductions. Simultaneously, the modest

relationship between Training Type and Productivity

suggests that while in-house training enhances

productivity, additional external or internal factors

may also influence total efficiency.

Figure 2 shows the Structural Equation Model

(SEM) Illustrating the Relationship Between Skill

Gap, Training Effectiveness, and Productivity. Table

5 shows the Structural

Equation

Model

(SEM)

Regression

Analysis

for

Productivity. Table 6

shows the Structural Equation Model (SEM)

Regression Analysis for Cost Effectiveness.

Figure 2: Structural Equation Model (SEM) illustrating the

relationship between skill gap, training effectiveness, and

productivity.

Table 7: Structural Equation Model (SEM) regression

analysis for training effectiveness. (Source: author)

Predictor

Variable

Coeffici

ent (B)

Std.

Error

Statisti

p-Value

Intercept -2.366 0.107 -22.05 0.000***

Skill Gap

Score

0.657 0.024 26.96 0.000***

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Table

Structural

Equation

Model

(SEM)

Regression

Analysis

for

Productivity. (Source: author)

Predictor

Variable

Coefficien

(

)

Std.

Erro

t-Statistic p-Value

Intercept 3.898 0.024 160.57 0.000***

High Skill Gap 0.926 0.034 26.96 0.000***

Structural Equation Modeling (SEM) analysis

shows how Skill Gap affects Training Effectiveness

and Productivity. Statistically significant coefficient

(B = 0.657, p < 0.001) suggests that training efficacy

becomes increasingly important in bridging

workforce deficits as skill gaps expand. Skill Gap and

Productivity strongly correlate (B = 0.926, p < 0.001),

indicating that larger skill gaps diminish workplace

efficiency and highlight the need for targeted skill

development activities. The model explains 60.8% of

Training Effectiveness and Productivity variance,

proving its robustness. The graphical SEM shows

direct impacts, emphasizing strategic actions. The

stronger path from Skill Gap to Training

Effectiveness suggests that firms with larger gaps

should prioritize effective training to improve worker

competency. The direct but significantly lower

influence on Productivity implies that while

narrowing skill gaps will boost efficiency, other

factors may also affect workplace performance.

These findings emphasize the relevance of systematic

training in improving skill levels and organizational

productivity. Table 7 shows the Structural Equation

Model (SEM) Regression Analysis for Training

Effectiveness. Table

8 shows the Structural

Equation

Model

(SEM)

Regression

Analysis

for

Productivity.

5 DISCUSSION

These findings are consistent with the literature on the

effectiveness of different types of training on skills

gaps and workforce development strategies. The

emphasis is on the fact that training greatly enhances

the enthusiasm and a sense of contribution of the

employees (Diamantidis, A. D., & Chatzoglou, P,

2019). A study found by RSP confirms this claim, as

those who took part in the company’s in-house

training showed an increase in productivity and

motivation. This shows organized internal training

programs not only increases operational efficiency

but also increases staff morale and participation.

Elmuti, D., & Kathawala, Y (2000) stated that despite

outsourced training provides special same

knowledge, it adds to operating expenses. Conducting

the training in-house has cost-benefit tradeoffs. The

current study at RSP supports this assertion with

outsourced training being less cost effective (M =

70.00, SD = 10.00) than their in-house training (M =

80.00, SD = 8.00).

This reflects the strategic guidance to enterprises

to develop in-house expertise while selectively

utilising out-sourced training - especially when it

comes to attaining technology-driven capabilities. In

a study by (Shih et al., 2011) employees

hierarchically differed in their impressions of

training, with CEOs generally holding training in

higher regard than lower-level employees. The

ANOVA results of this study substantiate this trend,

revealing significant differences in impressions of

training by occupational types (F = 18.02, p = 0.001).

Highlighting the need that role-based trainings suited

for all levels of employees be put into place to ensure

relevancy and involved development. Distinguishing

between generic and firm-specific training, Galanaki

et al., 2008 noted that generic training is most suitable

for outsourcing while firm-specific training is used

best in-house. This aligns with the data from RSP, in

which workers preferred in-house training focused on

corporate goals, while outsourced training

emphasized technological learning. This suggests that

a blended training model a tuition model that is a

combination of internal and outside training can

potentially maximize skill absorption while still

preserving cost efficiency. Talent shortages that are

left unaddressed can therefore have an important

impact on performance, (Chhabra 2021), which

looked at the effects of skills gaps on production and

organizational competitiveness. Structural Equation

Modeling (SEM) analysis of this study provides

support for this statement with a direct path from skill

gaps to training efficacy (B = 0.657, p < 0.001).

These findings highlight the importance of targeted

upskill programs to fill skill gaps and enhance

employee performance. Mayombe, C (2020)

emphasized how much good training design relies on

a needs analysis. The current study found that RSP

could not perform organized skill gap analysis that

has resulted in uneven training outcomes. It

highlights the importance of a systematic approach to

assessing workforce training requirements, which

enables skill-development activities to be aligned

with organizational objectives and employee needs.

5.1 Recommendations

The study shows that to save costs and make it

personalized, focus should be on in-house training at

Rourkela Steel Plant (RSP) along with the betterment

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of internal training, introduction of periodic and

systematic mentoring, and using digital learning

platforms for providing cost-effective training

solutions. Design a blended learning design for core

competencies, incorporate outsourcing for high-tech

advancements, incorporate both online and in-person

trainings, and partner with academic institutes for

external endures. Create valuable training tailored to

unique programs for different job positions, such as

best practices for strategic leadership, process

optimization, safety management, and competency

development.

5.2 Limitation

Key insights on training effectiveness, cost

effectiveness and skill gaps from the study of

Rourkela Steel Plant (RSP) Particularly, its

limitations include limited generalizability, cross-

sectional study design, positivity bias in self-reports,

limited exploration of training delivery methods, and

narrowed skill gap consideration. The study applies

only to RSP and does not necessarily apply to other

core workforce configurations or operating

methodologies at other steel plants. The study relies

on self-reported questionnaires and assessments and

is therefore subject to social-desirability bias. Future

study may integrate technology-augmented training

methodologies and assessments of on-the-job

training. Moreover, competency-based assessments

would yield a more accurate appraisal of training

efficacy.

6 CONCLUSIONS

This study establishes a fundamental comprehension

of training efficacy in the steel sector; yet, additional

research is necessary to rectify deficiencies, enhance

applicability, and integrate developing technology

into workforce development programs. Expanding

research parameters, employing objective skill

evaluations, and incorporating technology-based

learning strategies will improve training methods and

guarantee sustained enhancements in workforce

efficiency in future studies.

REFERENCES

Aguinis, H., & Kraiger, K. Benefits of training and devel-

opment for individuals and teams, organizations, and

society. Annual Review of Psychology, 60, (2009) 451-

474.https://doi.org/10.1146/annurev.psych.60.110707.

163505

Akyazi, T., del Val, P., Goti, A., & Oyarbide, A. Identifying

future skill requirements of the job profiles for a

sustainable European manufacturing industry 4.0. Re-

cycling, 7(3), (2022). 32. Retrieved from

https://www.mdpi.com

Akyazi, T., Goti, A., & Báyon, F. The effects of Industry

4.0 on steel workforce: Identifying the current and fu-

ture skills requirements of the steel sector and devel-

oping a sectorial database. Industry 4.0 and the Road to

Manufacturing Sustainability. (2024). Retrieved from

https://library.oapen.org

Antonazzo, L., & Stroud, D. Institutional complementari-

ties and technological transformation: IVET respon-

siveness to Industry 4.0—meeting emerging skill needs

in the European steel industry. Economic and Industrial

Democracy. (2023). Retrieved from

https://journals.sagepub.com

Antonazzo, L., Stroud, D., & Weinel, M. Preparing for a

digital steel industry: What challenge for skills for-

mation systems? Industry 4.0 and the Road to Manu-

facturing Sustainability. (2024). Retrieved from

https://library.oapen.org

Brewster, C., & Mayrhofer, W. Handbook of Research on

Comparative Human Resource Management. (2012).

Edward Elgar Publishing.

Chhabra, S. The fruitful training. (2021) Universal Journal

of Business and Management.

Diamantidis, A. D., & Chatzoglou, P. Factors affecting

employee performance: An empirical approach. Inter-

national Journal of Productivity and Performance

Management, 68(1), (2019)171–193.

https://doi.org/10.1108/IJPPM-01-2018-0012

Elmuti, D., & Kathawala, Y. The effects of global out-

sourcing strategies on participants’ attitudes and or-

ganizational effectiveness. International Journal of

Manpower, 21(2), (2000) 112–128.

https://doi.org/10.1108/01437720010331027

Fareri, S., Apreda, R., Mulas, V., & Alonso, R. The worker

profiler: Assessing the digital skill gaps for enhancing

energy efficiency in manufacturing. Technological

Forecasting and Social Change, 194, (2023). 122146.

Retrieved from https://www.sciencedirect.com

Galanaki, E., Bourantas, D., & Papalexandris, N. A deci-

sion model for outsourcing training functions: Distin-

guishing between generic and firm-job-specific training

content. The International Journal of Human Resource

Management, 19(12), (2008). 2332–2351.

https://doi.org/10.1080/09585190802479535

Heraty, N. (1992). Training and development—a study of

practices in Irish-based companies. University of

Limerick.

Jehanzeb, K., & Bashir, N. A. Training and development

program and its benefits to employee and organization:

A conceptual study. International Journal of

Business and Management,8(2), (2013). 243

250.https://www.researchgate.net/publication/2747039

Inâ

SHouse versus Outsourced Training: An Analytical Study of Cost and Productivity at Rourkela Steel Plant, Odisha

809

Kavanagh, M. J., & Thite, M. Human resource information

systems: Basics, applications, and future directions.

(2009). SAGE Publications.

Maldonado-Mariscal, K., Cuypers, M., & Götting, A. Skills

intelligence in the steel sector. Machines, 11(3), (2023)

335. Retrieved from https://www.mdpi.com

Mayombe, C. Needs assessment for vocational skills train-

ing for unemployed youth in eThekwini Municipality,

South Africa. Higher Education, Skills and Work-

Based Learning, 11(1), (2020) 18–33.

https://doi.org/10.1108/HESWBL-02-2019-0032

Namadi, S. Strategic management of outsourcing: Balanc-

ing profitability and cost control in corporate opera-

tions. Journal of Business and Economic Options.

(2023). Retrieved from http://resdojournals.com

Noe, R. A. Employee Training and Development (7th ed.).

(2017). McGraw-Hill Education.

SamGnanakkan, S. Mediating role of organizational com-

mitment on HR practices and turnover intention among

ICT professionals. Journal of Management Re-

search, 10(1),(2010)124136.https://www.indianjournal

s.com/ijor.aspx?target=ijor:jmr&volume=10&is

sue=1&article =004

Shaheen, M., Azam, M. D. S., & Soma, M. K. A compe-

tency framework for contractual workers of the manu-

facturing sector. Industrial and Commercial Training,

51(4), (2019). 202-

218.https://www.emerald.com/insight/content/doi/10.1

108/ict-10-2018- 0080/full/html

Sharma, P., & Mishra, K. The impact of training on em-

ployee performance in the manufacturing sector. In-

ternational Journal of Management Studies, 6(2),

(2019). 45-61.

Shih, H., & Chiang, Y. Exploring the effectiveness of

outsourcing, recruiting, and training activities, and the

prospector strategy’s moderating effect. The Interna-

tional Journal of Human Resource Management,

22(1), (2011) 163–180.

https://doi.org/10.1080/09585192.2011.538973

Thirkell, E., & Ashman, I. Lean towards learning: Con-

necting Lean Thinking and human resource manage-

ment in UK higher education. The International Journal

of Human Resource Management, 25(21),

(2014). 3011-3025. https://doi.org/

10.1080/09585192.2014. 948901

Ulrich, D. Human resource champions: The next agenda for

adding value and delivering results. (1996) Harvard

Business School Press.

William, B., & Okafor, C. Outsourcing HR activities for

organizational efficiency in selected firms in Lagos,

Nigeria. SSRN Electronic Journal. (2024). Retrieved

from https://papers.ssrn.com

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