Does Knowledge Retention Mediate Training Content,Training Needs Analysis on Sustainable  Development in Oman Higher Education Institution?

Abstract

To date, little research has examined the human resources side of sustainability. To bridge this gap, we examined human resource management (HRM) practices and sustainable development in the micro-level higher education context in Oman. Quantitative research was used to test the predictors of sustainable development. We received 347 responses from employees working in 10 higher education institutions (HEIs) in Oman. The structural as well as measurement model was calculated using SmartPLS. The result showed that training is a unique source of creating sustainability. The mediating effect of knowledge retention was found to play a significant role in this relationship. We found that many HEIs need to do more to make employees understand the importance of their contribution to the achievement of this goal. HEIs play a significant role in the development as well as implementation of sustainable practices. Significantly, we enrich the understanding of the emerging universal wave of sustainability by identifying how vital HRM practices impact sustainable development from an academic and professional perspective. The study is restricted to Oman, but the research impact and applicability may be conducted in another environment or sectors. Sustainability and knowledge retention in HEIs are paramount issues for everyone.

Keywords

Sustainable development training content training needs analysis knowledge retention

Introduction

Sustainable development has become a major issue in the global economy. Notwithstanding the gains accrued by businesses, organizations are blamed for creating social as well as ecological harm. Till date, the attention of the majority of studies on sustainable development is studied at the organizational level viewpoint, like the study on natural resources (Appelbaum, 2014), formal structures, systems, processes, certifications (Hu & Wall, 2012), sustainable development, and financial performance (Albertini, 2013). Therefore, the large-scale orientations of sustainable development have been well explored while the micro-orientations have been fundamentally overlooked. Previous studies have observed that there is a lack of research on how micro-level mechanisms, such as human resource (HR) practices, influence the achievement of sustainability objectives of an organization (Carmeli et al., 2017; Del Giudice et al., 2022). A study by Xing and Starik (2017) also highlighted the decline of studies on social drivers of sustainable development, particularly on knowledge retention as well as training. The few studies that have examined sustainable development in publicly listed organizations mostly pay attention to sustainable development practices of New Zealand organizations (Menon et al., 2007). In view of the above, Strauss et al. (2017) suggested the need for researchers to explore how these micro-level factors play a critical role in helping organizations confront sustainable development challenges. Other researchers, such as Cooper et al. (2017), have directed attention to the interlinking micro-level mechanisms that produce macro-level situations as well as convert higher-level factors into individual behavior that is valuable to the organization (Carmeli et al., 2017). The present research is intended to fill the void between knowledge retention and sustainable development in the Gulf Cooperation Council (GCC); such research that explores knowledge retention and sustainable development in higher education institution (HEI) is essential due to the death of study in this field mainly in the Sultanate of Oman. HEI plays a critical role in translating the individual behavior that will impact organizations’ long-term goals and change attitudes toward sustainability and supporting the systems (Wang et al., 2014). According to Sustainability Development Goals 4-Quality education, the related thematic area 4.3 is the future of work (ILO, 2016a, 2016b). The future of work initiatives would fully involve International Labor Organization (ILO) ideology for all sectors, particularly the academic world. However, many countries have not fully embraced this new change and are affecting social values. The actions taken now will decide if the regaining policies by countries will help to meet the current need without compromising future needs. HEI has a critical responsibility in achieving this goal, as defined by sustainable development goals.

HEI play a vital role in in achieving sustainable development by helping to develop new knowledge and and ideas that would help to have a clearer understanding (Findler et al., 2019). HEIs can help today, and tomorrow’s leaders can make a substantial impact on the transformation of society and create a whole-institutional approach, transforming themselves (Mulder, 2010; Rieckmann, 2018). Investing in people is more urgent since people make the most significant contribution to implementing sustainable development. Though most nations have progressed upward in the human development category, many are still far behind within the human development index (HDI) group (United Nations Development Programme, 2018). Accordingly, researchers have emphasized that the business case for sustainability needs to be connected to HRs (Maslennikova & Foley, 2000; White & Lean, 2008). The transition of this change can be achieved through an effective knowledge retention strategy. Knowledge retention is a significant responsibility of organizations in the twenty-first century as it remains the avenue for achieving sustainability (PricewaterhouseCoopers, 2012; Schuler et al., 2011) and is vital to stay competitive in a changing business setting (Al-Hussaini et al., 2019) because knowledge is a critical asset that underpins and nourishes organizational survival as well as productivity (Tseole & Marutha, 2022). Hence, knowledge retention is key in ensuring sustainability in HEI as the majority of HEI are currently faced with the risk of knowledge loss due to the global COVID-19 pandemic. Knowledge retention would ensure that the training employees received is not lost. Previous studies have shown that employee turnover is a major driver of knowledge loss within organizations (Durst & Zieba, 2019; Massingham, 2018; Sumbal et al., 2020). When this costly and important tacit knowledge is lost, the quality education output of the organization will also disintegrate. In addition, HEI will face the difficulty of continuing with its sustainable development programs. This thus directs the need for this study, specifically knowledge retention as a mediating factor. Orlitzky et al. (2003) recognized both internal as well as external advantages attained by organizations because of mediating variables, resulting in a competitive advantage for the organizations. Hence, the aims of this research are fourfold: (a) To test the impact of training content, training needs analysis on knowledge retention; (b) to examine the relationship between knowledge retention and sustainable development; (c) to examine the mediating role of knowledge retention on the relationships between training content and training needs analysis on sustainable development; and (d) to understand the essential construct between training needs analysis and training content in understanding knowledge retention using importance-performance matrix analysis (IPMA).

Literature Review

Knowledge Retention (KR)

Knowledge management (KM) has remained an attractive stream of study over the past decade. KR is part of KM that ensures organizations do not lose the knowledge entrenched in employees who quit from the organization (Annosi et al., 2021; Nair & Munusami, 2019). Knowledge retention, otherwise referred to as knowledge continuity, is the storage of knowledge inside the organization to be regained and utilized later (Levallet & Chan, 2019; Wikström et al., 2018). Mat Nor et al. (2020) also see knowledge retention as actions executed to increase the inner flow of knowledge inside an organization. Motshegwa (2017) defined knowledge retention as involving the action of concentrating on the key knowledge that an organization is at the risk of losing. According to the resource base view (RBV), an organizational competitive edge depends on the organizational inimitable combination of physical, organizational, as well as human assets (Butt et al., 2020; Chen et al., 2016; Farooq, 2019). An asset can be qualified as a source of competitive advantage if it is profitable, rare, unique, as well as complex to replace. Knowledge is one of the most critical drivers of economic development (Massingham & Massingham, 2014). Hence, organizations are required to put in place different mechanisms to retain key knowledge before the people possessing such knowledge exit the organization (Adobor et al., 2019). Knowledge retention can be achieved by utilizing a collection of different retention approaches or designs such as mentoring, exit interviews, communities of practice, job shadowing, storytelling as well as job rotation (Jeske & Linehan, 2020).

Though the primary issue in human resource management (HRM) research is whether there exists a comprehensive collection of regulations that serve as a single method of personnel administration and are connected to employee retention, much research on employee retention across different industries and its connection to HRM practices has been conducted. Levallet and Chan (2019) and Ensslin et al. (2020) emphasized the significance of knowledge retention in achieving sustainable organizational competitive advantage; hence, organizations are responsible for recognizing, securing, managing, transferring, exploiting, as well as retaining vital knowledge. A similar study by Dei and van der Walt (2020) argued that organizations need to focus on knowledge retention practices as well as strategies and channeling their knowledge to specifically focus on exploiting their intellectual capital. Since employee turnover is a significant concern for organizations, organizations with good HR policies can lower this ratio and boost sustainable competitiveness (Al-Twal, 2022). Branham (2005) added that the reason employees leave is strongly linked to HR activities. In view of the above, a thorough understanding about the link between HRM and employee loyalty will assist organizations in making the best choices to achieve their goals while generating the highest possible profits (Allui & Sahni, 2016). Organizations are discovering more and more that staff retention is a strategic theme that offers a long-term competitive advantage (Allui & Sahni, 2016). Therefore, organizations can successfully retain their capable personnel by implementing an all-encompassing retention strategy with the assistance of pertinent HRM programs (Al-Twal, 2022).

Knowledge is a valuable resource that can provide a sustainable competitive advantage for an organization (Grant, 1996). Organizations are not forced to retain all knowledge notwithstanding employees’ desires because retaining all knowledge will generate overload and confusion for the organization. Evaluating the knowledge and deciding what is appropriate afterward is relevant to determining how to retain the valuable knowledge (Ugheoke et al., 2021). It is important to retain this knowledge to use the rich expertise and achieve sustainability (Ugheoke et al., 2021). Failure to transfer knowledge from older workers to younger workers will negatively affect the economy (Stam, 2009). These developments will result in a “talent gap” (Arnone, 2006) and thereby threaten organizations’ ability to achieve sustainability and economic competitiveness (Slagter, 2007), resulting in just an economy with physical inputs and natural resources rather than a knowledge-based economy (Walter & Snellman, 2004).

Hence, we propose:

H₃: Knowledge retention has a positive influence on organizations’ attainment of sustainable development.

H₄: Knowledge retention mediates the influence of training content on sustainable development.

H₅: Knowledge retention will mediate the influence of training needs analysis and sustainable development.

Training Needs Analysis

Training is an essential cost-effective investment for every organization on the condition that the training is carried out to align and complement organizational requirements and goals (Denby, 2010). Training improves the capacity of existing skills within the labor force to improve organizational efficiency and effectiveness. One of the major reasons training fails to deliver the required result is due to the failure to suit the needs of the organization (Van Eerde et al., 2008). Training is conducted to add value to organizational needs and goals; however, training needs analysis is the precondition to any training investment (Shah & Gopal, 2012). Hence, training needs analysis is an integral part of any training cycle. Training needs analysis is an effective organizational approach that prepares the organization’s HR for sustainable growth, inescapably change, and gives them the opportunity to enhance technology, system, and the nature of work (Shah & Gopal, 2012). It is essential that training investment is strengthened with explicit knowledge of organizational needs (Denby, 2010). Guthrie and Schwoerer (1994, 1996) argued that self-evaluated training needs can be scientifically influenced by elements outside of actual needs. For instance, those in later career phases have less training self-efficacy, less training utility, as well as a lesser need for management training (Guthrie & Schwoerer, 1994, 1996). Chiu et al.’s (1999) argued that 87% of the needs evaluations were initiated by trainers, indicating a supply-led approach to training needs analysis. An efficient approach to training needs analysis involves determining the job requirements, needed skill levels, as well as the current skill levels of the employees involved (Van Eerde et al., 2008). But very limited research on training included a needs assessment (Arthur et al., 2003), and they found that training needs analysis has a positive effect on size.

Training needs analysis is a logical assessment and analysis of the organization’s current and expected performance level, concentrating intensely on the capability of the organizational workforce and the supportive network (Denby, 2010). Training needs analysis is the first phase of the training procedure, whereby the needs are recognized and positioned based on the organizational cost to meet the needs (Leskiw & Singh, 2007). Training needs analysis is a thorough examination involving two stages. First is the diagnostic stage, which identifies the performance and competency level discrepancies. The second stage is to match the performance differences with competencies by ranking them according to the order of role and organizational requirements (Shah & Gopal, 2012). Every training requires an effective assessment process (Denby, 2010). It is inaccurate to conduct a training program that is short of an audit procedure already developed into the process (Denby, 2010). Therefore, an appropriate training program should be planned, executed, and most significantly monitored and assessed in the long term to demonstrate the effectiveness of investment (Denby, 2010). The implication is that training needs to focus on the job responsibilities and the tasks people undertake. Organizations are the leading focal point of training needs analysis (Bowman & Wilson, 2008). A study by Bee and Bee (2003) highlighted that organizational needs should be the central focus in any training needs to close performance differences. Training needs analysis increases management commitment to sustainability, offers the most significant utilization of scarce resources, and assists in formulating strategies (Shah & Gopal, 2012). Without training needs analysis, the important budget will be wasted on unnecessary coaching and guidance, which will not produce a positive return on investment via the delivery of a positive outcome on the bottom line (Cekada, 2010). Training needs analysis enables the evaluation process to be uncomplicated and effective, supporting the organization and employees to evaluate the service’s success (Eighteen, 1999). Based on the above arguments, we propose:

H₂: Training needs analysis will be positively related to knowledge retention.

Training Content

Training content consists of the facts, ideas, theories, and standards taught and learned in a particular course, rather than related skills. It comprises how the trainer communicates clear instructions with the useful application of the training (Ghosh et al., 2011). Training should be enhanced with well-designed content to match various training needs (Schraeder, 2009). Training content is critical to the effectiveness of training to prevent the bias and perception of the trainee about the training program prior to the commencement of the training. Therefore, for training to accomplish its goals, the content of the training is a significant element for HRM (Ghosh et al., 2011). Harris et al. (2014) established that trainers with suitable teaching styles motivate trainees to enhance job demand, offer meaningful feedback, and monitor learning performance. Accordingly, organizations must be ready to utilize various instructional techniques to adapt to trainee needs and content (Harris et al., 2014). The approaches provide an opportunity to make trainees accountable for the transfer of knowledge (Burke & Saks, 2009). Andoh et al. (2022) argued that training content is a significant part of any training process without this, training cannot take place. Ford et al. (2018) added that training content is essential for training transfer. Hence, for meaning training process to take place we must pay attention to training content (Blume et al., 2010). Huang et al. (2015) further asserted that highly linked training content offers trainees the capability to transfer training. Abdul Aziz (2015) and Kraiger and Ford (2021) found that training content can result in declarative knowledge, skill acquisition, procedural knowledge, as well as knowledge retention. Thus, it is proposed that:

H₁: Training content significantly impacts knowledge retention.

Sustainable Development

Sustainable development has remained a significant attention for practitioners, academicians, as well as policymakers globally. Sustainability is not just about environmentalism. It has been embedded in many definitions as social equity as well as economic development. “The Rio Earth Summit,” which brings together representatives from more than 170 countries, created a critical understanding of sustainable development conversation as well as set a standard for understanding sustainable development. This development transferred the debate of sustainable development from a national perspective to a global viewpoint (United Nations, 1997). Moreover, it incorporates economic, social, as well as environmental issues and provides them equal weightage. Perhaps the first formal acknowledgment that human action had serious consequences for the current as well as future humanity of the planet. The Brundtland Report describes sustainable development as the development that meets the current needs without compromising the ability of future generations to meet their own needs (United Nations World Commission on Environment and Development, 1987, p. 8). This definition makes the understanding of sustainable development subjective because of its failure to specifically highlight the needs to be met nor the approach to accomplish sustainability; as such, it leads to an overabundance of meanings of sustainable development, which are fundamentally divergent (Raar, 2007). This lack of universal definition has resulted in the challenge in the measurement of sustainability indicators (Searcy et al., 2005; Wang, 2005), which characterizes the main obstacle to the implementation of sustainable development plans (Veleva & Ellenbecker, 2001), as well as energizes the need to define universal standard approach as well as measurements (Warhurst, 2002). However, once sustainable development is joined to the global objective, the language becomes vague; the objective continually “sustainable development” itself (Hilty, 2001; Robèrt et al., 2004). Researchers are mostly split on whether sustainable development goals are suitable (Chatterjee, 2011; Marcuse, 1998; Phillis & Andriantiatsaholiniaina, 2001; Pitcher & Pauly, 1998; Solow, 1993). The crux of this disagreement is that verbal statements about sustainability are truly just trains of view focusing on a specific encyclopedic understanding; hence, sustainable development from this perspective is a means, not a goal (Zinken, 2004).

Moreover, Chams and García-Blandon (2019) argued that sustainable development is crucial for most organizations. According to the resource-based view, organization-specific assets as well as capabilities play a significant role in the development of competencies required to achieve sustainable goals (Tripathi et al., 2019). In light of the above, sustainable development is the result of organizational resources, which are largely defined as “anything that can be a force or vulnerable to an organization” (Wernerfelt, 1984). Considering the resource-based view, we are proposing that knowledge retention with training is a building block for any organization. Understanding these elements is key for organizations to attain sustainable development. To attain sustainability, organizations are required to plan for as well as expect changes and actions required by employees (Young et al., 2015). Hence, integrating sustainable programs into an organization’s view would affect several organizational activities including HRM (Lopez-Cabrales & Valle-Cabrera, 2019; Sarvaiya et al., 2018). Within the context of HRM, the standard expectation is that policies and practices that back the achievement of sustainable goals are to be established (Macke & Genari, 2019). In view of this, Ehnert et al. (2016) define sustainable HRM as “the implementation of HRM policies as well as practices that permit the attainment of financial, social, as well as ecological goals, with an influence inside and outside of the organization and for a long-term horizon while controlling for unintentional side effects and negative feedback.” If organizations properly utilize their HRs in a viable way, employees will maximize their ability in their respective job responsibilities and thrive innovatively. For any organization to effectively achieve sustainable growth, it must have the ability to formulate all-inclusive sustainable plans and transform such plans into appropriate organizational structures (Wolf, 2013). Creating a sustainable workforce is necessary for every company that aims to generate effective results (Craig, 2018) because sustainable employees will facilitate the attainment of sustainable competitive edge for the organizations (Craig, 2018). Such capability assists companies in understanding as well as coping with difficulty and improving their performance (Banerjee & Bonnefous, 2011; Epstein & Widener, 2011). Organizational leaders must develop specific skills to recognize and integrate shareholders to effectively achieve sustainable goals (Lee & Klassen, 2008).

Research Methodology

One of the most significant interests of this study is the environment in which it was conducted. The research was conducted in the Sultanate of Oman, a fast-developing country in the GCC. Oman aims to achieve sustainable development goals by 2040, with the government making a great effort to improve human capital. Little is known about sustainability research in this context. The research is a quantitative approach. A quantitative approach is essential because of the confidentiality of the respondents and subsequent valid responses. The study population was limited to HEI in the Sultanate of Oman. We identified the population of the study to be academic and administrative staff of the 10 best colleges and universities in the Sultanate of Oman, according to Unirank. Besides, the 10 HEIs were selected because they have taken a more active role in their commitment to education for sustainable development activities using the United Nations sustainable development goals framework. The selected institutions have also entrenched the top five sustainable development goals into their undergraduate teaching.

We conducted power analysis utilizing G*Power 3.1.9.2 software package (Faul et al., 2007) to decide on the sample size of this study. The multiple-power statistical analysis indicated that a sample of 187 is suitable for this research. However, we consider the possible threat of non-response bias and know that a larger sample size will reduce the likelihood of bias; hence, we decided to increase the sample size to 324. A stratified sampling was used to select 324 respondents because it ensures that every subgroup within the population is appropriately represented in a sample. We first sought and received permission from the HR department in the 10 institutions to access the list of all academic and administrative staff of the universities. We divided the population into homogeneous groups called strata, considering the shared characteristics of the sample. After stratifying each member of the population into subsections, we applied random sampling techniques to select participants from each stratum randomly. Each stratum was formed based on shared attributes such as academic and administrative positions, gender, and work experience. We assigned a consecutive number to each of the employees in each stratum. Afterward, we randomly selected a number from each stratum in proportion to the stratum size according to the population. The subsets of the strata were then pooled to form a random sample. Finally, we combine all strata into one to have an accurate representative sample of the entire population. The data collection took over 1 year due to the global pandemic and was collected through Google Forms sent to the respondents online.

A closed-ended questionnaire was used in this study. We adopted sustainable measures from the research conducted by Dimitrov and Davey (2011). Training needs analysis was measured through four items designed based on the study by Van Eerde et al. (2008). The first two items capture whether training is connected to the job and departmental goals. The other two items addressed the perceived utility of training for current and future job requirements. Knowledge retention was measured based on the following: Gold et al. (2001) proposed knowledge acquisition, knowledge conversion, application, and protection. Instruments on training content have been adopted from the study conducted by Waldeck and Leffakis (2007). The survey was sent to the respondents of 10 higher institutions. The respondents were contacted by telephone to seek their consent to participate prior to administering the survey. The statements seeking the opinion of respondents on various parameters of the training needs analysis, training content, knowledge retention, and sustainability were based on a 5-point Likert scale from 1 strongly disagree to 5 strongly agree.

Data Analysis

This article employed PLS modeling applying SmartPLS 3.2.8 version (Hair et al., 2021) to test both measurement as well as structural models. As the research utilizes a complex model with mediation, SmartPLS is more suitable to test these relationships. Henseler (2018) highlighted the benefit of utilizing partial least squares structural equation modeling (PLS-SEM): The PLS-SEM can use a small sample size, and PLS-SEM is better than regression analysis in evaluating meditation.

Measurement Model

The internal consistency of all variables was measured via composite reliability (CR). In Table 1, based on Hair et al. (2021), the CR values for all variables were above 0.7 and show sufficient internal consistency. According to Hair et al. (2021), most item loadings are greater than 0.70 to achieve convergent validity (Hair et al., 2021). Refer to Figure 1, the average variance extracted (AVE) is greater than 0.5, as shown in Table 1. Therefore, it can be concluded that all variables showed sufficient evidence of convergent validity.

Table 1.

Results of Confirmatory Factor Analysis (CFA) for the Measurement Model.

Variable	Loadings	CR	AVE
Knowledge retention
KR1	0.757	0.883	0.653
KR2	0.847
KR3	0.823
KR4	0.803
Sustainable development
SD1	0.729	0.885	0.562
SD2	0.715
SD3	0.714
SD4	0.744
SD6	0.788
SD7	0.802
Training content
TC4	0.756	0.843	0.731
TC5	0.943
Training needs analysis
TNA1	0.894	0.890	0.730
TNA2	0.806
TNA3	0.861

Source: SmartPLS 3.2.8 version Output.

Note: AVE, average variance extracted; CR, composite reliability.

Figure 1.

Source: SmartPLS 3.2.8 version Output.

The discriminate validity was assessed using the heterotrait-monotrait ratio of correlations (HTMT) criterion. The HTMT between the two variables should be less than 0.85, as shown in Table 2 (Henseler et al., 2015). Therefore, the discriminate validity does not appear to be a major problem in this study.

Table 2.

Discriminant Validity Heterotrait-Monotrait Ratio of Correlations (HTMT).

	Knowledge Retention	Sustainable Development	Training Content
Knowledge retention
Sustainable development	0.823
Training content	0.792	0.826
Training needs analysis	0.840	0.789	0.794

Source: SmartPLS 3.2.8 version Output.

Structural Model

Hair et al. (2021) recommended that each independent construct in the inner model must be evaluated using a bootstrapping method for collinearity. Using resample of 5,000, Table 3 shows the variance inflation factor (VIF) values among predictors, which specify that all VIF values are less than 5 (Hair et al., 2021), thus ascertaining the absence of collinearity among the predictors (refer to Table 3).

Table 3.

Structural Model Assessment.

	Endogenous variables	R-squared		R-squared adjusted
R-squared	Knowledge retention	0.629	0.624	0.26: Substantial, 0.13: Moderate, 0.02: Weak effect (Hair et al., 2017)
R-squared	Sustainable development	0.547	0.544
	Exogenous variable	KR	SD
Effect size  (F-squared)	Training content	0.156		0.26: Substantial, 0.13: Moderate, 0.02: Weak effect (Hair et al., 2017)
	Training needs analysis	0.547
	Knowledge retention		1.208
	Exogenous variable	KR	SD
Inner VIF values	Training content	1.579		VIF < 5 (Hair et al., 2017)
	Training needs analysis	1.579
	Knowledge retention		1
	Endogenous variables	Q² (=1 – SSE/SSO)
Q-squared	Knowledge retention	0.395		A value higher than zero (0) shows  predictive relevance (Hair et al., 2017)
Q-squared	Sustainable development	0.290
	Test	Value
Summary of  model fit				<0.08
	SRMR	0.072
	d_ULS	2.219
	d_G	1.698
	Chi-square	1,996.293
	NFI	0.944		>0.90

Source: SmartPLS 3.2.8 version Output.

Table 3 reported the model fit test of the study. A structural model is considered a good fit if the standardized root mean square residual (SRMR) value is equal to or less than 0.08. Using model fitting parameters recommended by Hu and Bentler (1998), SRMR = 0.072 was lower than 0.08, the normed fit index (NFI = 0.944) was higher than 0.90, and the chi-square value is 1,996.293, which show that the structural model in this study has a good fit and reliable for further analysis.

Finally, following the recent suggestions by Shmueli et al. (2019), the article investigates the prediction of knowledge retention and sustainable development. From Table 4, the predicted values for all indicators are positive. Moreover, Table 4 indicated that all PLS results of the indicator show low prediction error in comparison to the benchmark of the linear model. Hence, the present research has established that the model has high predictive power (Shmueli et al., 2019).

Table 4.

Partial Least Squares (PLS) Predict Results.

	Linear Model Benchmark^a					PLS-SEM^a
	RMSE	MAE	MAPE	Q²_predict	RMSE	MAE	MAPE	Q²_predict
Knowledge retention
KR1	0.589	0.423	28.611	0.512	0.561	0.386	27.414	0.557
KR2	0.988	0.767	41.647	0.364	1.011	0.786	42.965	0.335
KR3	1.032	0.836	41.816	0.294	1.013	0.792	40.929	0.321
KR4	0.912	0.681	34.699	0.370	0.837	0.617	29.904	0.470
Sustainable development
SD1	0.996	0.796	41.690	0.280	1.014	0.806	40.950	0.254
SD2	1.083	0.916	46.053	0.232	1.119	0.925	46.238	0.179
SD3	0.967	0.803	37.367	0.184	1.000	0.819	37.953	0.128
SD4	0.913	0.717	39.182	0.291	0.914	0.730	38.417	0.290
SD6	0.649	0.494	31.546	0.539	0.578	0.342	20.315	0.634
SD7	0.637	0.494	31.375	0.581	0.637	0.000	0.000	1.000

Source: SmartPLS 3.2.8 version Output.

Notes: ^aWhen comparing the PLS-SEM results against the linear model benchmark, the bolded figures show where the prediction error is smaller. MAE, mean absolute error; MAPE, mean absolute percentage error; PLS-SEM: partial least squares structural equation modeling; RMSE: root mean square error.

Finally, this article applied the suggestion (Sarstedt et al., 2019) by introducing the new robust techniques and run a model, including quadratic effects (i.e., potential non-linear effects). The estimated coefficient for the quadratic effect is non-significant for knowledge retention ↓ sustainable development (β = –0.235; t = 0.0373; t = 0.793; p = .561), training content ↓ knowledge retention (β = 0.037; t = 0.567; p = .571) and training needs analysis ↓ knowledge retention (β = –0.020; t = 0.193; p = .847). Justifying linearity among the relationships.

The study also examines a number of hypotheses; therefore, the article must take endogeneity (Lathan, 2018) into consideration that might result from the variables left out of the PLS path model. The article used Park and Gupta’s (2012) Gaussian copula technique, applying Hult et al. (2018)’s criteria and using the construct scores of the pooled sample as input. According to the study, none of the Gaussian copulas is significant. A route coefficient estimate of –0.013 is obtained specifically by treating the training content features as potentially endogenous; however, this result is not significant (p value = .667). The Gaussian copula used for the training needs analysis has an estimated value of 0.01, which is not statistically significant (p value = .922). Finally, taking into account that the predictor construct for knowledge retention may be endogenous, results in non-significant copulas for the training content (–0.06; p value = .779) and the training needs analysis (–0.031; p value = .756). Thus, the study’s finding that endogeneity is absent confirms the robustness of the PLS-SEM results (Hult et al., 2018).

Hypothesis Testing

As shown in Table 5, the analysis established that knowledge retention positively and significantly predicts sustainable development (β = 0.74, t = 19.028, p < .01). As shown in Table 6, the analysis established that training content positively and significantly predicts knowledge retention (β = 0.302, t = 3.473, p < .01). As shown in Table 5 and Figure 2, the analysis established that training needs analysis positively and significantly predicts knowledge retention (β = 0.573, t = 7.378, p < .01).

Table 5.

Path Coefficient (Direct and Indirect Effects).

Relationships	Beta	SE	t-values	p Value	2.50%	97.50%	Decision
Direct effects
H₁: Training content ↓ knowledge retention	0.302	0.087	3.473	.001*	0.137	0.46	Supported
H₂: Training needs analysis ↓ knowledge retention	0.573	0.078	7.378	.000**	0.427	0.723	Supported
H₃: Knowledge retention ↓ sustainable development	0.740	0.039	19.028	.000**	0.670	0.814	Supported
Indirect effects
H₄: Training content ↓ knowledge retention ↓ sustainable development	0.223	0.064	3.517	.000**	0.102	0.345	Supported
H₅: Training needs analysis ↓ knowledge retention ↓ sustainable development	0.424	0.069	6.109	.000**	0.307	0.571	Supported

Source: SmartPLS 3.2.8 version Output.

Notes: **Significant at .01 (1-tailed), *significant at .05 (1-tailed). SE, standard error.

Figure 2.

Source: SmartPLS 3.2.8 version Output.

Table 5 reports the results of mediating effects of knowledge retention. As shown in Table 6, notwithstanding all the mediation results are significant, established on the beta values with t-values. The technique of bootstrapping with 5,000 resamples and a bias-correlated and accelerated confidence interval was used to test the indirect effect, which should not straddle a zero in-between (Hayes & Scharkow, 2013). In essence, knowledge retention mediates the relationship between training content and sustainable development [lower-level confidence interval (LLCI) = 0.102 and upper-level confidence interval (ULCI) = 0.345, p < .001]. Knowledge retention mediates the relationship between training needs analysis and sustainable development (LLCI = 0.307 and ULCI = 0.571, p < .001).

IPMA

The IPMA was enforced to understand the most important construct in the model. Figure 3 horizontally showed the result of the overall effects and vertically the index values for knowledge retention, where training needs analysis is important for determining knowledge retention due to its comparatively higher importance value (i.e., a high path coefficient) in comparison to training content.

Figure 3.

Source: SmartPLS 3.2.8 version Output.

Discussion

This study examined training needs analysis, training content, and sustainability: Mediating role of knowledge retention in the HEI. This section discusses the results obtained in Section ‘Data Analysis’ and attempts to develop strategies to improve sustainable development. From the results, we found that TNA and training needs analysis and training content are the keys to achieving sustainability in the HEI. Hence, organizations must build employees’ knowledge and skills to remain sustainable in advancing the economy, performance monitoring, holistic thinking, and action. With the growing interest by organizations to commit to sustainability development, adopting training needs analysis and training content will facilitate employee retention. Training content effectively closes organizational knowledge gaps between employees and where they need to be. Training content helps direct training to a specific skill or topic. This results in achieving different organizational goals while keeping employees engaged and their productivity high. When employees are recognized, working towards their growth and upgrading their skills, they will be motivated to work towards organizational progress and improve organizational productivity and results, tapping the employees’ curiosity and empowering them to share knowledge with others. When employees are provided with desired training, customers will benefit from positive changes, making them dependable and remain with the organization.

Following the growing global awareness of sustainable development, it is increasingly important for organizations to pay more attention to promoting sustainability of the physical and social environment. Because sustainability will help increase financial performance while at the same time promoting public support. Hence, managers are required to be conscious of global concerns and pay attention to organizational stakeholders. These objectives can only be realized by enhancing employees’ skills, mainly as sustainability has become an important key factor in buying decisions. Because customers can purchase from businesses conscious of their influence on society and their environment, sustainability enhances companies’ brand image. It offers them a competitive advantage over other competitors. Prioritizing training needs and training content in the HEI is critical because it impacts the organization’s decision-making quality. This can also provide external benefits to the organization by helping improve its stakeholder relationship and increase employer branding. To attain sustainable development, organizations must step up human capital development by implementing a universal approach to achieve the desired output. This implies that HEI needs to take a strategic methodology that connects training to the labor market needs and reduces skills mismatch to enhance human capital. To effectively achieve this, HEI needs to focus on prioritizing training, investment in human capital, and social development. Because human capital growth will positively affect sustainable economic growth, this connection depends on the approaches implemented at the national level. Thus, HEI must build their talent to develop skills that meet future requirements and assist in building new sectors of a future economy that is ultimately autonomous of oil. HEIs are capable of supporting graduates to achieve their abilities. However, failure to achieve this may result in a lifetime of social and economic crises. If action is taken now, it can help to make a planet where all students will be well-nurtured as well as prepared to acquire knowledge, a place that will help them to cultivate healthy, well-accomplished, productive adults; as well as where they have the opportunity to achieve their ability, a place where tomorrow’s employers will demand them, and it is the responsibility of today’s leaders to take action now.

According to the results we obtained, we also see that knowledge retention mediates these relationships. This article has contributed to the literature on sustainable development and HR practices by examining knowledge retention as a mediator differently than what has been examined previously by past research. The implication is that organizations need to recognize the significant role of employees in the attainment of sustainable development by increasingly encouraging them to consider knowledge retention as a win–win system to achieve sustainability. Knowledge retention can improve an organization’s quality of knowledge, trust, positive work engagement, employee motivation, and performance outcomes. Thus, HEI needs to create valuable knowledge retention plans to achieve sustainable development goals and the attainment of competitive edge. The result demonstrated that organizations need a unique strategy to retain knowledge, including a favorable learning environment with sustainable practices. Our result further indicated that training needs analysis, training content, and sustainability are interrelated due to knowledge retention. Senior management must be committed to knowledge retention to achieve sustainability because of its deep-rooted connection with the competency development in the organization.

Mentoring should be encouraging in organizational strategy to drive the development and retention of talent. HEI need to give special attention to retaining important knowledge and making comprehensive policies on the management of knowledge in the organizations because doing so will create massive value in the organizations’ sustainable performance. We deeply suggested that all HEIs establish a knowledge retention plan, provide important training, and ensure sustainable development practices are implemented. Knowledge is typically forfeited in an organization when senior employees quit the organization. Hence, HEI will face the difficulty of continuing with some or all of their sustainable development programs. The implication is that HEI will also lose much valuable knowledge, which is expected to provide the foundation for achieving sustainable competitive advantage. The knowledge that employees who quit the organization possess is important because it can result to memory deterioration in HEI. This can eventually make the recovery of this knowledge very challenging. As important stakeholder, there is a high risk to function based on logic or not to applying knowledge retention in any manner.

This study adds value to sustainable development and HRM study by filling two important gaps. First, the study examines core intangible benefits, including HR practices, to explain how organizations can achieve sustainable development. We recommended that organizations that implement these social practices would create rare, valuable, as well as incomparable resources and capabilities, with a significant positive relationship with all stakeholders. Second, by concentrating on something other than environmental features, as in many past studies, we clarify HR practices’ important roles in achieving sustainability. We illustrated that HR practices, directly and indirectly, impact sustainable development. The current research has important implications that spread to both industries and academics. From an academic view, the present research adds value to the literature on sustainable development by researching the mediating effect of knowledge retention on training content, training needs analysis, and sustainable development relationships. To the best of our knowledge, academic work has yet to be conducted to examine this type of relationship, particularly in the context of HEI in Oman. This research offers valuable insight to aid HR managers to make improvement to their retention strategy by integrating recognized or leading interventions. This understanding will inspire managers to adopt mentoring, strategic leadership, as well as knowledge sharing to advance or foster their employee’s capability or expertise as well as actualize intention to stay forth. Hence, managers need to invest in the identified HR practices to boost competency development, reap business benefits, and increase engagement and retention rates.

Conclusion

This study found that training needs analysis and training content are unique sources of sustainability in HEIs, and knowledge retention is an important strategy for achieving this goal. The present study is full of weaknesses that highpoint avenues for future research. The present research was restricted to a sample size of academic and administrative staff in the HEI. A single sector was chosen to avoid possible influences because of industry-specific or country-specific attributes. Nevertheless, the choice can restrict the generalizability of the findings of this study to other sectors or environments. The framework of this study may or may not be effective in another context. Future studies can reproduce the result of this study by examining whether hypotheses developed in Oman HEI can be confirmed in other settings.

Although a comparative analysis using a heterogeneous sample was conducted. Second, we focused on the relationship between training needs analysis, training content, and sustainable development, with knowledge retention as a mediator. Whether the external environment is a driver resulting in the implementation of sustainable development has not been undertaken in this study. Future research can test whether training effectiveness as a possible moderator can assist in explaining the missing relationship of HRM practices and sustainability. We recognize that other measures, like trust and organizational structure, can moderate sustainability. This study can be extended to another sector. A study on sustainability within small and medium-scale enterprises will be beneficial since there is a strong relationship between SMEs and large-scale organizations.

In most instances, the finished products of SMEs become the raw material of large-scale organizations or vis-à-vis. Furthermore, most of the countries’ SMEs contribute the majority to the GDP of the economies. Additionally, this research was focused only on knowledge retention, training needs analysis, and training content to achieve sustainability goals. Therefore, other researchers are required to conduct all-inclusive investigations to recognize more practices and design an extensive relationship to achieve sustainable development so that organizations can reap the advantage from academic research and effectively achieve sustainable development to protect the future generation.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iDs

Solomon Ozemoyah Ugheoke

Munir Shehu Mashi

Nitha Siju

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Does Knowledge Retention Mediate Training Content,Training Needs Analysis on Sustainable Development in Oman Higher Education Institution?

Abstract

Keywords

Introduction

Literature Review

Knowledge Retention (KR)

Training Needs Analysis

Training Content

Sustainable Development

Research Methodology

Data Analysis

Measurement Model

Results of Confirmatory Factor Analysis (CFA) for the Measurement Model.

Discriminant Validity Heterotrait-Monotrait Ratio of Correlations (HTMT).

Structural Model

Structural Model Assessment.

Partial Least Squares (PLS) Predict Results.

Hypothesis Testing

Path Coefficient (Direct and Indirect Effects).

IPMA

Discussion

Conclusion

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iDs

References

Does Knowledge Retention Mediate Training Content,Training Needs Analysis on Sustainable  Development in Oman Higher Education Institution?