Factors affecting the employability of private university graduates: an exploratory study on Bangladeshi employers

Abstract

Purpose

This paper aims to identify the factors that can affect the overall graduate employability (OGE) of the private university graduates of Bangladesh. The authors carefully selected six such employable factors after searching the existing literature. Those six factors: academic performance (AP), technical skills (TS), communication skills (CS), personality (PE), leadership & motivational skills (LMS); and teamwork and problem solving skills (TPSS), had been considered as the independent variables while OGE had been considered as the single dependent variable.

Design/methodology/approach

The authors collected the primary data from a valid sample of 360 employers through a structured questionnaire working as the hiring managers. Those respondents were selected on a random basis. The authors used exploratory factor analysis to validate the items under those independent variables and structural equation modeling with AMOS (24) to test the hypothesized relationship between each independent variable and the dependent one.

Findings

After proper statistical analysis, the results revealed that AP, PE, CS and TPSS can positively and significantly influence the OGE of Bangladeshi graduates while LMS and TS have positive but insignificant influence over OGE.

Research limitations/implications

Based on the findings, this paper can help scholars in further investigating the employability factors.

Practical implications

This explorative study will guide the fresh graduates in developing their required employability skills while assisting the employers in recruiting suitable candidates with the required skills and performance.

Originality/value

This is one of the few attempts that focused on the employability factors of private university graduates in Bangladesh. The authors are well confident that this empirical paper can shed some light on the fresh graduates’ employability and conducting further investigations on it.

Citation

Hosain, M.S., Mustafi, M.A.A. and Parvin, T. (2023), "Factors affecting the employability of private university graduates: an exploratory study on Bangladeshi employers", PSU Research Review, Vol. 7 No. 3, pp. 163-183. https://doi.org/10.1108/PRR-01-2021-0005

1. Introduction

One of the pre-conditions of higher education is to produce entrepreneurs and employable graduates who can serve their respective organizations, society and the country in general through their dedication and innovative skills. As we cannot expect all the graduates to be independent entrepreneurs, we can well assume that majority of the graduates in a country will search for suitable entry-level jobs according to their knowledge, skills and previous performance. The employment rate of graduates is frequently considered as a performance indicator to determine the value of higher education by the governments and international rankings (Teichler, 2009). The prospective students also pay attention to the employment prospects while selecting a university to pursue their higher study. Considering the increasing cost of higher education such as tuition fees and other charges, the national and global competition for attracting students is becoming more rigorous.

Due to the long-term effect of the global recession that began in 2008; and the very recent pandemic situation, the world economy is becoming shrinking substantially. One of the ultimate consequences of such a shrinking world economy is the less purchasing power of general people leading to less production and finally, less employment generation. Therefore, graduate employability has been and will continue to be the talk of the forum for the upcoming period. As a result of many changing circumstances, many countries will observe fewer jobs rather than new graduates at least for the next few years until the national economies will gain their regular speed. Universities and the graduates themselves are required to adopt newer sets of skills and techniques along with the traditional ones to get their expected jobs. In such a time, there is a fundamental and mounting requirement for conducting some empirical studies to investigate the skill sets that the employers are looking for.

There are quite a lot of theoretical and empirical research studies that have enriched academia (Rad et al., 2020; Jayasingha and Suraweera, 2020; Chowdhury, 2019; Chen, 2017; Nazron et al., 2017; Fitriyanto and Pardjono, 2017; Yulia and Yuzhuo, 2017; Gowsalya and Kumar, 2015; Sumanasiri et al., 2015; Ahmed and Crossman, 2014; Dotong, 2014; Shah and Srivastava, 2014; Cai, 2013; Weligamage, 2009; Chisty et al., 2007). However, despite a large number of studies, graduate employability appears to be suffering from the problems of lack of theoretical control. Furthermore, the concept of graduate employability is changing rapidly due to the external natural, political and economic circumstances such as recession, war and very recently, the outbreak of COVID-19. Therefore, the authors believe that there is still a need for further investigations on this specific and vital area of business and economics.

This particular exploratory study was conducted to identify the required factors for the employability of Bangladeshi private university graduates. The authors pre-selected six employable factors after searching the existing literature and made an extensive exploratory factor analysis. Following this step, the authors tried to correlate those factors with the overall graduate employability (OGE). The authors took the perceptions of Bangladeshi employers from a cross-section of industries to make the results more justifiable to the readers and scholars. The research question of this exploratory study was been identified as below:

RQ.

What are the factors that can affect OGE in Bangladesh?

2. Literature review

2.1 Graduate employability

Graduate employability can generally be defined as the compilation of a series of skills and abilities that a graduate can obtain to achieve a desirable job and succeed in his/her career (Chen, 2017; Tomlinson, 2012). Such skills and capabilities enable the graduate job candidates to meet the desired requirements of employers and adapt to changes in the labor market. It is a type of all-inclusive set of skills and abilities to improve future career development. Based on the existing published research works that primarily started from the 1990s, can be separated into two categories. The first one is from the standpoint of employment performance which proposes that employability is a combination of multi-faced dimensions, including interior and exterior factors (Guilbert et al., 2016). The internal factors include personal knowledge and skills associated with the job such as technical and team working skills, while the external factors include the condition of the labor market such as labor demand and supply (Tholen, 2014).

The second set of skills and capabilities can be viewed from the standpoint of personal ability that considers the graduate employability is the outcome of individual ability and is a collection of competitive skills and abilities that help the graduates to attain employment and develop (Tholen, 2014). Therefore, graduate employability is a complete set of skills to improve graduates to further career development (Finch et al., 2013). Such a set includes a series of skills, knowledge and personality traits (Yorke and Knight, 2007). As a sort of personal ability, the composition of graduate employability includes basic personal and social attributes, leadership skills, communication skills (CS) and teamwork skills (McQuaid and Lindsay, 2005). However, the existing most researched studies emphasized that graduate employability is a sort of “soft skills” to acquire jobs and getting career success (Chen, 2017; Reid, 2016; Kalfa and Taksa, 2015).

Previous research studies have identified a number of numbers of factors that can affect graduate employability. A study conducted by Weligamage and Siengthai (2003) on “employer needs and graduate skills” establishes seven vital expected factors that employers consider when recruiting fresh graduates are CS, general knowledge, personality (PE), computer and IT skills, verbal CS, realistic experience and educational background. According to Paddi (2014), most sought-after graduates should be proficient in teamwork, communication, analytic & critical thinking and IT skill. As pointed by Liyanage et al. (2016), graduates’ realistic knowledge, logical ability, dedication to work, communication & IT skills, management skills and positive attitudes are the highly concerned factors among employers. Another study conducted by Ambepitiya (2016) at two management education institutes in Sri Lanka observed that academic knowledge, soft, practical and technical skill development are the major factors that prepare a graduate ready for employment. Those results also concluded that although academic knowledge is an important factor, it is not the sole one for the effective employability of graduates (Jayasingha and Suraweera, 2020). However, this study considered six pre-selected factors for graduate employability in the Bangladeshi job scenario. Those six factors are academic performance (AP), technical skills (TS), communication skills (CS), personality (PE), leadership & motivational skills (LMS); and teamwork & problem solving skills (TPSS).

2.2 Academic performance and overall graduate employability

Academic performance (AP) is generally indicated through grade point average (GPA) or cumulative grade point average (CGPA) measured by various academic indicators such as class performance, assignments, presentation skills; and exam results. Numerous scholars identified a positive association between AP and OGE. Pinto and Ramalheira (2017) examined whether the AP and the participation in extra-curricular activities (ECA) affect the perceived employability of business graduates using an experimental study between-subjects factorial design on 349 Portuguese working adults. They found that AP published through GPA is the key to lift up business graduates’ employability. GPA and ECAs jointly foster business graduates’ employability. Almost similar findings were reported by Helena and Kena (2019) where they argued that AP along with participation in ECA results in higher rates of job suitability and employability skills for Chinese graduates. Fenta et al. (2019) also identified that graduates’ initial employability has a positive relationship with CGPA, preferred field of study and internship practice.

On the contrary, Soon et al. (2019) pointed that AP is not a key determinant in whether or not a graduate secures a job upon graduation and that having a better AP would only be beneficial if the graduates are working in jobs at the lower half of the salary distribution. Therefore, there are contrasting views regarding the influence of AP on OGE. However, this study included AP as one of the indicators of OGE for Bangladeshi graduates:

H1.

AP can positively and significantly affect OGE for Bangladeshi graduates.

2.3 Technical skill and overall graduate employability

Technical skill (TS) refers to the skills related to learning and acquiring different tools and techniques such as software, computer and IT. In a present competitive world, such a set of skills are quite essential due to the rapid changes in adopting IT and Internet. Furthermore, an employee is expected to be competent in using different software although those competencies vary according to the nature of the jobs. Mansour and Dean (2016) argue that employers require employees to have both TS. as well as soft or non-TS. Another recent study conducted in Sri Lanka by Jayasingha and Suraweera (2020) found that TS such as IT skills can partially influence OGE and have not reflected a significant impact on OGE. In a very recent study carried out in Bangladesh, Hossain et al. (2020) identified that both soft skills and TS are positively related to employability, which is consistent with prior studies. They suggested creating more technically skilled graduates particularly in a Bangladeshi job market where labor supply is abundant but skilled candidates are scarce.

On the other hand, Nazron et al. (2017) revealed that the attributes such as ICT and TS have no significant association with OGE. However, this study considered TS as one of the factors required for being employable:

H2.

TS can positively and significantly affect OGE for Bangladeshi graduates.

2.4 Personality and overall graduate employability

Personality (PE) indicates a distinctive manner of thinking, feeling and behaving. It embraces moods, attitudes and opinions; and is expressed while interactions with other people. It includes behavioral uniqueness, both inherent and acquired, that distinguishes one person from another and that can be observed through a person’s relationships to the environment and the social groups. Potgieter and Coetzee (2013) investigated the employability attributes and PE preferences of postgraduate business management students in South Africa and found significant relationships between the participants’ PE preferences and their employability attributes. Qureshi et al. (2016) identified PE as a predictor of engagement and employability. Neneh (2019) conducted an empirical study on PE traits, job market appraisal and self-perceived employability in an uncertain market and ultimately revealed that agreeableness, conscientiousness and openness to experience are positively and significantly associated with self-perceived employability. Based on the literature, this study included PE as one of the factors influencing graduate employability:

H3.

PE can positively and significantly affect OGE for Bangladeshi graduates.

2.5 Communication skill and overall graduate employability

Commutation skill (CS) generally refers to the ability to communicate with others effectively through sending and receiving the intended meaning. It can be done face to face, online or by mail. Effective communication and interaction reduce the perception bias, time and effort to enhance further efficiency. Rasul et al. (2013) investigated the graduate employability factors for the manufacturing industry and identified that employers place great importance on CS, problem-solving skills, teamwork skills and personal qualities. They argued that the graduates also need to emphasize leadership skills, entrepreneur skills, technology skills and informational skills. Another study conducted by Shah and Srivastava (2014) on the factors affecting the employability skills of management students and revealed that four factors: analytical skills & self-understanding, general management & work culture, leadership & problem-solving ability and communication make a significant impact on employability skills of management graduates. A recent study conducted by Succi and Canovi (2020) in different European countries identified that soft skills including communication skills, interpersonal skills and problem-solving skills increase the likelihood of employability of the students/graduates.

However, a complete opposite view was expressed by Nazron et al. (2017), who investigated the relationship between graduate’s soft skill attributes and employment status among students in University Malaysia Sabah (UMS). They found that the attributes examined (knowledge, ICT skills, TS, problem-solving, CS, teamwork, leadership, professionalism and ethics) have no significant relationship with the employment status of the graduates. Despite the opposing views, the authors included CS as one of the factors that can positively affect OGE for Bangladeshi graduates:

H4.

CS can positively and significantly affect OGE for Bangladeshi graduates.

2.6 Leadership & motivational skills and overall graduate employability

Leadership skills refer to effectively lead a team or subordinate(s) whereas motivational skills refer to motivate and positively influence a team or working partners. A good leader is always supposed to motivate and guide his/her followers or subordinates in a constructive manner. Rasul et al. (2013) investigated the graduate employability factors for the manufacturing industry and recognized that the graduates need to emphasize leadership & motivational skill (LMS) along with other qualities. Rahman et al. (2016) identified that low motivational level, lack of creativity and leadership values are among the major weaknesses of the graduate students in getting employed. Subbu and Rajasekaran (2018) made an extensive literature survey on the employability skills in the Indian job market and commented that LMS has a widening impact on OGE:

H5.

LMS can positively and significantly affect OGE for Bangladeshi graduates.

2.7 Teamwork & problem-solving skills and overall graduate employability

Team working indicates an interpersonal skill of a person who can effectively communicate with a team and can accomplish his/her role as a part of the team. On the other hand, problem-solving skill refers to effectively solving a practical or simulated problem in an efficient manner. Teamwork and problem solving skills (TPSS) are the two vital skills that make a job candidate competent in any situation. Numerous studies confirmed that these two skills are imperative for a graduate in getting an expected job. Gowsalya and Kumar (2015) identified that TPSS can highly increase the chance of a graduate being employed. Nazron et al. (2017) supported such findings and found that TPSS can raise the employment status among the students in University Malaysia Sabah (UMS). Nusrat and Sultana (2019) investigated the impact of soft skills on sustainable employment of business graduates in Bangladesh and reported that soft skills including TPSS can, in fact, not only assist in getting a job but also sustain it for longer. These two combined skills together were considered as one of the independent factors of employability in this explorative study:

H6.

TPSS can positively and significantly affect OGE for Bangladeshi graduates.

2.8 Theoretical model

This explorative study involves six independent variables with one single dependent variable: OGE. The theoretical model has been illustrated in the following diagram (Figure 1):

3. Research method

3.1 Collection of data

Primary data were collected for this explorative study as the secondary information are not suitable for the quantitative scale measurement. A detailed structured survey questionnaire was used to collect data from the respondents who had been chosen using a random sampling method from the two big cities (Dhaka and Chattogram) of Bangladesh.

Initially, 400 questionnaires were distributed to the employers and HR professionals working as the recruitment and selection officers at 11 job sectors in Bangladesh. Afterward, the authors received 370 questionnaires (with a response rate of 92.5%) where 10 questionnaires were found incomplete, biased and/or abnormally answered, and hence discarded through scrutinizing process. Finally, the valid data (n) used for this study was 360. The analysis was made by using multivariate analysis techniques such as exploratory factor analysis, confirmatory factor analysis and structural equation modeling.

3.2 Determination of sample size

As a medium-sized economy, the Bangladeshi job sector is not large enough to feed its entire unemployed people. To determine the sample size of the employers, the formula published by the University of Florida was used as a reference. This study used a formula for taking sample data from population suggested by Yamane (1967):

n=N(1+Ne2)

where n = sample size, N = population, e = level of precision. In calculating a number of samples, the following assumptions were made to determine: n = 330, if population size is 400,000; level of precision is 5%. However, 360 respondents had been taken as valid in this study.

3.3 Survey instrument

This study selected 360 recruiting officers working at 11 different job sectors in Bangladesh. A structured questionnaire with 23 items was used to collect the data developed by literature review. This structured questionnaire with a five-point Likert scale was used for collecting the pertinent data from the respondents. Table 1 highlights the number of items for each independent variable and the dependent one.

3.4 Validity and reliability of the items included on the survey instrument

If numerous items are used to determine an individual construct, the items’ (indicator) convergent validity should be one of the main concerns to the researcher that can be explained as the degree to which multiple items to measure the identical concept are in concord (Hair et al., 2010). According to Hair et al. (1998), convergent validity could be accessed through composite reliability (CR). The results of the measurement model (Table 2) indicate that the factor loadings for all items surpassed the recommended value of 0.70 (MacKinnon, 2008). The CR values ranged from 0.72 to 0.93 which exceeded the recommended value of 0.70.

On the other hand, to analyze the reliability (internal consistency) of the variables, this study used the Cronbach’s alpha coefficient and CR value. Table 2 shows that all the Cronbach’s alpha values are above 0.60 cutoff values as suggested by Nunnally and Bernstein (1994). Therefore, the results of reliability and validity indicate that each individual item is internally consistent and has a fairly high degree of reliability.

4. Analysis and interpretation

4.1 Demographic characteristics

Table 3 highlights the demographic characteristics of the participants of this study. It indicates that more than three-fourths of the participants are male while the majority of them are between the age range of 35 to 44 years. Most of the respondents are Master degree holders while there are a handful of PhD degree holders as well. Regarding the length of service, more than one-third of them (34.17%) have experienced between 11 and 15 years followed by a segment of 6 to 10 years (31.11%). Exactly one-fourth of the participants have job experience of 16 years or more.

4.2 Normality of data

Fairly normal distribution for the indicators of the latent factors in terms of skewness was observed (Table 4). However, a mild kurtosis for the indicators of the independent variable (LMS2) was evident although the highest kurtosis value is well below 2.6. While such value does violate strict rules of normality, it is still within the more relaxed rules suggested by Sposito et al. (1983), who recommend 3.3 as the upper threshold for normality.

4.3 Exploratory factor analysis

To assess EFA, four commonly used assumptions were followed (Hair et al., 1998; Field, 2000) such as sampling adequacy (Kaisers–Mayesolkin) measure greater than 0.5; the minimum eigenvalue for each factor; considering the sample size, factor loading of 0.50 for each item was considered as the threshold for retaining items to ensure greater confidence and varimax rotation was used, as it is a good general approach that simplifies the interpretations of the factors (Field, 2000).

Table 5 shows the EFA results. Hair et al. (2010) suggested that factor analysis can be performed when the Kaiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphericity are significant. An index of Kaiser’s measures of sampling adequacy (overall MSA = 0.838) and Bartlett’s test of sphericity x² (p = 0.000) suggested that the factor analysis is appropriate for further analyzing the data for this study. After examining the pattern matrix of EFA, this study found that all the items had factor loadings greater than 0.50 (Table 5).

The first factor (OGE) can explain 24.54% of the total variance with three items, the second factor (LMS) can explain 16.65% of the total variance with four items, the third factor (TS) can explain 7.56% of the total variance with three items, the fourth factor (TPSS) can explain 7.02% of the total variance with three items, the fifth factor (PE) can explain 6.06% of the total variance with four items, the sixth factor (AP) can explain 5.59% of the total variance with three items and the last factor (CS) can explain 3.78% of the total variance with three items in this analysis. Also, the reliability values (Cronbach’s Alpha) of all factors are greater than 0.7 satisfying the threshold value as recommended by Nunnally and Bernstein (1994). Finally, all 23 items were found to be suitable for further analysis such as confirmatory factor analysis and structural equation modeling.

The results indicate that the factor analysis is appropriate. After confirming research constructs, maximum likelihood (ML) and the Promax method (PM) were specifically used to extract factors from 23 items. Hair et al. (2010) recommended that each item factor loading must be more than 0.40 values to be considered as highly significant. Based on an eigenvalue greater than 1, a six-factor model was identified that explains 71.72% of the total variance of the data set. As a whole, 23 items were grouped (based on eigenvalue) into seven different factors. The EFA result also showed 0.55 as the lowest and 0.981 as the highest factor loadings of the variables. The result of the factor analysis showed that all the factors, as a whole, are acceptable for further analysis (Table 5).

4.4 Confirmatory factor analysis

Confirmatory factor analysis (CFA) is a statistical technique used to verify the factor structure of a set of observed variables. CFA allows the researchers to confirm that the variables are related to the respective factor. The relative Chi-Square for this model was 3.097 that is smaller than 5.0 as recommended by Marsh and Hocevar (1985) while other fit indexes also showed a good fit for the measurement model. The GFI of the model is 0.903 which is more than the recommended value of 0.90 suggested by Joreskog and Sorbom (1993). The summary result of the analysis is shown in Figure 2 and Table 6. The fit indices showed a good model fit to the data.

In the present study, the adjusted goodness of fit index (AGFI) was found to be 0.861 which meets the recommended value of (>0.85), hence deemed to be a good fit and acceptable supported by Anderson and Gerbing (1984). Furthermore, the non-incremental fit index such as the comparative fit index (CFI) is 0.918 that exceeds the recommended cut-off level of 0.90 (Bentler, 1990). In the CFA, the root mean residual (RMR) value was found to be 0.077, which is less than 0.08 and is commonly recommended as acceptable (Hu and Bentler, 1998). The root mean square error of approximation (RMSEA) is 0.079, which is also less than the suggested good fit to the data (Browne and Cudeck, 1993). Finally, the standardized means square residual (SRMR) is 0.079 which is less than 0.08 recommend by Browne and Cudeck (1993).

4.5 Colinearity assessment

Variance inflation factors (VIFs) range from 1 to 10 and upwards. The VIF numerical tells us what percentage of the variance is inflated for each coefficient. A rule of thumb for interpreting the variance inflation factor, 1 represents not correlated, between 1 and 5 are moderately correlated and greater than 5 represents highly correlation.

To check the influence of multicollinearity, the VIFs were calculated and found to be with a maximum value of 2.2 as shown in Table 7 which is at a permissible limit as recommended by Hair et al. (1998).

4.6 Common method bias test

A Harman’s single factor test can be used if the majority of the variance can be explained by a single factor. If a single factor will not explain the majority of variance, it can be assumed that the common method bias (CMB) has not occurred.

According to the results indicated in Table 8, a single factor can explain only 21.548% variance of this study that means that CMB did not occur in this study.

4.7 Structural equation model

A multivariate analysis technique (covariance-based structural equation modeling) was utilized to identify the significant relationships among six different employability factors. The overall factor concerning the employability of the private university graduates of Bangladesh and the six factors identified through factor analysis have been listed in Table 9 with the structural parameter estimates and hypothesis testing results.

The path diagram of this study revealed that four factors: AP, PE, TPSS and CS together can significantly explain 37.2% of employability of Bangladeshi private university graduates (Table 9) supporting the hypotheses H1, H3, H4 and H6. On the other hand, two factors: LMS and TS have a positive but insignificant influence over the single dependent variable OGE. Therefore, hypotheses H2 and H5 had been rejected. The structural equation model has been shown in Table 9 and Figure 3.

5. Discussion of results

The results of this exploratory investigation point that all of the six selected factors have positive effects on the OGE of Bangladeshi private university students. However, four of them (AP, PE, CS, TPSS) can strongly influence the overall employability supporting the major previous findings of Succi and Canovi (2020), Fenta et al. (2019), Helena and Kena (2019), Neneh (2019), Nusrat and Sultana (2019), Qureshi et al. (2019), Pinto and Ramalheira (2017), Nazron et al. (2017), Shah and Srivastava (2014), Rasul et al. (2013), Gowsalya and Kumar (2015) and Potgieter and Coetzee (2013).

On the other hand, according to the analysis, LMS and TS can inadequately influence graduate employability. Such results largely oppose the previous findings while having a limited consistency with the findings of Nazron et al. (2017). As the job market perspective is different in different countries, such results are not very unusual. However, although the last two mentioned factors cannot adequately influence the OGE, they are still essential as two important skills that can enhance the chance of getting expected jobs.

6. Theoretical and practical implications

Employability has been always a center of attraction to the university management, researchers, economists and obviously the graduates themselves. This research is expected to contribute to the understanding of employability skills that can affect the OGE in Bangladeshi work settings. As an important research priority for any country, more and more empirical investigations are required to be conducted in this area. The authors expect that this empirical study can enrich such effort to a further extent.

On the other hand, these empirical findings will drop some guided results for the new graduates allowing them to amplify in boosting their skill set. Moreover, the employers can also get some clues from the studies like this one.

7. Limitations and further scope

The study has several limitations that need to be pointed out. First of all, the study was limited to only the private university graduates of Bangladesh. Second, the scope of this study was limited to only a few skills based on one particular country. A cross-cultural study or comparative analysis taking more factors might have provided different and wider conclusions.

Therefore, there is a gap that could be bridged and an opportunity to conduct further analysis on this important area of management. The authors are expecting that more and more empirical investigations will be conducted in the future considering the above limitations and overcoming them.

8. Conclusion

Although within the present optimistic economy, a growing number of development projects and rapid industrialization are expected to create the necessary levels of employment for the university graduates, it cannot guarantee a perfect match between graduate qualities and employer needs. Therefore, establishing the relationship between the two would necessitate in-depth research studies. The perspectives of all the stakeholders such as graduates, employers and tertiary education providers need to be sought after to offer a holistic view of multifaceted employability factors. Conducting enquiries along these lines might shed some light on perceptions of the quality of the various programs that the private universities offer. The quick rise of private universities in Bangladesh and the increased number of graduates produced each year require guidance when making decisions about the programs and universities that would best serve their learning and long-term career plans.

In an age of globalization, no nation can sufficiently evaluate the applicability or relevance of any factor or factors that indicate the employers’ needs. In such a case, understanding the requirements of local and global employers is obviously not only a matter of concern for private universities but also for all institutions engaged with higher education. The outcomes and implications will be heading toward the interests of a broader educational community beyond that of private higher education providers.

Finally, the graduates must be adaptive to all the latest technologies and skillsets required by the job and the changing employment scenario. Such skills not only make them competent and valuable but also guarantee them sustainable career paths as expected.

Figures

Figure 1.

Theoretical model (all the relationships were hypothesized to be positive)

Figure 2.

Confirmatory factor analysis

Source: Structural equation modeling (AMOS 24)

Figure 3.

Path model estimation

Figure A1.

Theoretical model (all the relationships were hypothesized to be positive)

Table 1.

Number of items under each variable on the survey questionnaire

Variables	No. of items
Overall graduate employability (dependent)	4
Academic performance (independent)	3
Technical skill (independent)	3
Personality (independent)	3
Communication skill (independent)	3
Leadership and motivational skills (independent)	4
Teamwork and problem-solving skills (independent)	3
Total number of items	23

Source: Survey instrument

Table 2.

Reliability and validity of the questionnaire items

Factors	EM	LMS	TS	TPS	PE	AP	CS
EM	0.93
LMS	0.06	0.81
TS	0.303***	0.457***	0.83
TPS	0.547***	0.112†	0.472***	0.90
PE	−0.099†	0.462***	0.221***	0.07	0.79
AP	−0.08	0.160*	0.199**	0.08	0.05	0.73
CS	0.359***	−0.02	0.369***	0.313***	−0.10	−0.03	0.72

Note:

Significance of correlations: † p < 0.100, * p < 0.050, ** p < 0.010 *** p < 0.001

Source: Descriptive statistics (SPSS 24)

Table 3.

Demographic characteristics of the participants

Demographic variables	Category	Arithmetic no.	(%)
Gender	Male	277	76.94
	Female	83	23.06
	Total (n)	360	100
Age range (in year)	25–34	95	26.39
	35–44	211	58.61
	45 or more	54	15
	Total (n)	360	100
Educational level	Undergraduate	48	13.33
	Master	301	83.61
	PhD	11	3,06
	Total (n)	360	100
Length of service (in years)	5 or less	35	9.72
	6–10	112	31.11
	11–15	123	34.17
	16 or more	90	25
	Total (n)	360	100

Source: Demographic components of the questionnaire

Table 4.

Normality of the data

Descriptive statistics
Items	n	Mean	SD	Skewness	Kurtosis
	Statistic	Statistic	Statistic	Statistic	Statistic
CS1: Candidates must have sound communication skills along with other requirements	360	3.59	1.16	−0.26	−1.20
CS2: Candidates with better networking capabilities are highly valued	360	4.09	1.06	−0.99	−0.28
CS3: Better communication skills make a candidate confident	360	3.85	1.02	−0.60	−0.72
AP1: Academic performance is an indicator of a candidate’s employability in my organization	360	2.96	1.08	−0.05	−0.99
AP2: My organization considers academic performance as an important indicator of employability although it is not the only one	360	3.13	1.01	−0.32	−0.71
AP3: The condition of good academic performance can be relaxed for exceptionally qualified job candidates	360	2.79	1.11	0.15	−0.85
TS1: Technical skills are one of the mandatory competencies for employability in my organization	360	3.52	1.22	−0.33	−1.22
TS2: Candidates with sound technical skills are better sought	360	3.50	1.26	−0.36	−1.17
TS3: Candidates with technical skills are better equipped for solving any challenges	360	3.46	1.25	−0.26	−1.27
OGE1: Only the best candidates are employed at my organization	360	3.85	1.03	−0.79	−0.51
OGE2: My organization provides a better chance to the fresh graduates	360	3.95	1.10	−0.81	−0.67
OGE3: Before hiring, all the selected candidates go through strict and detailed selection tests	360	3.87	1.05	−0.80	−0.50
OGE4: The HRM professionals at my organization are expert to use the best candidates	360	3.86	1.04	−0.75	−0.56
TPSS1: Teamwork is a very essential quality to be hired	360	3.89	1.07	−0.75	−0.48
TPSS2: We strongly seek candidates with better teamwork capabilities	360	3.94	1.06	−0.82	−0.36
TPSS3: Candidates are tested through brainstorming for teamwork capability	360	3.98	0.99	−0.90	−0.06
PE1: I believe a candidate with a strong personality have a better commitment to his/her job	360	4.12	0.74	−0.51	−0.09
PE2: Personality can be developed	360	4.04	0.80	−0.43	−0.28
PE3: A candidate with a strong personality has the leadership qualities	360	4.21	0.74	−0.35	−1.11
LMS1: Only a good leader can motivate his/her followers	360	4.17	0.74	−0.91	1.47
LMS2: We strongly seek candidates with leadership and motivational skills	360	4.22	0.67	−1.01	2.60
LMS3: My organization is one of the best places to develop leadership and motivational skills	360	4.23	0.70	−0.88	1.69
LMS4: My organization encourages its employees to develop leadership and motivational skills	360	4.01	0.91	−0.85	0.38

Source: Structural equation modeling (AMOS 24)

Table 5.

Exploratory factor analysis

Factor name	EV1	PV2	CV3	Component variables	Factor loading	CR	AVE	Alpha
OGE	5.65	24.54	24.54	The HRM professionals at my organization are expert to use the best candidates (OGE4)	0.981	0.96	0.86
				Before hiring, all the selected candidates go through strict and detailed selection tests (OGE3)	0.922			0.957
				My organization provides a better chance to the fresh graduates (OGE2)	0.874
				Only the best candidates are employed at my organization (OGE1)	0.864
LMS	3.83	16.65	41.19	Only a good leader can motivate his/her followers (LMS1)	0.916	0.88	0.65	0.874
				My organization is one of the best places to develop leadership and motivational skills (LMS3)	0.823
				We strongly seek candidates with leadership and motivational skills (LMS2)	0.769
				My organization encourages its employees to develop leadership and motivational skills (LMS4)	0.786
TS	1.74	7.56	48.75	Candidates with sound technical skills are better sought (TS2)	0.935	0.87	0.70	0.867
				Technical skills are one of the mandatory competencies for employability in my organization (TS1)	0.885
				Candidates with technical skills are better equipped for solving any challenges (TS3)	0.736
TPSS	1.61	7.02	55.77	We strongly seek the candidates with better teamwork capabilities (TPSS2)	0.959	0.93	0.82	0.929
				Teamwork is a very essential quality to be hired (TPSS1)	0.939
				Candidates with sound technical skills are better sought (TPSS3)	0.798
PE	1.39	6.06	61.8	Personality can be developed (PE2)	0.837	0.84	0.63	0.834
				A candidate with a strong personality has the leadership qualities (PE3)	0.801
				I believe a candidate with a strong personality have a better commitment to his/her job (PE1)	0.745
AP	1.29	5.59	67.43	My organization considers academic performance as an important indicator of employability although it is not the only one (AP2)	0.788	0.78	0.54	0.775
				The condition of good academic performance can be relaxed for exceptionally qualified job candidates (AP3)	0.75
				Academic performance is an indicator of a candidate’s employability at my organization (AP1)	0.677
CS	1.00	3.78	71.21	Candidates with better networking capabilities are highly valued (CS2)	0.847	0.76	0.52	0.743
				Better communication skills make a candidate confident (CS3)	0.776
				Candidates must have sound communication skills along with other requirements (CS1)	0.55
CV3 = cumulative variance, EV1 = eigenvalue, PV2 = percent of the variance
KMO = 0.838, DF = 253, Significance = 0.000

Source: Descriptive statistics (SPSS 24)

Table 6.

Model fit indices and their acceptable thresholds

Goodness of fit indices	Value	Level of acceptance	Reference
Chi-square/df	3.097	<5.0	Marsh and Hocevar (1985)
CFI	0.918	>0.90	Bentler (1990)
RMR	0.077	<0.08	Hu and Bentler (1998)
GFI	0.903	>0.90	Joreskog and Sorbom (1993)
AGFI	0.861	>0.85	Anderson and Gerbing (1984)
RMSEA	0.079	<0.08	Browne and Cudeck (1993)
SRMR	0.079	<0.08

Source: Literature review

Table 7.

Variance inflation factor and tolerance in multicollinearity

Tolerance	0.716	0.922	0.721	0.703	0.45	0.552
VIF	1.398	1.084	1.387	1.422	2.221	1.813

Source: Structural equation modeling (AMOS 24)

Table 8.

Common method bias test

Total variance explained
Component	Initial eigenvalues			Extraction sums of squared loadings
	Total	% of variance	Cumulative (%)	Total	% of variance	Cumulative (%)
1	6.212	27.009	27.009	4.956	21.548	21.548

Source: Structural equation modeling (AMOS 24)

Table 9.

Regression weights: (group number 1 – default model)

Relationship	Hypothesis	Estimate	S.E.	C.R.	p	Label
OGE ← AP	H1	0.173	0.075	2.292	0.022	Supported
OGE ← TS	H2	0.020	0.064	0.308	0.758	Not supported
EM ← PE	H3	0.215	0.079	2.736	0.006	Supported
EM ← CS	H4	0.199	0.067	2.956	0.003	Supported
EM ← LMS	H5	0.144	0.101	1.430	0.153	Not supported
EM ← TPSS	H6	0.486	0.057	8.530	***	Supported
OGE		0.372

Note:

***indicates p value < 0.001

Source: Structural equation modeling (AMOS 24)