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Abstract

The present study explores the impact of the age-diverse workforce (young and old employees) on organization’s performance (financial and non-financial) and how job crafting mediates the relationship between age-diverse workforce and organization’s performance. By following the administrative survey approach, a total of 450 questionnaires were distributed to the employees of the Pakistan Post Office; however, 288 properly filled questionnaires (64%) were received back. The partial least squares–structural equation modeling (PLS-SEM) approach was used for data analyses. The outcomes of this study explain that there is a significant relationship between both age groups of employees (young and old) and an organization’s financial and non-financial performance. In addition, job craft partially mediates the relationship between young-age employees and organization’s financial and non-financial performance. However, job crafting fails to mediate the association between old-age employees and organization’s financial and non-financial performance. Implications, limitations, and future direction are discussed in the last sections of this study.

Keywords

age-diverse workforce organizational performance job crafting PLS-SEM post office Pakistan

Introduction

The focused objective of an organization is to improve and sustain its performance. To achieve this goal, a competent workforce is a basic and most critical resource (Liang, 2012). Therefore, organizations need to modify human resource management (HRM) policies to inspire the workforce (Truss et al., 2013). The employees of Generations X, Y, and Z have different skills and perceptions regarding their jobs, and organizations face multidimensional challenges due to the age differences among the employees (Rhoades & Eisenberger, 2002; Witt & Wilson, 1991). The performance of the organizations also fluctuates due to the employees’ different behaviors (based on their age) toward their jobs (Shropshire & Kadlec, 2012). Age diversity refers to a social characteristic that reflects subjective and objective variations among group members (Ferrero-Ferrero et al., 2015; Lu et al., 2015).

The concept of diverse workforce refers to the co-existence of people from different social, cultural, and ethnic backgrounds within the organization (Kundu, 2003). Diversity also signifies the differences between individuals on their attributes which indicate how the people distinguish from one another and demand diverse management practices (Carstens & De Kock, 2017). There are multiple indicators of diversity; however, age, competition, gender, and national source are the most popular dimensions to measure diversity. This study is probing age as a major dimension of diversity and its effect on organization performance (OP). The age diversification in the workforce can cause lower work performance due to employees’ compatibility issues (Case et al., 2015). Age diversity reflects the variations between workforce groups within an organization based on different characteristics. Several scholars consider age as a source of diverse processes and its effects on the organization’s performance (Kunze et al., 2013), and employees of various age groups behave differently in a working relationship (Bal & Smit, 2012).

Drawing on social categorization theory, age diversity affects diversely due to intergroup biases of the workforce (Pichler et al., 2012). Thus, age diversity can lead to either positive, negative, or zero effects on employees’ group outcomes, depending on the contextual factors (Van Knippenberg et al., 2013). OP refers to the combination of different activities that are important for an organization to stay in a competitive business environment (Wang et al., 2015). Financial performance (FP) and non-financial performance (NFP) of an organization determine its competitiveness and strength in the market (Giessner et al., 2016). The HRM policies such as job redesigning help to not only increase employees performance and OP (Weber & Tarba, 2010) but also decrease absenteeism (Hausknecht et al., 2008) and satisfy the employees of different ages, with lower turnover intentions (Drabe et al., 2015). Hence, constructive awareness about HRM policies (Kundu & Mor, 2017) helps the organization to motivate the age-diverse workforce.

Job crafting (JC) is an important aspect of job redesigning that helps to motivate the age-diverse workforce (Bakker et al., 2012). JC refers to a bottom-up and individually driven workplace HRM practice that makes the job more attractive through changes in job demand and resource level (Demerouti, 2014). In other words, JC refers to the workers’ independence to make rational changes in the social boundaries of their work (Wrzesniewski & Dutton, 2001; Wrzesniewski et al., 2013). JC approach develops intrinsic values when job responsibilities are considered significant, inspiring, and progressive, and employees are recognized for their participation (Deci & Ryan, 2000; Kanfer & Ackerman, 2004). Therefore, JC approach facilities to the old and young employees to craft their job activities as per their ease without disturbing the organizational decorum. Hence, JC may mediate the impact of an age-diverse workforce on organization FP and NFP.

Several scholars have investigated the relationship between age-diverse workforce and organization FP and NFP; however, outcomes are still unstable (Grund & Westergaard-Nielsen, 2008; Ilmakunnas & Ilmakunnas, 2011). Thus, previous investigations have no agreement on the said relationship and demand for more comprehensive theoretical and empirical evaluation of the behavioral processes that clarify the age-diverse workforce and organizational FP and NFP relationship (Kunze et al., 2013; North & Fiske, 2015). The researchers indicate the different roles of old and young employees to increase the OP; however, empirical evidence of this relationship is still missing.

This study has twofold objectives. First, to explain the relationship between age-diverse workforce and organization FP and NFP. Second, to evaluate the mediating role of JC between the relationship of age-diverse workforce and organization FP and NFP. To seek the above-mentioned research objectives, this study has the following research questions. First, what is the relationship between an age-diverse workforce (young and old employees) and organization FP and NFP? Second, how JC mediates the relationship between age-diverse workforce and organization FP and NFP.

For the empirical investigation, this study used the data collected from the employees of the Pakistan Post Office which is one of the oldest and big state-owned organizations of Pakistan. The offices of the Pakistan Post Office are situated all over Pakistan. The rationale behind the selection of the Pakistan Post Office is its human resource diversity. The employees of Pakistan Post Office have diversified age limits (i.e., 18–60 years) and different social and local cultural values. The arrangement of the study is as follows: introduction, literature review, methodology, results and analyses, discussion, theoretical and managerial implications, future research direction, limitations of the study, conclusion, and references.

Literature Review and Hypotheses Development

Age-Diverse Workforce

The term diverse workforce refers to the co-existence of people from numerous social, cultural, and racial backgrounds within the organization (Kundu, 2003). Diversity also means the differences between individuals on their attributes (Carstens & De Kock, 2017). The workforce diversity creates many benefits as well as challenges because diversity increases the work performance contradictions because of human inconsistency issues (Case et al., 2015). There are different dimensions of diversity though, age, competition, gender, and national source are often considered to be evaluated. However, this study operationalized the age diversification (old and young employees) in the meanings of diversity. Age diversity reflects the variations among an organization’s groups concerning age and can be hypothesized as inconsistencies or disparities based on different characteristics (Harrison et al., 2007). Many recent studies explicitly light on age as a source of diverse processes and their effects on the organization (Kunze et al., 2013). Former scholars described that employees of various age group behave differently in a working relationship (Bal & Smit, 2012). The demographic changes have increased the age diversity in the working class, and it is difficult to answer whether age diversity is a positive or negative sign (Ries et al., 2013). Wegge et al. (2012) in their investigation concluded that mixed-age teams have advantages and disadvantages as well.

There are two popular perspectives on diversity in literature; the information-processing sight and social categorization theory (Mannix & Neale, 2005). Information-processing indicates positive outcomes of diversity such as a favorable expansion of task-relevant information that follows an increased variety of resources within a group (Phillips et al., 2004), and social categorization theory explains the adverse effects of diversity by describing intergroup biases (Pichler et al., 2012). Thus, age diversity can lead to either positive, negative, or zero effects on group outcomes depending on the contextual factors (Van Knippenberg et al., 2013).

OP

The sustainable OP is directly linked with how the organization and age-diverse workforce handle the challenges in a competitive environment. Performance is central while planning HRM policies (Richard et al., 2009). OP refers to the core of all activities in organizations as it determines the organization’s survival (Choudhary et al., 2013; Wang et al., 2015). The evaluation of OP is important to seek measures against the week areas of the organization. Scholars have agreed that employees are most to enhance the OP, and employee performance can be improved by effective HRM policies (Fugate et al., 2004; Van der Heijden et al., 2016). In literature, OP is evaluated in two ways, namely, FP and NFP (Bendickson & Chandler, 2017).

FP refers to an organization’s monetary benefits, financial statements, and additional summaries that generally measure return on investment, profit growth rate, return on equity, return on sales, and return on assets (Dai et al., 2015; Hamdan & Al Mubarak, 2017). FP is a key element in the achievement of organizational goals (Wang et al., 2015). Although by encouraging the workforce through effective HRM policies, it was noted that customer commitment increased that contributes positively to a firm’s FP in terms of growth, market share, or productivity (Yu et al., 2017). Firms that provide better services to their employees yield greater profit from employees than firms that are poorer in providing services (Cheng et al., 2016). By investing in human skills, the organizations raise an indirect positive association toward FP (Ling & Jaw, 2006).

NFP also indirectly increases the organizations’ FP. NFP refers to quality, efficiency, growth, and customer/employee satisfaction (Abdel-Maksoud et al., 2016; Fullerton & Wempe, 2009). Besides this, creativity, efficiency, and goal achievements also are important indicators to measure NFP (Brush, 1996; Kapoor & Lim, 2007). The organizations conducted different training and motivational programs to motivate the employees that significantly affect NFP (McNamara et al., 2012). Previous studies determined that only accounting-based financial measures are not enough, non-financial measures are also equally significant to make the criteria of performance excellence (Taylor et al., 2001).

JC

JC refers to a workplace where workers independently make rational changes in the social boundaries of their work (Wrzesniewski & Dutton, 2001; Wrzesniewski et al., 2013). According to lifespan development approaches, changes in human beings’ lives are taking place regularly, especially related to their age, health, and safety (Haase et al., 2013). Numerous studies described that JC is significantly related to OP as well as employee satisfaction (Leana et al., 2009).

By considering the JC paradigm, the employees have the autonomy to make three types of changes in their work behavior (Chen et al., 2014). First, to create changes in multiple activities on performing the job (Wrzesniewski et al., 2013). When employees perceive the significant impact of their efforts on others, they perform more better way and get inspired (Grant & Parker, 2009). The second is relational crafting, it involves the alteration in employees’ relationships (Cheng et al., 2016). Relational crafting made the job more flexible, developed positive work behavior, increased job commitment, and decreased anxiety (Chiaburu & Harrison, 2008). The third is intellectual boundaries, it is adapted when employees revise their opinions about work (Tims et al., 2014). JC is based on the Job Demands-Resources (JD-R) model. As per the JD-R model, an age-diverse workforce tries to maximize their job resources and minimize their job demand (Tims et al., 2015). Job demands links with customers and required job aspect such as supportable physical and psychological power (Demerouti et al., 2001; Tims et al., 2015). Previous studies described that job demands have an optimistic or pessimistic relationship between job hassles and work assignments (Thorsteinsson et al., 2014; Tims et al., 2015), while job resources help to motivate employees intrinsically as well as extrinsically and enhance the competencies of employees (Tims et al., 2015). A high level of job resources leads to an increase in the commitment of the workforce at work (Bakker & Demerouti, 2007).

Age-Diverse Workforce and OP

The literature on age diversity explains that employees who are well aware of organization needs change continuously over time (Ng & Feldman, 2010; Warr et al., 2001). When employees become older, their priorities related to work assignments also changed (Roebers & Schneider, 2010). Recent studies found that employees as per their age behave differently in the workplace and situation (Truxillo & Fraccaroli, 2013; Zaniboni et al., 2013). The researchers explained that the collective opinions of employees to justify the diversity link at the organization level (Roberson & Perry, 2017). Organizations need to expand age composition and innovative work environment, and provide a platform to transfer suitable knowledge from the old to the young generation (Backes-Gellner & Veen, 2013).

Selection, optimization, and compensation theory highlights the merits and demerits regarding age diversity (Bajor & Baltes, 2003). Aging is usually related to buffering in fluid intelligence and physical strength (Treadway et al., 2005; Warr et al., 2001). Old-age employees’ aptitude and work-related expertise are increased because of their long span of work experience in the organization (Oberauer et al., 2005). Corporations with old-age employees are more productive because of the extensive experience and job rotations in different departments in the same organization (Van Knippenberg et al., 2013). On the contrary, socio-emotional selectivity and expectancy theory highlight the significance of time perception to detect goals in young-age employees (Carstensen et al., 1999). With the time flexibility, young-age employees give more importance to the factors such as knowledge gaining, advancement opportunities, and job security as compared with old-age employees (Bal et al., 2008; Protogerou et al., 2017). Moreover, young-age employees have new ideas and skills that are also necessary to enhance the organization’s innovative performance (Reininger et al., 2003). Hence, by keeping in view the above literary evidence, it is proposed that

Hypothesis 1a (H1a): Old-age employees have an association with the organization’s FP.

Hypothesis 1b (H1b): Old-age employees have an association with the organization’s NFP.

Hypothesis 2a (H2a): Young-age employees have an association with the organization’s FP.

Hypothesis 2b (H2b): Young-age employees have an association with the organization’s NFP.

JC as a Mediator

Supportive HR practices to the age-diverse workforce are necessary to enhance the OP. Employees-oriented HR policies and practices such as JC help the workforce for getting career development opportunities (Armstrong-Stassen & Schlosser, 2011; Truxillo et al., 2012). The HR practices supportive to an age-diverse workforce are the motivation for the workers of diverse ages (Connelly et al., 2011; Ybema et al., 2017). The concept of JC refers to how employees had the autonomy to change the ways of doing a job (Chen et al., 2014). Several scholars explained that when employees are engaged in proactive JC activities, their commitment to the organization is increased (Tims et al., 2014, 2015). The literature also indicates that an age-discriminatory environment negatively affects the affective commitment and OP at the individual as well as the organizational levels (Shropshire & Kadlec, 2012). Despite the different viewpoints on the age-diverse workforce in the literature, the authors concluded that valued, inspired, and facilitated employees affect the OP positively (Cheng et al., 2016). Hence, it is hypothesized as follows:

Hypothesis 3a (H3a): JC mediates the relationship between old-age employees and the organization’s FP.

Hypothesis 3b (H3b): JC mediates the relationship between old-age employees and the organization’s NFP.

Hypothesis 4a (H4a): JC mediates the relationship between young-age employees and the organization’s FP.

Hypothesis 4b (H4b): JC mediates the relationship between young-age employees and the organization’s NFP.

Figure 1 explains the hypothesized relationships among the proposed variables.

Figure 1.

Study framework.

Method

Sample and Data Collection Procedure

By considering the objectives of this study, the authors collected the data from the employees of the Pakistan Post Office. Pakistan Post Office is one of the largest employers in Pakistan having more than 49,502 workers (Express Mail Track & Trace System [EMTTS], 2020). Pakistan Post Office comprises a network of 13,419 post offices, 76 General Post Offices, 48 District Mail Offices, and three Offices of Exchange, along with central management facilities in Islamabad and Lahore (EMTTS, 2020). The rationale behind the selection of Pakistan Post Office employees is the diversity in their age. This study used a simple random sampling technique and administrative survey approach. All employees of the Pakistan Post Office cannot understand English at a good level; therefore, a bilingual questionnaire (English and Urdu) was prepared for easy understanding to all employees. The authors randomly selected 450 post office employees from different management units (e.g., urgent mail service, finance, marketing, HRM), who are responsible to exercise the entire process of postal services offered by the organization.

Through an administrative survey approach, the authors explained to the participants the study’s objectives and confirmed to them about data safety. A cover letter was also attached to the top of the questionnaire. This letter explained to the respondents that your individual information will be kept secret and collective response will be used for analyses. It was also cleared to the respondents that there are no right or wrong answers. Therefore, all respondents should stay cool and answered the questions as naturally as possible. This study is also permitted by the ethics committee and research board of the school. These measures helped to minimize social desirability and consent biases (Bari et al., 2020; Spector, 2006).

A total of 450 questionnaires were distributed to the employees of the Pakistan Post Office. The questionnaires were distributed through different mediums such as emails, mails, and personal visits. A total of 251 questionnaires were received within 1 month without the reminder. However, after two soft reminders, 149 more questionnaires were received. Hence, a total of 400 questionnaires were received back. After the primary screening, from 400 questionnaires, 288 were randomly selected (144 old and 144 young respondents). Therefore, the final response rate was 64%. Regardless of any social/professional influences, the data were collected on the free consent and willingness of the respondents. The informed consent of the participants was implied through investigation achievement. The authors also did a comparison between late and early responses (Bari, Abrar, Shaheen, et al., 2019; Dillman, 2011). After comparison, it was confirmed that there was not a significant difference between the early and late respondents. These outcomes confirm the reliability and quality of the data. The respondents’ profile is provided in Supplemental Appendix 1.

Measurement of Variable

The questionnaire was adopted from the previous studies and necessary amendments were made as per study objectives. All items were measured on a 5-point Likert-type scale ranging from strongly disagree (1) to strongly agree (5).

Age-diverse workforce

To measure the age-diverse workforce, 12 items were derived from previous studies. The workforce was divided into two groups based on their age such as above 40 are considered as old employees and up to 40 years were considered as young employees. The six-item scale of Treadway et al. (2005) was used to measure the response of old employees and the Cronbach’s alpha value was .855. Similarly, the six-item scale developed by Reininger et al. (2003) was used to measure the response of young employees, the Cronbach’s alpha value was .842.

OP

A 10-item scale was used to measure the OP (FP and NFP). The FP was measured with the five-item scale developed by Dai et al. (2015), Cronbach’s alpha value of FP is .90. Similarly, the NFP was measured by the five-item scale developed by Abdel-Maksoud et al. (2016), Cronbach’s alpha value of NFP was .889.

JC

To measure JC (task, relational, and cognitive), this study used six-item scale developed by Carrie Leana et al. (2009) For instance, “introduce new approaches on your own to improve your work at the workplace.” Cronbach’s alpha value of JC was .790.

Partial Least Squares–Structural Equation Modeling (PLS-SEM)

PLS-SEM is a classical multivariate model (Henseler & Sarstedt, 2013). This article applied a variance-based PLS-SEM approach, instead of other co-variance-based approaches such as AMOS, LISREL, and so on. The main reason behind the application of PLS-SEM is its effectiveness for both types of investigations, that is, exploratory and confirmatory (Hair et al., 2014, 2016). The SEM has two forms, namely, PLS-SEM and CB-SEM (co-variance based; Hair et al., 2016). The CB-SEM is applied to confirm/rejection theories; however, PLS-SEM helps not only theory development but also its extension (Bari, Abrar, Bashir, et al., 2019; Hair et al., 2016). PLS-SEM is also very supportive for complex and second-order models as well as small data analyses (Hair et al., 2016). This study used SmartPls 3.9 software for data analysis.

Results and Analysis

Reliability and Convergent Validity

The factors’ consistency reliability is measured by two methods, namely, composite reliability (CR) and Cronbach’s alpha (α). These two methods are also considered as substitutes for each other (Hair et al., 2016). The values of CR should be greater than .7 (Hair et al., 2014). Table 1 shows that all CR values are higher than .70. Cronbach’s alpha values of all items are higher than the threshold level of .70 as presented in Table 1 (Bari et al., 2020; Hair et al., 2016). Convergent validity explains the variance between variables with the help of the average variance extracted (AVE). As per scholars, the values of AVE should be higher than 0.500. Table 1 shows that the values of AVE are above the threshold level of 0.500 (Square et al., 2013). Hence, Table 1 demonstrates the outer loading values of each item are also equal to or above 0.700.

Table 1.

Measurement Model.

Constructs	Items	LV	CR	α	AVE
Financial performance	FP-1	0.850	.927	.902	0.719
	FP-2	0.868
	FP-3	0.877
	FP-4	0.804
	FP-5	0.839
Job crafting	JC-1	0.700	.855	.790	0.542
	JC-2	0.746
	JC-3	0.764
	JC-4	0.754
	JC-5	0.736
Non-financial performance	NFP-1	0.770	.918	.889	0.693
	NFP-2	0.862
	NFP-3	0.858
	NFP-4	0.830
	NFP-5	0.838
Old-age employees	OAE-1	0.737	.892	.855	0.579
	OAE-2	0.794
	OAE-4	0.773
	OAE-5	0.746
	OAE-6	0.752
Young-age employees	YAE-1	0.778	.833	.842	0.558
	YAE-2	0.715
	YAE-3	0.764
	YAE-4	0.707
	YAE-5	0.755
	YAE-6	0.762

Note. All values are significant at .050 level (two-tailed); α = Cronbach’s alpha; LV = loading values; CR = composite reliability; AVE = average variance extracted; FP = financial performance; JC = job crafting.

Discriminant Validity

To measure the discriminant validity of the present study model, two approaches are used. First, Fornell–Larcker criterion. It is an evaluation of square root values of all AVE with the correlation of the latent variables along with their items (Ali & Park, 2016; Hair et al., 2014). As per rules, the top value of each column should be higher than the other values from the same column (Hair et al., 2016). Table 2 shows that all columns’ top values are higher than the other values. Second, the second approach is heterotrait–monotrait (HTMT) ratio. As per criteria, the values of HTMT ratios should be less than 0.85; however, up to 0.90 is acceptable limit (Hair et al., 2016). Table 2 indicates that all HTMT ratio values are less than 0.90 and meet the criteria (Henseler & Sarstedt, 2013).

Table 2.

Discriminant Validity.

Fornell–Larcker criteria						HTMT ratios
Variables	FP	JC	NFP	OAE	YAE	Variables	FP	JC	NFP	OAE	YAE
FP	0.848					FP
JC	0.695	0.738				JC	0.800
NFP	0.820	0.686	0.832			NFP	0.888	0.791
OAE	0.773	0.733	0.816	0.761		OAE	0.875	0.874	0.902
YAE	0.676	0.685	0.654	0.662	0.747	YAE	0.773	0.822	0.751	0.774

Note. HTMT = heterotrait–monotrait; FP = financial performance; JC = job crafting; NFP = non-financial performance; OAE = old-age employees; YAE = young-age employees.

Collinearity issues in the data are observed through the variance inflation factor (VIF). In the present study, the inner VIF values of each variable should be less than three; however, up to five is acceptable. Table 3 depicts that all inner VIF values are less than five, which indicates that there are no collinearity issues in the data.

Table 3.

Collinearity Statistics.

Variables	Financial performance	Non-financial performance	Job crafting
Young-age employees	2.102	2.102	1.780
Old-age employees	2.415	2.415	1.780
Job crafting	2.55	2.55

Model Fitness

The value of R² explains the variance between independent and dependent variables to predict the model accuracy. According to the rule of thumb, R² values ≥.75, ≥.50, and ≥.25 indicate the strong, moderate, and weak models, respectively (Bari, Abrar, Bashir, et al., 2019; Hair et al., 2016). In this study, the values of R² of endogenous variables (JC, FP, NFP) are (.659, .609, and .695), respectively, that are accepted at a moderate level (Hair et al., 2014, 2016). The validated redundancy Q² calculation is done through the blindfolding technique. As per rule, the values of Q² should be above zero (all values > 0) by two times the submission between distance error seven and 25 (Henseler & Sarstedt, 2013). All Q² values are above zero in the present study model.

Hypothesis Verification (Direct Relationship)

This study applied bootstrapping technique with 5,000 samples with replacement to calculate the level of significance (Hair et al., 2016). Table 4 explains that young-age employees have significant associations with FP (b = 0.229, p < .05) and NFP (b = .158, p < .05). Thus, H1a and H1b are accepted. Similarly, old-age employees have significant associations with FP (b = .491, p < .05) and NFP (b = .623, p < .05). Therefore, H2a and H2b are also accepted.

Table 4.

Hypothesis Verification (Direct Relationship).

Structural paths	Path coefficient(T statistics)	Effect size(f²)	Confidence interval	p value0.05%	Results
YAE → FP	0.229 (4.283)	0.073	[0.333, 0.125]	.000	H1a accepted
YAE → NFP	0.158 (3.511)	0.039	[0.245, 0.069]	.000	H1b accepted
OAE → FP	0.491 (9.444)	0.293	[0.587, 0.387]	.000	H2a accepted
OAE → NFP	0.623 (12.997)	0.527	[0.581, 0.407]	.000	H2b accepted
YAE → JC	0.355 (7.956)	0.181	[0.438, 0.264]	.000
OAE → JC	0.499 (11.284)	0.357	[0.581, 0.407]	.000
JC → FP	0.178 (3.834)	0.036	[0.267, 0.082]	.000
JC → NFP	0.121 (2.456)	0.019	[0.219, 0.027]	.014

Note. FP = financial performance; JC = job crafting; NFP = non-financial performance; OAE = old-age employees; YAE = young-age employees.

Hypothesis Verification (Indirect Effect)

To calculate the mediation degree of JC between an age-diverse workforce (old and young employees) and organization FP and NFP, this study applied the variance accounted for (VAF) technique (Bari et al., 2020). To evaluate the mediation degree, the VAF technique is as follows: The VAF > 80% indicates full mediation, the VAF value greater than 20% and less than 80% shows partial mediation while VAF < 20% is no mediation (Bari et al., 2020). Table 5, as per VAF criteria, JC has not significant mediation effect between old-age employees and FP. However, JC partially mediates the relationship between young-age employees and the FP of the organization. Hence, H3a is rejected and H4a is accepted. Similarly, JC has not a significant mediation effect between old-age employees and NFP. However, JC partially mediates the relationship between young-age employees and NFP of the organization. Hence, H3b is rejected and H4b is accepted. Figure 2 depicts the post-analyses model.

Table 5.

Hypothesis Verification (Indirect Relationship).

Constructs	Direct effect(t value)	Indirect effect(t value)	Total effect	VAF %	Interpretation	Results
OAE → JC → FP	0.491(9.444)	0.089(3.502)	0.580	15.33%	No mediation	H3a rejected
YAE → JC → FP	0.229(4.283)	0.063(3.580)	0.292	21.57%	Partial mediation	H4a accepted
OAE → JC → NFP	0.623(12.997)	0.060(2.301)	0.683	8.78%	No mediation	H3b rejected
YAE → JC → NFP	0.158(3.511)	0.043(2.415)	0.201	21.39%	Partial mediation	H4b accepted

Note. |t| ≥ 1.96 at p = .05 level. VAF = variance accounted for; FP = financial performance; JC = job crafting; NFP = non-financial performance; OAE = old-age employees; YAE = young-age employees.

Figure 2.

Post-analyses model.

Discussion

The objective of this study was to evaluate the impact of diverse-age factors of employees on organization FP and NFP, and to investigate the mediating role of flexible work strategies such as JC between age-diverse workforce (old- and young-age employees) and organization’s FP and NFP. The outcomes from the data collected from the employees of Pakistan Post Office describe the positive and significant association between young- and old-age employees, and the organization’s FP and NFP. These results are also in line with previous studies (Blanz, 2017; Karpinska et al., 2015; van Dam et al., 2017). However, the case of JC as a mediator is different. Table 5 shows that JC significantly (partially) mediates the relation between young-age employees and organization’s FP and NFP. Contrary, JC fails to mediate the relationship between old-age employees and the organization’s FP and NFP.

The outcomes of the present study reveal some very interesting facts. First, drawn on selective, optimization, and compensation theory and socio-emotional selectivity theory, the employees of both age groups (young and old) are equally important and valuable assets for the continuous growth of the organization (Roebers & Schneider, 2010). When the young innovative minds are clubbed with the experienced and skilled minds, the organizations not only sustain their share in the market but also increase their performance continuously. Hence, a diverse-age workforce is necessary for better organizational performance. However, flexible workplace strategies such as JC have different roles for young- and old-age employees. The empirical investigation reveals that young-age employees prefer to adopt the JC option. On the contrary, the JC strategy did not significantly suit old-age employees. According to the job demand (JD-R) model, when employees are getting old, they give more importance to intrinsic job aspects. Previous studies revealed that old-age employees take more interest in their working assignments when they perceive that the organization environment is age supported. The JC approach is not a suitable approach to induce the intrinsic values of old-age employees. Therefore, old-age employees did not agree with JC strategy.

This study elaborates on various organizational perspectives. The organization is often referred to as a goal-oriented body in which performance is a key factor for organization survival (Karpinska et al., 2015). Therefore, an organization needs to implement effective HR practices to achieve targeted goals (Bakker & Demerouti, 2007). Organizations design different HR policies to create and improve resources which are supporting the employees of different age groups. For instance, JC and an open communication system play a significant role in improving workforce commitment (Yu et al., 2017). JC is an effective approach in which employees have the freedom to work according to their desire and ease (Chen et al., 2014; Cheng et al., 2016). This study clarifies that the JC approach plays a significant role and becomes a great source of motivation for young-age employees as compared with old-age employees. Scholars recommend multiple HR strategies and practices to sustain the ideal performance because the single approach is not enough to sustain organizational performance (McNamara et al., 2012).

Research Implications

The present study has several theoretical and managerial implications. First, this study endorses the social categorization theory and explains that diverse-age workforce is such as old- and young-age employees are equally important for the growth and development of an organization. Second, this study specifies the impact of JC theory. This study highlights that young-age employees prefer JC activities as compared with old-age employees. In other words, young-age employees are more change-oriented than old-age employees. Hence, JC theory is more applicable to Generation Y than Generation X (Demerouti, 2014).

Third, it is recommended that the Pakistan Post Office should redesign their HRM policies by considering the age group of the employees. JC is a more significant approach in the case of young-age employees as they are more career- and change-oriented. Young-age employees are more eager and enthusiastic to learn new things and more committed when they have autonomy in their workplace. Fourth, old-age employees are more emotionally attached to their organizations and they focus more on intrinsic job aspects such as respect, appreciation, an age-supportive environment, and so on. Hence, it is suggested that the Pakistan Post Office should also focus on intrinsic motivational aspects of the job to enhance the old employee’s satisfaction level. Fifth, it is also recommended that the HR department of the Post Office should organize different training and mentoring programs to update the knowledge, skills, and expertise of the diverse-age workforce. Sixth, the organizations should mix the workforce based on age diversity. Through this strategy, innovative minds and experienced minds will perform more effectively.

Limitations and Future Research Directions

Like other theory-based studies, this study has also certain limitations and future research directions as well. First, the outcomes of this study are based only on the data collected from the employees of different departments of the Pakistan Post Office located in different areas of Pakistan. It is suggested that this study model can be applied in other services sectors of Pakistan and other parts of the world as well. Second, this study investigated the combined role of different dimensions of JC (task, relational, and cognitive) as a mediator between young- and old-age employees, and organization FP and NFP. For future studies, different dimensions of JC as a mediator individually can be investigated to get a clearer role of JC between diverse-age workforce and organization’s performance. It will be helpful to understand which dimension is more effective as a mediator. Third, this study is conducted in one country and one culture. In future, cross-border and cross-culture studies can be conducted. Fourth, this is a cross-sectional study; in future, longitudinal and time lag studies can also be conducted.

Supplemental Material

sj-docx-1-sgo-10.1177_2158244021999058 – Supplemental material for The Impact of Age-Diverse Workforce on Organization Performance: Mediating Role of Job Crafting

Supplemental material, sj-docx-1-sgo-10.1177_2158244021999058 for The Impact of Age-Diverse Workforce on Organization Performance: Mediating Role of Job Crafting by Mohsin Bashir, Ammarah Hameed, Muhammad Waseem Bari and Raza Ullah in SAGE Open

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Muhammad Waseem Bari

Supplemental Material

Supplemental material for this article is available online.

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