Exploring the relationship between generational diversity and knowledge sharing: the moderating role of workplace intergenerational climate, boundary-spanning leadership and respect Free

Over the recent decades, a remarkable shift in workforce demographics has been observed globally (Özçelik, 2015; Teng et al., 2018). Some of the reasons for this shift include an aging workforce, elimination or change of mandatory retirement age, increased life expectancy because of improved medical facilities, bridge employment, and an influx of young professionals (Brooke, 2003). The changing demographics have led to a multigenerational workforce in many organizations (Kantarci and Van Soest, 2008; Lancaster and Stillman, 2002). The workplace today comprises three to four generations working together. Multiple generations at work results in a nonoverlapping knowledge, perspectives, experience, and expertise uniquely drawn from each generation leading to a more extensive knowledge pool that helps in better decision-making, problem-solving, and attaining positive individual and organizational performance (Wang and Wang, 2012; Argote and Ingram, 2000). However, each generation is different from the others in certain key characteristics such as attitudes, beliefs, personalities, motivation, work values, and workplace behaviors (Costanza et al., 2012; Becton et al., 2014; Singh et al., 2020). Failure to recognize and address these differences may lead to undesirable consequences such as conflicts, diminished trust, misunderstandings, discrimination and dip in productivity and commitment (Kunze et al., 2013; Pritchard and Whiting, 2015).

India has the largest and youngest employable population in the world despite that it will see an increase in retirement age due to a lack of skilled workforce similar to other developed nations (Brooke, 2003). This would result in the Indian workforce being more age-diverse than ever before and demand the consideration of age/generation as an essential dimension of human resource management research and practice. Organizations across the globe are already acknowledging generational diversity as an essential form of diversity and taking initiatives to address it. In particular, organizations in India are shifting their focus from diversity as a program to diversity and inclusion as a business strategy, and 15% of their diversity initiatives are centered on age/generation (Kundu and Mor, 2017). Saxena and Singh (2019) reported that 12% of organizations in India had highlighted generation as a dimension that defines diversity for them. Organizations realize that each generation has something unique to contribute. It is essential to recognize different generations’ expectations and work styles to work together collaboratively to make the organization successful. Past research highlighted that generationally diverse teams are critical for innovation and knowledge sharing as each generation brings in a unique set of competencies and experiences with them. Hence, it becomes paramount for organizations to effectively manage their multigenerational workforce to derive unique benefits from each generation.

In a dynamic and competitive world, knowledge is one of the most critical organizational resources that helps in attaining superior performance and sustainable competitive advantage (Nonaka et al., 1996). Knowledge sharing among employees positively influences group performance and organizational performance (McKay et al., 2008). However, this knowledge needs to be shared among employees to make teams more effective and productive (Pinjani and Palvia, 2013) and organizations more competitive (Argote and Ingram, 2000). Thus, organizations should build a positive intergenerational climate (free of ageism) harmonious for employees of different generations to share knowledge seamlessly.

Further, researchers posit that effective leadership behavior helps manage diversity at work and enhances positive group outcomes (Al-Asfour and Larry, 2014). A leader can address negative group processes such as discriminatory behaviors, conflicts, miscommunication, etc. (Homan and Greer, 2013) and facilitate knowledge sharing among individuals (Lee et al., 2010; Xue et al., 2011). A notable form of leadership, boundary-spanning leadership, effectively facilitates intergroup collaboration (Salem et al., 2018).

The current article attempts to address this gap by understanding how effective management of generational diversity facilitates increased knowledge sharing, leading to improved group performance. The purpose of this study is multifold; firstly, the study investigates the impact of generational diversity on knowledge sharing and group performance. Secondly, this study explores the moderating effects of intergenerational climate, boundary-spanning leadership, and respect in facilitating greater knowledge sharing and superior group (branch) performance in the context of a multigenerational workforce.

Generation refers to an identifiable group that shares birth year and significant life events at critical developmental stages (Kupperschmidt, 2000). People in their adolescence or young adulthood, when exposed to these significant historical, social, cultural, and political events, form collective memories of those events, which will contribute to a unique frame of reference or worldview that acts as a powerful influence in a person’s life (Parry and Urwin, 2011). Different authors adopt several categorizations to study generational phenomena – (Strauss and Howe, 1991; Wey Smola and Sutton, 2002). These categorizations are influenced by the significant historical, social, cultural, and political events prevailing in a country during a particular period and may change across different countries. Hence, using a classification specific to a country’s context for studying generations becomes more relevant. This study adopts the type given by Ghosh and Chaudhuri (2009) since this classification is proposed in relevance to significant events in India. The category includes: Conservatives (1947–1969) who were born postindependence and raised in a rigid bureaucratic set-up, Integrators/Baby Boomers (1970–1984) are a blend of Indian cultural heritage and contemporary Western values, and Millennials/Gen Y (1985–1995) are influenced by economic reforms, postliberalization and are highly technology-oriented. Barhate and Dirani (2022) proposed the newest generational category in the workforce, i.e. Gen Z/iGen that includes people who are born after 1995. They are the first true “digital native” people, highly technology-oriented, and entrepreneurial in nature.

Extant literature captures several studies on age diversity and its related consequences at work. However, the concept of generational diversity differs from age diversity. Age diversity is simply a distribution of individuals based on their ages, as age is a continuous variable. On the contrary, generational diversity considers a generation as a group of individuals born and raised in a particular period and are affected by the significant events prevailing during that period. Age diversity refers to the employees of different ages at the workplace. Generational diversity refers to the presence of employees belonging to other generations. Age diversity is not conceptualized in the same way. Thus, generational diversity is a generation/cohort (group) study and distinguishes one generational cohort from another based on certain fundamental characteristics, such as attitudes, beliefs, behaviors, personality traits, work values, etc. According to generational diversity, two managers of the same age but separated by 20 years would possess a different value system because of the period they are born into (Singh et al., 2020).

Generational diversity has two distinct dimensions–surface-level and deep-level (Harrison et al., 1998). It is surface level because age/generation is a visible attribute and can be easily perceived by individuals. It is deep level because every generation is distinct on certain key characteristics such as beliefs, attitudes, perspectives, work values, and workplace behavior (Jansen and Searle, 2021). The authors in this study conceptualize generational diversity at both levels, using the surface-level indicator to measure it and the deep-level dimension to build the arguments and hypotheses development (Figure 1).

Generational diversity has not received considerable attention in the literature as compared to other forms of diversity such as gender, ethnicity, or race despite the salience and universality of age in organizations and society at large (Palmore, 1999; McGuire et al., 2007; Rajput et al., 2013).

The current model draws from the rich theoretical framework of Social Categorization proposed by Turner et al. (1987). Social categorization implies the categorization of oneself and others into differentiated categories based on perceived similarities and differences among people. People with similar collective characteristics are grouped and described as in-group members, whereas people with distinct characteristics are placed together as out-group members. The theory suggests that individuals cognitively represent social categories as prototypes where prototypes embody all attributes (including beliefs, attitudes, values, and behaviors) that characterize groups and distinguish them from other groups.

In the current study, it is proposed that individuals form prototypes based on generations. People belonging to one generation differ based on essential characteristics such as beliefs, attitudes, perspectives, work values, and motivation (Singh et al., 2020). An employee belonging to one generation categorizes themself into in-group and coworkers from other generations into out-group. This process of forming social categories based on generational attributes can severely restrict communication, undermine trust and impede interaction and knowledge sharing (Tajfel, 1981; Turner, 1981).

Diversity at the workplace allows for more ideas, creativity, and a greater chance to identify a workable solution to a specific problem that increases the potential for advanced performance. This view corresponds to generational diversity as well. Generational diversity is associated with different generations carrying nonoverlapping perspectives, expertise, and experiences that help in creating a more extensive knowledge base leading to better decisions, faster problem-solving, and positive group outcomes (Wey Smola and Sutton, 2002; Kundu and Mor, 2017). However, generational diversity may sometimes lead to negative consequences at work such as increased ambiguity, miscommunication, conflicts, discrimination, less trust, lowered job satisfaction and commitment, difficulty achieving consensus, and decreased productivity (Dickerson et al., 2010; Kunze et al., 2013; Urick et al., 2016). Thus, it becomes essential for organizations to acknowledge these generational differences as valuable and promote greater inclusion at work to benefit from a multigenerational workforce. Creating an inclusive workplace for employees from different generations is the fundamental way to manage generational diversity effectively (Ashikali and Groeneveld, 2015). Once appropriately managed, it leads to superior individual, group, and firm performance. Considering the above discussion, it is hypothesized that:

A generationally diverse workforce gives organizations access to tacit knowledge, a precious resource that differentiates an organization from its competitors. However, this knowledge needs to be shared among employees to gain and sustain competitive advantage; Generations differ from each other on specific key characteristics such as beliefs, attitudes, work values, world views, personal values, psychological traits, and workplace behaviors (Wey Smola and Sutton, 2002; Twenge, 2010; Singh et al., 2020). Drawing on social categorization theory, when multiple generations cohabit at the workplace, differences result in subgroup formation, stereotyping, and discrimination. This leads to less trust, increased task and relationship conflicts and less frequent interactions among different generations, ultimately affecting the knowledge-sharing process at work (Urick et al., 2016). Therefore, it is hypothesized that:

According to the resource-based theory, knowledge is a crucial resource that enables firms to attain superior performance and competitive advantage over tangible resources (Lubit, 2001; Andrews and Smits, 2018). Empirical results show that knowledge sharing (both implicit and explicit) among individuals has advanced individual, group, and organizational level consequences. It positively impacts individual task performance (Kim and Yun, 2015) and team performance (Srivastava et al., 2006) and stimulates organizational creativity (Wang and Wang, 2012; Wang et al., 2014). Knowledge-sharing opportunities at work help employees learn from each other’s experiences and develop high-quality solutions over arbitrary opinions. Organizations benefit by improving the speed and quality of their decisions, innovating products and services, and increasing employee retention. Knowledge sharing positively influences group performance in many different contexts (Kim and Yun, 2015; Wang and Wang, 2012; Choi et al., 2010). This study considers branch performance as a proxy for group performance, the dependent variable. Based on the above arguments, it is hypothesized that:

Literature suggests that an inclusive organizational/team climate helps in subsiding the negative effect of demographic diversity on individual and group outcomes (McKay et al., 2008; Mor Barak et al., 2016) and has a significant influence on increasing trust and knowledge-sharing behaviors among individuals (Ruppel and Harrington, 2000; Xue et al., 2011). In the case of multiple generations cohabiting at the workplace, the presence of a perceived age-discrimination climate is more likely to negatively affect trust and interactions among individuals, hampering individual and organizational performance (Kunze et al., 2011). A psychological climate free of ageism is called a positive intergenerational climate, where employees of all generations are valued, and their differences are celebrated (Liff, 1997). When employees are recognized for their uniqueness without judgment, they seem to be more motivated, engaged, and cooperative. These positive attitudes at work lead to superior individual and organizational consequences (King and Bryant, 2017; Lagacé et al., 2019). Thus, a positive intergenerational climate would weaken the negative relationship between generational diversity and knowledge sharing. The relationship between generational diversity and knowledge sharing would be stronger for the adverse intergenerational climate. Drawing on the above arguments, it is hypothesized that:

A leader has the ability and power to influence and inspire his group members through his actions and words. Researchers posit that a leader can address negative group processes such as discriminatory behaviors and conflicts (Homan and Greer, 2013; Pilhofer and Holgersson, 2017; Alvarez and Alvarez, 2018) and facilitate knowledge-sharing behaviors among employees (Xue et al., 2011). The role of a leader becomes even more pivotal in the context of generational diversity. Generational differences at work may bring in several unpleasant outcomes (Kunze et al., 2013; Urick et al., 2016), which can be minimized with effective leadership. A leader acts as a role model for his employees, and his positive actions can help the employees transcend generational boundaries (Kearney and Gebert, 2009; Al-Asfour and Larry, 2014). Leaders who equally interact, spend time, and share their expertise with members of different groups help bridge the divide among groups and enable inter-group collaboration. This boundary-spanning behavior of leaders creates a platform for individuals to exchange their ideas, opinions, and knowledge with other individuals (Salem et al., 2018). Therefore, the more the leader engages in boundary-spanning behaviors, the weaker the relationship between generational diversity and knowledge sharing, and the less the leader engages in boundary-spanning behaviors, the stronger the relationship between generational diversity and knowledge sharing. Based on the above discussion, it is hypothesized that:

Respect is one of the core organizational values that has received little attention from researchers. Respectful and fair treatment for diverse groups has always remained one of the most critical aspects of diversity training for organizations. Lack of respect for others gives rise to most conflicts in organizations (Rosado, 2006). Mishra and Spreitzer (1998) propose that when employees are treated fairly and with respect, they are more likely to trust others and cooperate with them. It is seen that employees who are increasingly respected at the workplace by their peers and supervisors are more likely to reciprocate this positive job experience with increased collaboration and interpersonal helping behaviors (San Martín-Rodríguez et al., 2005; Singh and Winkel, 2012). Employees from all generations need to be treated with respect. Young employees should value their older colleagues' enriched knowledge and experience, and more senior employees should be more accommodating of the innovative ideas and updated product/market knowledge that young employees bring to the table. This level of respect helps create a harmonious workplace, proffering benefits for all. Hence, the more perceived respect, the weaker is the relationship between generational diversity and knowledge sharing, and the less the perceived respect, the stronger the relationship between generational diversity and knowledge sharing. Based on the above proposition, it is hypothesized that:

Banking is a classic example of a knowledge-driven industry. The processes in banks are complex and detailed, and the core competitiveness of this industry is a function of its ability to utilize knowledge (Windrum and Tomlinson, 1999) effectively. Financial liberalization and internalization coupled with fierce competition have put tremendous pressure on the banking industry. Banks have realized over time that physical assets can provide short-term competitiveness in the industry. There is a need to exploit the new intangible assets (knowledge being the most crucial resource) to achieve long-term sustainability (Ali and Ahmad, 2006). Social knowledge remains an essential aspect of knowledge for banks where social refers primarily to sharing. Experienced workers have more explicit and implicit knowledge of the operational and legal aspects of activities relevant to them. Automation and digitalization of banking processes require employees to equip themselves well with technology-related skills. Young workers have a good knowledge of information systems. Therefore, knowledge sharing among employees becomes necessary to improve operational efficiency, create new products, service innovation, customer-centricity, and higher customer value for any bank (Shih et al., 2010; Dutt et al., 2011).

Data were collected from the employees working in the urban branches of the banking industry in Hyderabad, India. As per Kundu and Mor (2017), generational diversity is one of the top 10 trends discussed among HR and business leaders, and it is prevalent in the banking industry along with a few other sectors such as technology, consumer business, media, and telecommunications, life sciences and health care. Further, Posthuma and Campion (2009) highlighted that age-based stereotypes (ageism) are more prevalent in specific industries, such as retail, banking, insurance, and information technology. Additionally, when the outbreak of coronavirus (COVID-19) pandemic pushed several industries to render work-from-home opportunities for their employees, the banking industry was exempted from that provision. Banking services became even more essential during this crisis to avoid the fund crunch and financial hassles for people across the country. Considering the above arguments, choosing the Indian banking industry for the current study becomes relevant.

The sample comprises four public-sector and four private-sector banks (NSE/BSE indexed) with 12 branches of each bank. The number of respondents from public-sector and private-sector banks was 327 and 308, respectively. Data were collected through a questionnaire comprising 40 items reflecting all the constructs (Generational diversity, knowledge sharing, group performance, intergenerational climate, boundary-spanning leadership, and respect). The study followed a cross-sectional approach for collecting data. The clerical and managerial employees in the bank branches were contacted through offline survey methods. The authors provided a brief description of the study to each branch manager and requested his permission to survey branch members. Further, the employees were informed about the objective of conducting the study, and their prior consent was taken. Information regarding branch performance was taken from both, the branch employees and the branch managers. Information from two different sources helped in reducing the extent of common method bias. Privacy, confidentiality, and data anonymity were maintained throughout and after the survey. Employees were assured that no right or wrong answers exist for the questions asked.

Demographic variables such as age group/generation, gender, marital status, experience with the current bank, cadre, and educational qualification were captured. The sample consists of 17.2% of respondents belonging to generational group one (G1), 23.1% belonging to generational group two (G2), and 59.7% belonging to generation three (G3). 54% of the respondents were males, and 46% were females. It was observed that 26.3% of the respondents had greater than ten years of work experience with the current bank, and 7.7% with less than two years of experience. As per the respondents’ cadre, 14.7% were clerks, 42.3% officers, 29% managers, 6% senior managers, and 8% executives. Regarding their educational qualification, 42.9% of the respondents were graduates, 55.1% were postgraduates, and 2% mentioned their qualification as others. Of all, 76.8% of respondents were reported to be married.

Generational diversity was measured using Blau’s (1977) index of heterogeneity (1 − ∑ρ_i²), where ρ was the proportion of group members in a category, and i was the number of different categories represented on a group. The present study considered three categories of generations: Conservatives (1947–1969), Integrators/Baby Boomers (1970–1984), Millennials/Gen Y (1985–1994), and Gen Z/iGen (Ghosh and Choudhari, 2009; Barhate and Dirani, 2022). All three categories were used to calculate Blau’s index. The range of the index depends on the number of categories, where the number ranges from 0 to (i – 1)/i. Therefore, generational diversity could range from 0 when only one generation was present to 0.67 when there were equal numbers of all three generations present in the group. The index started with a zero-point representing complete homogeneity to larger numbers indicating greater diversity.

The study captured both explicit and implicit knowledge. Knowledge sharing was measured using a five-item scale (two-item for explicit knowledge and three-item for implicit knowledge) by Bock et al. (2005). The items ranged on a Likert scale of 1–5, 5 = strongly agree, 4 = agree, 3 = neither agree nor disagree, 2 = disagree, 1 = strongly disagree. The reliability coefficient for this scale was 0.82.

Branch performance from employees and branch managers was measured using a four-item scale developed by Chow and Chan (2008). The items ranged on a Likert scale of 1–5, 5 = excellent, 4 = good, 3 = average, 2 = poor, 1 = very poor. The reliability coefficient for this scale was 0.853. This study considers the branch performance of banks as a proxy for group performance.

The intergenerational climate is a measure of ageism attitudes and perceptions at the workplace and was measured using Workplace intergenerational climate scale (WICS) developed by King and Bryant (2017). The scale was a 20-item measure and has five dimensions, namely, Lack of Generational Stereotypes (LGS), Intergenerational Contact (IC), Positive Intergenerational Affect (PIA), Workplace Generational Inclusiveness (WGI), and Workplace Intergenerational Retention (WIR). Sixteen items ranged on a Likert scale of 1–5, 5 = strongly agree, 4 = agree, 3 = neither agree nor disagree, 2 = disagree, 1 = strongly disagree. Rest four items ranged on a Likert scale of 1–5, 5 = very often, 4 = often, 3 = neutral, 2 = rare, 1 = very rare. The reliability coefficient for this scale was 0.863.

Boundary-spanning leadership refers to an employee’s perception about whether his leader is engaged in boundary-spanning behaviors or not. Boundary-spanning leadership was measured using a three-item scale adopted from the Intergroup Rhetoric Scale by Rast (2013). The items ranged on a Likert scale of 1–5, 5 = very much, 4 = more, 3 = neutral, 2 = little, 1 = not at all. The reliability coefficient for this scale was 0.916.

Respect was measured using a 7-item scale by Smith and Tyler (1997). The items captured the respondent’s overall perception of respect from their colleagues. The items ranged on a Likert scale of 1–5, 5 = strongly agree, 4 = agree, 3 = neither agree nor disagree, 2 = disagree, 1 = strongly disagree. The reliability coefficient for this scale was 0.799.

Formulated hypotheses were tested using partial least square structural equation modeling (PLS-SEM) through the SmartPLS version 3 software package. There are three reasons to use this technique for the current study. First, the PLS-SEM technique allows latent constructs to be modeled as reflective and formative indicators. The present study measured generational diversity using an index that has formative indicators, and reflective indicators represented all the other constructs. Second, the current model had two mediating variables and three moderating variables, making the model a little complex to use multiple regression techniques for data analysis. PLS-SEM seemed to be appropriate for this study as it permits the simultaneous estimation of multiple causal relationships reducing the endogeneity problem that may arise using multiple regression. Third, PLS-SEM is an appropriate technique for exploratory research where theory is underdeveloped. This study is also the first to investigate the majority of the relationships stated.

The descriptive statistics (mean and standard deviation) and frequency distribution of the measurement items of the current study. The standard deviation ranged from 0.13 to 0.62, showing that data are more clustered around the mean. The correlation values among all the constructs are presented in Table 1. As hypothesized, generational diversity was negatively related to knowledge sharing (r = −0.195) and positively associated with branch performance (r = 0.349). Further, knowledge sharing and branch performance were positively correlated (r = 0.423). These results set the initial ground for further testing hypotheses and estimating β coefficients using PLS-SEM.

Indicator reliability was assessed by examining outer loadings that indicate the loading of each indicator to its construct. The values above the threshold of 0.70, suggest good indicator reliability. However, the values ranging from 0.50–0.70 are also acceptable, as highlighted by several studies in the literature (Hair et al., 2017). The majority of the items in the present study had loadings above 0.70 and items with lower loadings were emitted from the measurement model (see Table 2).

Further, partial least square structural equation modeling (PLS-SEM) was used to test the hypotheses. The proposed model examines the impact of generational diversity on knowledge sharing and branch performance. It also examines the moderating effects of intergenerational climate, boundary-spanning leadership, and respect on the relationship between generational diversity and trust. The covariance-based structural analysis relied on goodness-of-fit measures to assess the structural model, whereas PLS evaluated the structural model by examining coefficient of determination (R²) values, predictive relevance (Stone-Geisser Q²), and the effect size of path coefficients. Further, a bootstrap analysis with 2,000 resamples was performed to obtain the significance of estimates (t-statistics). All the variables chosen for the study were standardized before running PLS-SEM. The structural model from PLS analysis is presented in Figure 2.

Generational diversity was found to have a significant positive impact on branch performance (β = 0.277, t = 2.77, p = 0.006), supporting hypothesis 1. Generational diversity significantly negatively influenced knowledge sharing as proposed (β = −0.131, t = 2.08, p = 0.038), supporting hypothesis 2. Further, knowledge sharing was found to have a positive association with branch performance (β = 0.369, t = 4.146, p = 0.000), supporting hypothesis 3.

Two of the three proposed moderating effects were found to have a significant effect on the relationship between generational diversity and knowledge sharing. The intergenerational climate was found to have a significant moderating effect on the relationship between generational diversity and knowledge sharing (β = −0.139, t = 1.66, p = 0.097), such that the more positive, the intergenerational climate is, the weaker is the negative relationship between generational diversity and knowledge sharing, thus supporting hypothesis 4. Boundary-spanning leadership was also found to have a significant moderating effect on the relationship between generational diversity and knowledge sharing (β = −0.199, t = 1.969, p = 0.049), such that the more a leader engages in boundary-spanning behaviors, the weaker the negative relationship between generational diversity and knowledge sharing becomes, thereby supporting hypothesis 5. Respect was not found to significantly moderate the relationship between generational diversity and knowledge sharing (β = 0.043, t = 0.515, p = 0.607). Hence, hypothesis 6 was not supported. The structural model explained 71.5% variance in knowledge sharing (R² = 0.715) and 25.3% variance in branch performance (R² = 0.253) (Table 3).

The authors also examined Stone-Geisser’s Q² values as a criterion of predictive relevance of exogenous constructs besides evaluating the magnitude of R² (Stone, 1974; Geisser, 1974; Woodside, 2013). Q² values > 0 indicate that the structural model has good predictive relevance, whereas Q² values < 0 indicate the low predictive relevance of the model (Chin, 1998). Results of the blindfolding approach in the present study demonstrated the Q² value for branch performance as 0.158 and Q² value for knowledge sharing as 0.425 (both greater than the threshold of 0). The results suggested the satisfactory predictive relevance of the structural model (refer to Table 3) (see Table 4).

The authors found that generational diversity negatively influences knowledge sharing and positively influences branch (group) performance. These findings validate that generational differences exist at the workplace and result in the in-group and out-group formation at the workplace leading to less frequent interactions and other negative consequences (Kunze et al., 2013; Urick et al., 2016). However, if these differences are managed properly, generational diversity leads to better decisions, more creativity, and producing positive or superior group performance by creating a more extensive nonoverlapping knowledge base (Wegge et al., 2008).

The moderating effects of intergenerational climate and boundary-spanning leadership on the relationship between generational diversity and knowledge sharing were significant. Boundary-spanning leaders interact and exchange information impartially with members of all groups and are perceived as in-group prototypes by group members. This may bridge the gap between generational groups at the workplace and increase collaboration. Further, these findings reaffirm two established theories. First, an inclusive organizational climate positively shapes the effects of demographic diversity (generational diversity in this study) on individual and group performance (McKay et al., 2008; Mor Barak et al., 2016) and has a significant influence in facilitating knowledge sharing among individuals (Ruppel and Harrington, 2000; Xue et al., 2011). Second, leadership plays a paramount role in facilitating collaboration among otherwise unconnected groups. Leaders who equally interact, spend time and share their expertise with members of different groups at the workplace help bridge the divide among groups and foster collaboration (Salem et al., 2018).

However, respect was not a significant moderator in the relationship between generational diversity and knowledge sharing. The reason for data rejecting this hypothesis could be that sometimes employees’ commitment toward their organizations and superordinate goals allows them to help their coworkers at work, even if they do not respect or trust them. They also believe that management will recognize and reward them for doing so if their act of sharing knowledge with others enables their coworkers to help achieve organizational goals and improve group performance (Renzl, 2008).

The current study contributes to the literature on generational diversity, knowledge sharing, intergenerational climate, and boundary-spanning leadership. The study makes four critical contributions to the theory.

First, the extant literature on generational diversity revolves more around generational differences on several psychological characteristics among employees and their negative impact. The research related to generational diversity is scarce compared to other forms of diversity such as gender diversity, racial diversity, and cultural diversity. The present study adds to the literature by studying generational diversity in various bank branches and its impact on the performance of knowledge sharing and group (branch). This is the first empirical study to test and establish these relationships in the Indian context. Second, there are few considerable studies on age diversity and its impact on individual/group performance. However, studies related to generational diversity and its influence on individual/group outcomes are scanty. Studying generational diversity holds equal importance as age diversity does. Third, the current study contributes to social categorization theory and enriches it by making prototypes based on generational differences. Employees with similar characteristics such as beliefs, attitudes, behaviors, values, etc., are formed as one group, and employees exhibit similar characteristics as another group. This subgroup formation results in prejudice, stereotypes, and discriminatory behaviors of employees belonging to one group toward the employees of another group, negatively influencing the communication, interactions, and knowledge sharing among employees at the workplace. Fourth, this is the first-ever study to empirically test the moderating effects of intergenerational climate and boundary-spanning leadership on the relationship between generational diversity and knowledge sharing.

Organizations are becoming more age-diverse than ever before. A workplace today comprises three to four generations cohabiting and working together. Organizations celebrate each generation's uniqueness by understanding and addressing their different expectations and work styles, thereby facilitating more collaboration and knowledge sharing at work. The present study would help human resource managers, practitioners, and line managers understand the impact of a generationally diverse workforce on knowledge sharing and group performance. The study’s findings revealed that generational diversity negatively influences knowledge sharing while knowledge sharing positively influences group performance. Thus, organizations need to be aware of certain factors that may help in mitigating the negative effect of generational diversity on knowledge sharing, as knowledge sharing among employees leads to positive individual and group performance. The present study highlights the importance of a positive intergenerational climate and boundary-spanning leadership in facilitating knowledge sharing among employees belonging to different generations.

Line managers and human resource managers should focus on building or creating a psychological climate free from ageist attitudes, where employees from different generations are being respected, and their contributions are being valued, recognized, and appreciated. Employees from one generation should not prejudice or stereotype employees from a different generation. A positive intergenerational climate would help bring employees belonging to different generations together by increasing intergenerational contact and interactions that would further reduce the age-discrimination attitudes at work. Managers’ and organizations’ efforts toward creating an inclusive work environment for all the generational groups will encourage employees to shed off the surface-level differences or stereotypes against employees of other generations if they hold any.

Also, organizations would aim to hire leaders who display boundary-spanning behaviors because leaders with such quality dedicate their efforts and resources equally among employees from different generations, guide all of them equally and improve the interactions, collaboration, and knowledge sharing among employees belonging to different generations. This helps in bridging the gaps among employees belonging to different generations by inspiring them to be like their leaders or mimic their leader’s boundary-spanning actions. Organizations should also arrange training programs for existing leaders on boundary-spanning behaviors to help them acquire or strengthen the boundary-spanning skills.

Managers may also identify other factors that foster more knowledge sharing and collaboration among employees in a multigenerational work environment. A smooth multigenerational integration can be attained if employees from different generations listen to each other. Senior employees should acknowledge the unbiased inputs of the younger group, and youngsters should learn to respect and appreciate the wisdom of the aging workforce. The confluence of multiple generations at the workplace may result in subgroup formation and discrimination due to age. These behaviors may hamper trust, respect, and knowledge sharing between employees.

The study also has a few limitations that are important to consider. The study uses a cross-sectional design for data collection, and therefore, it becomes difficult to establish the causal relationships among the constructs. Future studies require a longitudinal research design to establish the causal relationships among the constructs. The present study is conducted in the banking industry and restricts future researchers and practitioners from generalizing the findings to other sectors. More similar kinds of studies are required across different sectors and cultural contexts to generalize the results. The present study has examined the effects of intergenerational climate and boundary-spanning leadership as moderators on the relationship between generational diversity and knowledge sharing. Both moderators helped subside the negative consequences that may arise when multiple generations work together in any organization. However, researchers in future studies can examine the role of other moderating variables on the relationship between generational diversity and knowledge sharing.

There is a growing realization among organizations on the importance of increasing generational diversity at the workplace and its positive and negative individual and organizational consequences. Managers constantly recognize the need to effectively manage multiple generations at work since the unique contributions from different generational groups result in superior individual and group performance, high-quality decision-making, problem-solving, and other work-related benefits. However, managing a multigenerational workforce remains a challenge before human resource managers and line managers in any organization. It is necessary to identify appropriate practices, tools, and strategies and successfully implement them throughout the organization to derive the benefits from different generational groups by restricting the adverse outcomes, such as age-discrimination behaviors, conflicts, less trust, and knowledge sharing, that may arise when multiple generations cohabit at the workplace. Generational diversity has received increased attention from researchers, practitioners, and organizations lately and provides greater scope for future researchers to weave out new paths for this underexplored area.

Corrigendum: It has come to the attention of the publisher that the article, Hans, S., Nayeem, A.M., Mikkilineni, S. and Gupta, R. (2023), “Exploring the relationship between generational diversity and knowledge sharing: the moderating role of workplace intergenerational climate, boundary-spanning leadership and respect”, Employee Relations, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/ER-11-2022-0507, incorrectly stated the institution in which author Gupta R. is based. Our guidelines state that the ScholarOne record must accurately include all affiliation details at initial submission. Gupta R.'s affiliation was listed as “IIM Ranchi, Kharagpur, India” and has been amended to “Indian Institute of Management Raipur, India”.