Organizational culture as an explanation for job search effort across small, medium, and large firms

1. Introduction

Individuals seek employment as new entrants, job losers, or employed job seekers. The term search for job alternatives refers to situations in which employed individuals actively pursue other job opportunities. At any given time, these individuals may engage in such searches. The literature identifies job search efforts as a proxy for employees’ withdrawal intentions (Blau, 1993; Mobley et al., 1979). Employees may initiate job searches as a voluntary response to organizational contexts or personal circumstances (Shaw et al., 1998).

When considering organizational contexts, employees’ withdrawal intentions are often influenced by attributes that lie within the organization’s control. One such attribute is organizational culture, which encompasses the social fabric of an organization, including its collective values, beliefs, and assumptions (Arogyaswamy & Byles, 1987; Chatman & O’Reilly, 2016; Denison & Mishra, 1995; Schein, 1985).

A review of the literature reveals that much of the existing research has focused on the impact of organizational culture on firm performance, while comparatively less attention has been given to its effect on employees. Empirical studies examining the relationship between organizational culture and job search effort or withdrawal intentions remain scarce (Cronley & Kim, 2017; Kyndt et al., 2009; Sheridan, 1992).

This study seeks to address this gap by investigating whether organizational culture compels employees to search for job alternatives. Additionally, it examines the moderating role of firm size in shaping the relationship between organizational culture and job search effort.

In the organizational context, many factors can be considered contextual. Examples include firm size (e.g., micro, small, medium, large), firm ownership (e.g., locally owned, jointly owned by local and foreign entities, family-owned, non-family-owned), and customer base (e.g., local trade only, export trade only). However, the literature distinguishes between factors that are contextual by design, such as firm ownership and serving customers overseas (Neckebrouck et al., 2018), and those that are contextual by circumstance, such as firm size (Ogunyomi & Bruning, 2016). For instance, a large organization may operate as a family-owned business, reflecting the deliberate decisions of its owners to design the business accordingly (Neckebrouck et al., 2018). Conversely, as a business grows, the number of employees may naturally increase, leading a firm initially categorized as small to shift into the medium-sized category (European Commission, 2003; UNIDO, 2004). In this study, firm size—defined by the number of employees—is identified as an organizational contextual factor shaped by circumstance.

This perspective aligns with the arguments of structural contingency theory (Child, 1975; Hickson et al., 1969) and critical resource theory (Baker et al., 1997; Holmström, 1999; Holmström & Roberts, 1998), which are reviewed in Section 2.3. Previous research grounded in these theories highlights firm size as a critical factor in national economic growth. For example, European countries with a higher proportion of large firms tend to exhibit more capital-intensive industries, higher-wage sectors, substantial research and development (R&D) activities, efficient judicial systems (Kumar et al., 2001), and greater productivity growth at the sectoral level (Pagano & Schivardi, 2003).

At the firm level, research has shown that larger firms, compared to smaller ones, are more likely to exhibit strategic orientations (Sirén et al., 2017), adopt new technologies (Bordonaba‐Juste et al., 2012), and drive innovation (Ettlie & Rubenstein, 1987; Vaona & Pianta, 2008; Zona et al., 2013). Even within small and medium-sized enterprises (SMEs), firm size emerges as a key determinant of differences in organizational practices (Gabrielli & Balboni, 2010; Merrilees et al., 2011). These findings challenge the common assumption that SMEs constitute a homogenous group distinct from larger firms. For example, studies by Sirén et al. (2017) and Zona et al. (2013) have demonstrated that firm size moderates the relationship between key organizational variables. However, prior research has not explored whether firm size influences employee behavior, such as job search effort.

In the present study, firm size is treated as a moderator in the relationship between organizational culture and employees’ job search effort. The unit of analysis comprises employees permanently engaged in one of three categories of private sector firms operating in Sri Lanka, a small island nation in South Asia.

The contribution of this study is threefold. First, it aims to provide new evidence on the effect of organizational culture on employees’ job search effort, addressing a gap in the literature, particularly in the context of firms of varying sizes. Second, by examining firm size as a moderating factor, the study offers insights into how firm size shapes the relationship between organizational culture and job search behavior. Third, it challenges the assumption that SMEs form a homogenous group by investigating small, medium, and large firms, thereby contributing to a more nuanced understanding of firm size diversity and its implications.

This paper is structured as follows: the next section provides a review of the literature on job search behavior and organizational culture, identifying key gaps and proposing hypotheses. The subsequent section outlines the study’s methodology, followed by a presentation of the findings. Finally, the implications for theory and practice are discussed, along with suggestions for future research.

2. Review of literature

2.1 Job search effort as an explanation for job search behavior

Job search behavior plays a critical role in securing alternative employment or finding a new job and is frequently identified as a proxy for withdrawal intention (Blau, 1993; Kanfer et al., 2001; Kopelman et al., 1992; Mobley et al., 1979). The theory of self-regulation provides a robust framework for understanding job search behavior (Bandura, 1991; Kanfer et al., 2001; Koopmann et al., 2021; Wanberg et al., 2010).

Self-regulation is defined as an “intraindividual deliberate process that enables individuals to initiate and maintain their goal-directed activities and guide their goal attainment over time and across changing situations” (van Hooft, 2016b, p. 7). Building on the principles of self-regulation, job search behavior begins when individuals initiate efforts to seek new opportunities and culminates in a change in their current employment (Blau, 1993; Kanfer et al., 2001).

Expanding on this concept, job search behavior is categorized along three dimensions: intensity-effort, content-direction, and temporal-persistence (Kanfer et al., 2001, p. 838). Prior research has often examined these dimensions independently, as each requires a range of personal resources such as time, effort, social connections, and financial investment. This approach is supported by studies emphasizing the importance of “breaking job search behavior into distinct dimensions” (Blau, 1993, p. 327; see also Kanfer et al., 2001; Koopmann et al., 2021).

Within the self-regulation framework, the present study focuses on the effort individuals invest in searching for job alternatives (Blau, 1993; da Motta Veiga et al., 2021; Kanfer et al., 2001; Wanberg et al., 2010). The literature presents varying approaches to measuring this effort. For instance, studies like those by Kanfer et al. (2001) and Wanberg et al. (2010) have quantified effort using intensity ratios, such as the number of hours or instances dedicated to job search activities (e.g., “How many hours have you spent on your job search today?” from Wanberg et al., 2010).

In contrast, other studies, including Blau (1993) and da Motta Veiga et al. (2021), have measured effort through behaviors using Likert-type response scales (e.g., “I spent a lot of time looking for job opportunities,” as in da Motta Veiga et al., 2021). The literature suggests that behavioral measures of effort are more effective in explaining subsequent withdrawal intentions or transitions to new employment than intensity-based measures. Kanfer et al. (2001) highlight that “an advantage of the broader effort measure is that it may capture behaviors and cognitions (e.g., emotional energy, planning, and strategizing) important to the job search behavior that may not be captured in an intensity measure.” (p. 844).

Based on these insights, the present study adopts a Likert-type response scale to assess job search effort, as outlined in the methodology section.

2.2 Organizational culture and job search effort

From a self-regulation perspective, job search behavior is shaped by global-level trait-like predictors, contextual-level predictors, and situational-level predictors (van Hooft, 2016a). Among these, contextual-level predictors are defined as “constructs concerning specific life domains (e.g., work)” (van Hooft, 2016a, p. 7). In the context of job search behavior, these predictors specifically arise from “the domain of employment” (van Hooft, 2016a, p. 21). Similarly, Kanfer et al. (2001) argue that job search effort emerges as a response to the state of affairs within an individual’s current workplace. Building on this self-regulation framework, the present study identifies organizational culture as a key contextual-level predictor within the employment domain. Organizational culture, representing the social fabric of an organization, reflects the workplace environment and prevailing conditions, which can potentially trigger job search effort.

Organizational culture embodies the fundamental assumptions shared by employees about how an organization functions, assumptions that evolve over time as the organization matures. Much research has been conducted on organizational culture. Regarding its value and rarity, Barney (1986) observes: “Previous research has indicated that some organizational cultures, far from being rare, are likely to be quite common among any given set of firms. Indeed, some have argued that although cultures may appear to be unique or specific to a given firm, they sometimes actually reflect an underlying commonality and function, and thus are not rare at all.” (p. 660). The functionalist approach highlights the role of organizational culture in achieving important outcomes (Chatman & O’Reilly, 2016; Denison & Mishra, 1995). Specifically, regarding outcomes that affect employees, Barney (1986) asserts: “Firms that are successful at obtaining productivity through their people generally have an organizational culture that supports and values the worth of the employee. Firms without such a supportive culture generally do not succeed in maximizing their productivity through their people.” (p, 660). Here, the theoretical argument of the functionalist approach is that organizational culture directly influences how employees within a particular organization perceive events and shape their behavior (Barney, 1986; Denison & Mishra, 1995; Schein, 1985).

Several studies, such as those by Cronley and Kim (2017), provide evidence that organizational culture influences employees’ withdrawal intentions or actual voluntary turnover. Additionally, studies by de Silva (2016), Kyndt et al. (2009), and Sheridan (1992) suggest that organizational culture significantly impacts employee retention.

Building on these arguments, the present study posits that employees’ job search effort is influenced by organizational culture. Furthermore, as discussed in the introduction and reviewed below, the study hypothesizes that the relationship between organizational culture and job search effort is moderated by firm size.

The research model proposed in this study is presented in Figure 1. The remainder of this section reviews the relevant literature to support the proposed research model and formulate hypotheses.

Figure 1. Research model

2.2.1 Organizational culture dimensions

The fundamental arguments surrounding organizational culture can be categorized into two perspectives. One perspective suggests that organizations reflect a cross-section of society, exhibiting cultural attributes unique to that society (Gardner et al., 2018; Taras et al., 2010). Studies supporting this view often utilize national culture dimensions to interpret organizational culture (Gardner et al., 2018; Gardner & Wickramasinghe, 2023). The other perspective argues that organizational culture can be understood through dimensions specific to the organizations themselves (Chatman & O’Reilly, 2016; Denison & Mishra, 1995). This study adopts the latter perspective. The subsequent sections review the literature that interprets organizational culture through organization-specific dimensions.

The literature on organizational culture is extensive, offering researchers a wide array of conceptualizations. For instance, Jung et al. (2009) provide a comprehensive review of 70 different conceptualizations of organizational culture, detailing their characteristics and technical properties (Chatman & O’Reilly, 2016).

Most theoretical and empirical research, however, discourages combining organizational culture dimensions into a single latent variable (Chatman & O’Reilly, 2016; Denison & Mishra, 1995; Jung et al., 2009). Denison and Mishra (1995) argue that each cultural dimension uniquely relates to specific outcomes, making it inappropriate to aggregate them into a single variable. This approach has enabled researchers to focus on the distinct effects of individual dimensions on particular outcome variables. For example, Hartnell et al. (2016) selected “outcome orientation” and “aggressiveness” from the eight dimensions identified by O’Reilly et al. (1991) to examine their impact on firm performance. Similarly, Badawi et al. (2019) investigated the dimension of “adaptability” from Denison and Mishra’s (1995) framework to study its influence on SME performance.

Given the extensive conceptualizations of organizational culture, this study adopts the four dimensions proposed by Denison and Mishra (1995): involvement, consistency, adaptability, and mission. These dimensions reflect “the trade-offs between stability and flexibility and between internal focus and external focus” (Yilmaz & Ergun, 2008, p. 291). Specifically, involvement represents flexibility and internal integration; consistency represents stability and internal integration; adaptability represents flexibility and external integration; and mission represents stability and external integration (Denison & Mishra, 1995).

Denison and Mishra (1995) note that “involvement and adaptability are indicators of flexibility, openness, and responsiveness, and were strong predictors of growth,” whereas “consistency and mission are indicators of integration, direction, and vision, and were better predictors of profitability.” (p. 204). These dimensions are also significant predictors of various organizational performance criteria, including employee perceptions and behaviors.

Previous studies have employed these dimensions to explore organizational culture’s effects on employees. For instance, they have been used to investigate employee retention (de Silva, 2016) and occupational stress (Nair et al., 2021). Building on this foundation, the present study focuses on the effect of organizational culture on employees’ job search effort.

The dimensions proposed by Denison and Mishra (1995) have gained significant traction since their introduction and have been validated across various countries (Denison, Haaland, et al., 2004; Denison, Lief, et al., 2004; Fey & Denison, 2003; Gillespie et al., 2008; Kotrba et al., 2012; Yilmaz & Ergun, 2008). Specifically, they have been applied to research on organizations of varying sizes, including SMEs (Badawi et al., 2019; Nair et al., 2021), firms with 50 or more employees (Denison & Mishra, 1995; Kotrba et al., 2012; Yilmaz & Ergun, 2008), firms of all sizes and growth stages (Denison, Haaland, et al., 2004), and comparisons between large and small firms (Zeng & Luo, 2013). In the Sri Lankan context, these dimensions have been utilized by de Silva (2016) and Subasinghe and Wickramasinghe (2012).

The following sections examine each dimension in relation to job search effort, providing a foundation for the arguments advanced in this study.

Involvement refers to empowering employees by incorporating their input into decision-making processes, fostering their skill development, and organizing them into teams (Fey & Denison, 2003). This dimension highlights flexibility and the internal integration of resources, particularly human resources (Denison & Neale, 2019). By building human capacity, cultivating a sense of ownership, and encouraging shared responsibility, involvement enables employees to feel they can make meaningful contributions to the organization (Denison & Neale, 2019).

Involvement aims to instill a strong sense of ownership, thereby strengthening employees’ commitment to the organization. This perspective is extensively supported in organizational studies (Fey & Denison, 2003; Kotrba et al., 2012; Spreitzer, 1995; Yilmaz & Ergun, 2008). Organizations excelling in the involvement dimension are generally associated with more favorable employee attitudes (Yilmaz & Ergun, 2008).

Thus, the following hypothesis is proposed:

H1a: Involvement significantly predicts job search effort, such that higher levels of involvement are associated with lower levels of job search effort.

Consistency refers to the promotion of common principles, rules, procedures, and behavioral norms within the organization to ensure high levels of coordination, integration, and predictability (Denison & Mishra, 1995). When organizational members share common values, a sense of identity, and clear expectations, they are better equipped to reconcile differences, reach agreements, and collaborate effectively in the organization’s best interest (Yilmaz & Ergun, 2008). These experiences help foster more favorable attitudes toward the organization (Denison & Neale, 2019). This perspective on consistency is widely supported in organizational studies literature (Senge, 1990).

Thus, the following hypothesis is proposed:

H1b: Consistency significantly predicts job search effort, such that higher levels of consistency are associated with lower levels of job search effort.

Adaptability refers to an organization’s capacity to respond to changes in the external environment, orient itself toward customers, take risks, and learn from past mistakes (Denison & Mishra, 1995). In essence, adaptability enables internal adjustments in response to external conditions. Organizations with strong adaptability focus on customer needs, respond swiftly to demands, enhance their ability to adapt to external contingencies, and demonstrate creativity in their responses (Denison & Neale, 2019).

The organizational studies literature supports this perspective on adaptability (Argyris & Schön, 1978; Senge, 1990). Employees in organizations with strong adaptability may actively seek innovative ways to perform their work, better serve customers, and continue learning from successes and failures (Denison & Neale, 2019). Such experiences foster more favorable attitudes toward the organization.

Thus, the following hypothesis is proposed:

H1c: Adaptability significantly predicts job search effort, such that higher levels of adaptability are associated with lower levels of job search effort.

Mission refers to an organization’s ability to articulate a clear long-term vision, establish goals, and formulate strategies (Denison & Mishra, 1995). This understanding of mission is well-supported in organizational studies literature (Barney, 1986; Mintzberg, 1987). For example, Barney (1986) argues that a firm’s mission directly reflects cultural assumptions about its business operations and the way it conducts those operations. Similarly, O’Reilly et al. (1991) highlight the importance of a clear guiding philosophy as a core component of organizational culture.

A strong mission enables an organization to effectively communicate its purpose and future direction to employees (Fey & Denison, 2003). Employees in organizations with a well-defined mission are more likely to experience a sense of purpose, direction, and meaning in their organizational activities (Yilmaz & Ergun, 2008).

Thus, the following hypothesis is proposed:

H1d: Mission significantly predicts job search effort, such that higher levels of mission are associated with lower levels of job search effort.

2.3 Firm size

The present study examines firm size through two lenses: (1) its direct relationship with employees’ job search effort and (2) its moderating role in the relationship between organizational culture and job search effort. This analysis is grounded in two key theoretical frameworks: structural contingency theory (Child, 1975; Hickson et al., 1969) and critical resource theory (Baker et al., 1997; Holmström, 1999; Holmström & Roberts, 1998).

Structural contingency theory identifies firm size as a crucial structural variable within an organization. It argues that firm size influences a range of organizational elements, including leadership style, strategy selection, level of decentralization, job design, and other operational practices. Moreover, it affects how organizations respond to environmental uncertainties (Donaldson, 2015).

Critical resource theory, on the other hand, underscores the significance of owning critical assets—such as brand names, intellectual property, innovative processes, and physical assets—in shaping a firm’s production processes. Larger firms are generally better equipped with these resources, enabling them to expand their operational boundaries and gain a competitive advantage (Kumar et al., 2001).

The following sections review the relevant literature to support the arguments presented in Figure 1.

2.3.1 Firm size and employees’ job search effort

The literature has long recognized firm size as a critical variable influencing employee behavior (Pugh et al., 1969; Zeng & Luo, 2013). Drawing on structural contingency theory, prior research indicates that larger firms tend to excel in areas such as innovation (Ettlie & Rubenstein, 1987; Vaona & Pianta, 2008; Zona et al., 2013), strategic orientation (Sirén et al., 2017), and the adoption of new technologies (Bordonaba‐Juste et al., 2012).

Similarly, critical resource theory suggests that larger firms possess more critical assets than smaller firms, such as brand equity, intellectual property, and physical resources, which allow them to expand their operational boundaries (Kumar et al., 2001; Pagano & Schivardi, 2003). This resource advantage makes larger firms particularly attractive to employees. For instance, in South Korea, large corporations are widely regarded as the most desirable employers (East Asia Forum, 2024; Park, 2013; The Korea Bizwire, 2018).

This preference stems from benefits associated with larger firms, including higher salaries (East Asia Forum, 2024; Park, 2013), generous welfare programs (East Asia Forum, 2024; Park, 2013; The Korea Bizwire, 2018), better working conditions (The Korea Bizwire, 2018), and greater job security (East Asia Forum, 2024). Employees also consider factors like a firm’s reputation (The Korea Bizwire, 2018), its long-term vision (The Korea Bizwire, 2018), and its commitment to sustainability and green initiatives (Wicaksari et al., 2024) when choosing employers.

Therefore, the following hypothesis is proposed:

H2: Firm size significantly predicts employees’ job search effort, such that larger firm size is associated with lower levels of job search effort.

2.3.2 Firm size as a moderator between organizational culture and job search effort

Previous research, guided by structural contingency theory, reveals that firms differ significantly in how they manage operations—such as leadership, decentralization levels, and decision-making processes—and in how they respond to uncertainties and changes in their organizational environment (Bordonaba‐Juste et al., 2012; Donaldson, 2015; Gabrielli & Balboni, 2010; Merrilees et al., 2011; Sirén et al., 2017; Štangl Šušnjar et al., 2016; Zona et al., 2013). These studies indicate that such differences are particularly pronounced in larger firms (Bordonaba‐Juste et al., 2012; Gabrielli & Balboni, 2010; Merrilees et al., 2011; Štangl Šušnjar et al., 2016).

Additionally, within the framework of structural contingency theory, research underscores the need to avoid treating small and medium-sized enterprises (SMEs) as a homogenous group. For example, Ogunyomi and Bruning (2016) argue that “the circumstances of the organization, i.e., whether micro, small, medium, or large at a particular point in time, determine the types of strategies, policies, aims, and lists of activities that will be adopted.” (p. 615). Similarly, studies by Bordonaba‐Juste et al. (2012), Sirén et al. (2017), and Zona et al. (2013) emphasize the importance of examining firm size as a moderating factor, with firm size typically operationalized by the number of employees engaged.

Drawing on critical resource theory, prior research (Baker et al., 1997; Holmström, 1999; Holmström & Roberts, 1998; Rajan & Zingales, 2001) highlights that larger firms have superior access to critical resources, such as brand names, intellectual property, innovative processes, and physical assets. These resources not only enhance their ability to manage operations effectively but also provide a significant competitive advantage. Moreover, larger firms are better equipped to tolerate potential losses from trial-and-error strategies when adapting to changes in the external environment (Damanpour, 2010).

Expanding on this theoretical framework, Teo and Pian (2003) demonstrated that only larger firms possess the necessary resources to undertake significant business transformations. Similarly, Zhu et al. (2003) observed that larger firms, due to their resource advantages, are better positioned to achieve faster returns on investment. These findings underscore the crucial role of resource availability in driving both firm-level transformations and sustained long-term performance.

In addition, studies such as Teo and Pian (2003) suggest that larger firms are more inclined to adopt innovative technologies, further solidifying their competitive edge. Consequently, prior research—including Kumar et al. (2001) and Ettlie and Rubenstein (1987)—emphasizes the importance of exploring firm size as a moderating factor. This perspective reveals how larger firms leverage their superior resources to shape organizational outcomes and respond effectively to environmental demands.

Summarizing the arguments from the literature reviewed above, prior studies have consistently highlighted firm size as a critical variable influencing both managerial decisions and employee behavior. Research guided by structural contingency theory (Bordonaba‐Juste et al., 2012; Sirén et al., 2017) and critical resource theory (Kumar et al., 2001; Rajan & Zingales, 2001) emphasizes the importance of testing the moderating role of firm size—typically defined by the number of employees—on key dependent variables.

Building on this, prior research has predominantly focused on organizational-level outcomes such as innovation (Ettlie & Rubenstein, 1987; Vaona & Pianta, 2008; Zona et al., 2013), strategic orientation (Sirén et al., 2017), e-business adoption (Bordonaba‐Juste et al., 2012), and R&D intensity (Kumar et al., 2001). However, none of the studies reviewed have investigated employee-related outcomes as dependent variables. This highlights a key gap in the literature.

Finally, in the present study, firm size is conceptualized as a moderator shaping the impact of organizational culture on employees’ job search effort. As previously discussed, this study challenges the notion that small and medium-sized firms form a homogeneous group distinct from larger firms. Instead, it argues that significant differences exist between small and medium-sized firms themselves (Bordonaba‐Juste et al., 2012; Štangl Šušnjar et al., 2016).

The organizational studies literature highlights the flexibility of small-sized firms. Mintzberg (1987) notes that small firms tend to exhibit greater adaptability, while Child and Mansfield (1972) suggest that the formal structures of large-sized firms make it difficult for them to adopt flexible management approaches. Similarly, Gray et al. (2003) found that small- and medium-sized firms possess “greater flexibility and less rigidity in decision-making and can respond more quickly to new opportunities and threats than large firms” (p. 3). Although Zeng and Luo (2013) reported no significant differences between large and small-sized firms in terms of involvement, most studies support the idea that the inherent flexibility of small- and medium-sized firms fosters higher levels of involvement.

Based on this evidence, the following hypothesis is proposed:

H3a: The impact of involvement on job search effort is more advantageous for small- and medium-sized firms than for large-sized firms.

The organizational studies literature identifies large-sized firms as having more formal and stable organizational structures (Donaldson, 2015; Pugh et al., 1969). Zeng and Luo (2013) found that large firms demonstrate greater consistency compared to small firms. Conversely, Gialuisi and Coetzer (2013) emphasize challenges faced by small firms, such as the need to establish clear work roles and minimize relationship conflicts that arise from less formalized structures.

H3b: The impact of consistency on job search effort is more advantageous for large-sized firms than for small- and medium-sized firms.

Small-sized firms, on the other hand, are better equipped to adapt to uncertain environmental conditions due to their simple structures and agility. They are more likely to take risks (Arogyaswamy & Byles, 1987) and respond quickly to environmental changes (Meggison et al., 2000). Gray et al. (2003) also highlight that small and medium-sized firms are more innovative and can respond to new opportunities and threats faster than large firms. However, Zeng and Luo (2013) observed that large firms are often stronger in adaptability. Despite this, the majority of the literature supports the idea that small and medium-sized firms are more adaptable due to their flexibility and risk-taking orientation.

H3c: The impact of adaptability on job search effort is more advantageous for small- and medium-sized firms than for large-sized firms.

Finally, large-sized firms are often characterized by a clearer long-term vision, goals, and strategies (Quinn & Cameron, 1983). Zeng and Luo (2013) found that large firms excel in mission compared to small firms. Operationalizing firm size as the number of employees, Sirén et al. (2017) demonstrated that firm size moderates the relationship between entrepreneurial orientation and strategic learning, with stronger associations in larger firms.

When new technology adoption is integrated into a firm’s long-term strategy, Bordonaba‐Juste et al. (2012) found that firm size significantly influences the adoption of e-business. They observed that “medium-sized and large firms are more likely to use e-business more intensively, and significant differences exist between ‘large and medium-sized firms’ and small-sized firms” Similarly, Teo and Pian (2003) demonstrated that only larger firms carried out business transformations meaningfully when these transformations were aligned with a long-term mission. Additionally, Zhu et al. (2003) argued that larger firms are better positioned to achieve economies of scale and faster returns on investment, which can shape their decisions regarding long-term business direction.

Based on the reviewed literature, which supports the argument that mission is stronger in large-sized firms than in small- and medium-sized firms, the following hypothesis is proposed:

H3d: The impact of mission on job search effort is more advantageous for large-sized firms than for small- and medium-sized firms.

3. Methodology

3.1 Sample and method of data collection

The unit of analysis for this study comprised employees working in small, medium, or large-sized private sector firms located in urban areas of the Western Province of Sri Lanka, the country’s main business hub and most densely populated province.

Respondent selection criteria: Participants were required to meet the following criteria:

• Hold entry-level or lower-managerial job positions.
• Possess a higher diploma (SLQF 4 or equivalent NVQ Level 6) or a bachelor’s degree (SLQF 5 or equivalent NVQ Level 7).
• Have a minimum of three years of work experience in their current workplace.
• Be engaged as permanent employees.

The three-year minimum tenure ensured respondents had sufficient experience to provide meaningful insights into organizational culture, while a five-year tenure was excluded due to high employee turnover rates in SMEs (Wickramasinghe, 2022).

Sampling methods: A combination of convenience and snowball sampling techniques was used, as these methods are recommended when:

• The population is unknown or difficult to access.
• Selecting representative samples across organizations is challenging.
• Cost-effective sampling is required (Berndt, 2020).

A Google Form was designed to filter respondents based on workplace location, firm size, employment type, years of experience, and educational qualifications. Only respondents meeting all criteria could submit their responses. The form was circulated via educational institutions, higher education institutions, and professional associations. Participation was voluntary and anonymous.

Sample distribution: A total of 252 valid responses were received, distributed as follows:

• 40% from large-sized firms, 34% from medium-sized firms, and 26% from small-sized firms.

Demographic profile:

• Gender: 31% female, 69% male.
• Educational qualifications: 42% held SLQF 4 (or equivalent NVQ Level 6), while 58% held SLQF 5 (or equivalent NVQ Level 7).
• Age: Mean age was 24 years (SD = 3.21; minimum = 22, maximum = 29).
• Tenure: Mean tenure was 4 years (SD = 0.71; minimum = 3, maximum = 5).

3.2 Measures

Organizational culture:

Organizational culture was assessed using the Denison Organizational Culture Survey (Denison & Neale, 2019). Respondents rated items on a five-point Likert scale (1 = Strongly disagree, 5 = Strongly agree). This scale has been validated in prior research conducted in Sri Lanka, including studies by de Silva (2016) on organizational culture in information technology firms and Subasinghe and Wickramasinghe (2012) on state universities.

Job search effort:

Employee job search effort was measured using a four-item scale developed by Blau (1993). Items were rated on a five-point Likert scale (1 = Strongly disagree, 5 = Strongly agree). As recommended by Blau (1993), respondents were asked to reflect on their job search effort over the past six months.

Firm size:

Firm size was measured based on the total number of employees in the respondent’s workplace. Participants provided this information as part of the survey.

Control variables:

To account for potential confounding factors, the study collected the following demographic and contextual variables as controls:

• Age: Recorded in years.
• Gender: Binary coded.
• Tenure: Measured in years of experience at the current workplace.
• Education: Binary coded based on the highest qualification attained (see Section 3.1, “Sample and method of data collection”).

3.3 Methods of data analysis

This section describes the preparation of data for analysis and the methods used to test the hypotheses. All analyses were performed using SPSS.

3.3.1 Data preparation

Firm size:

Respondents reported the number of employees in their workplaces (e.g., 48, 121, 249, 1,010). Given the variability of the data on a relative scale, log transformation was applied, as recommended by Rönkkö et al. (2022) and West (2022). Log transformation is suitable for handling data with substantial variability and addresses common analytical issues in organizational research, such as scaling for further analysis. This approach aligns with prior studies, including Ettlie and Rubenstein (1987), Kimberly and Evanisko (1981), Kumar et al. (2001), and Zona et al. (2013). The natural log of the number of employees was calculated and labeled as firm size.

Other variables:

• Age and tenure: Both variables (age in years and tenure in years) were log-transformed for consistency.
• Education level: Coded as a binary variable (0 = Higher Diploma [SLQF 4/NVQ 6]; 1 = Bachelor’s Degree [SLQF 5/NVQ 7]).
• Gender: Coded as a binary variable (0 = Female, 1 = Male).

Organizational culture:

To enhance the interpretability of interactions in moderation analyses, the organizational culture dimensions were mean-centered, following recommendations from Dalal and Zickar (2012), Iacobucci et al. (2017), and Kromrey and Foster-Johnson (1998).

Data transformation:

Log transformations were performed using the SPSS log transform function, as outlined in the IBM SPSS Statistics (2020).

Common method bias:

To assess the presence of common method bias in the independent and dependent variables, Harman’s single-factor test was conducted. Following Hair et al. (2013), the analysis confirmed that no single factor accounted for the majority of variance, indicating that common method bias was not a significant concern.

Validity and reliability testing:

The data were tested for validity and reliability to ensure the robustness of the constructs.

• Principal component factor analysis: Factor loadings exceeded 0.50, with eigenvalues greater than 1, confirming construct validity.
• Job search effort:
  • Cronbach’s alpha = 0.876, indicating strong internal consistency.
  • The construct explained 68.82% of the variance.
• Organizational culture:
  • Overall Cronbach’s alpha = 0.819, with each dimension (involvement, consistency, adaptability, and mission) achieving Cronbach’s alpha values above 0.7, confirming reliability.
  • Organizational culture explained 69.14% of the variance, distributed as follows:
    • Involvement: 25.82%
    • Consistency: 20.12%
    • Adaptability: 13.76%
    • Mission: 9.44%
• Average variance extracted (AVE): All constructs had AVE values exceeding the threshold of 0.5, supporting convergent validity (Hair et al., 2013).

3.3.2 Method of data analysis

Hierarchical regression:

The primary analysis employed hierarchical regression, following Frazier et al.’s (2004) procedure for testing moderator effects using SPSS. The steps were as follows:

1. Control variables: Age, gender, education, and tenure were included as control variables in the first step.
2. Organizational culture dimensions: Involvement, consistency, adaptability, and mission were introduced in the second step.
3. Moderator variable: Firm size was added as the moderator in the third step.
4. Interaction terms: Interaction terms between firm size and organizational culture dimensions were included in the fourth step to test for moderation effects.

Multicollinearity testing:

Variance inflation factor (VIF) scores for all constructs were below 2.00, indicating no significant multicollinearity concerns (Hair et al., 2013).

Testing hypotheses and interaction effects:

The results of the hierarchical regression were used to test the study’s hypotheses. Simple effects tests were conducted to identify significant interaction effects (Aiken & West, 1991). For the creation of moderation plots and the calculation of simple effects, the ModGraph program was used (Jose, 2013).

To demarcate the differences between small, medium, and large-sized firms and to enhance clarity for readers less familiar with advanced statistical methods, one-way ANOVA was also performed. This analysis extended beyond hypothesis testing to provide additional insights. For this purpose, the present study adopted firm size categorizations from the European Commission (2003) and UNIDO (2004), as follows:

• Small-sized firms: 10 to 49 employees.
• Medium-sized firms: 50 to 249 employees.
• Large-sized firms: 250 or more employees.

4. Findings

The results of the correlation analysis and descriptive statistics are presented in Table 1.

• The mean value of 3.93 for job search effort suggests that employees exhibit relatively high levels of job search effort.
• All dimensions of organizational culture are negatively correlated with job search effort, indicating that stronger organizational culture is associated with lower job search effort.
• Firm size, measured by the number of employees, is also negatively correlated with job search effort, suggesting that employees in larger firms are less likely to engage in job search activities.

Table 1 provides further insights:

• Employees with greater tenure demonstrate higher levels of job search effort.
• Similarly, employees with higher educational qualifications are associated with increased job search effort.

The results of the hierarchical regression analysis are presented in Table 2.

Figure 2. The effect of involvement on job search effort moderated by firm size

Figure 3. The effect of consistency on job search effort moderated by firm size

Figure 4. The effect of adaptability on job search effort moderated by firm size

Figure 5. The effect of mission on job search effort moderated by firm size

• Model 1: This model examines the influence of control variables (age, gender, education, and tenure) on job search effort.
• Model 2: This model introduces the four organizational culture dimensions. The findings confirm that organizational culture significantly predicts job search effort:
  • Each dimension—involvement (H1a), consistency (H1b), adaptability (H1c), and mission (H1d)—is negatively and significantly associated with job search effort. These results suggest that higher levels of organizational culture are linked to lower levels of job search effort.
• Model 3: This model incorporates the moderator variable, firm size. The results demonstrate that firm size significantly predicts job search effort, with higher firm size (i.e., more employees) associated with lower job search effort, thereby supporting H2.
• Model 4 examines the results when the four interaction terms were included to test the moderation effects. As shown in Table 2, all four interaction terms are significant, confirming that firm size moderates the relationship between each organizational culture dimension and job search effort.
  • Involvement (H3a): Firm size significantly moderates the relationship between involvement and job search effort for low levels of firm size (t = -2.24, p < .05) and medium levels of firm size (t = -2.15, p < .05). These findings indicate that the impact of involvement on job search effort is more advantageous for small- and medium-sized firms compared to large-sized firms. As described in the methods section, moderation plots were created using ModGraph (Jose, 2013), and Figure 2 illustrates this interaction.
  • Consistency (H3b): Firm size significantly moderates the relationship between consistency and job search effort for high levels of firm size (t = -2.41, p < .05). These results suggest that the impact of consistency on job search effort is more advantageous for large-sized firms compared to small- and medium-sized firms. Figure 3 illustrates this interaction.
  • Adaptability (H3c): Firm size significantly moderates the relationship between adaptability and job search effort for low levels of firm size (t = -2.05, p < .05) and medium levels of firm size (t = -2.28, p < .05). These findings indicate that the impact of adaptability on job search effort is more advantageous for small- and medium-sized firms compared to large-sized firms. Figure 4 illustrates this interaction.
  • Mission (H3d): Firm size significantly moderates the relationship between mission and job search effort for high levels of firm size (t = -1.81, p < .05) and medium levels of firm size (t = -1.77, p < .05). While H3d proposed that the impact of mission on job search effort is more advantageous for large-sized firms compared to small- and medium-sized firms, the findings suggest that this impact is advantageous for both large- and medium-sized firms. Therefore, H3d is partially supported. Figure 5 illustrates this interaction.

As described in the methods of data analysis, a one-way ANOVA was conducted to illustrate differences in organizational culture dimensions across firm sizes, aimed at providing insights for readers with a foundational understanding of statistics. The results are presented in Table 3.

• Involvement: Small-sized firms recorded the highest scores for involvement. The differences between small-sized and large-sized firms and between medium-sized and large-sized firms were statistically significant. However, no significant difference was observed between small-sized and medium-sized firms.
• Consistency: Large-sized firms achieved the highest scores for consistency. Statistically significant differences were found between small-sized and large-sized firms as well as medium-sized and large-sized firms, while no significant difference was noted between small-sized and medium-sized firms.
• Adaptability: Small-sized firms scored the highest for adaptability. Statistically significant differences were observed between small-sized and large-sized firms and between medium-sized and large-sized firms, but no significant difference was identified between small-sized and medium-sized firms.
• Mission: Large-sized firms reported the highest scores for mission. Statistically significant differences were found between small-sized and large-sized firms and between small-sized and medium-sized firms. However, no significant difference was noted between medium-sized and large-sized firms.

5. Discussion of findings with contributions

Organizational culture, as a factor within an organization’s control, has the capacity to significantly influence employees’ decisions to withdraw and seek alternative employment. This study investigated the effect of organizational culture on employees’ job search effort and confirmed its pivotal role in shaping job search behavior.

Firm size, operationalized as the number of employees, was examined in this study for two primary purposes:

1. To determine whether firm size significantly predicts employees’ job search effort.
2. To assess whether firm size moderates the relationship between organizational culture and job search effort.

The findings revealed the following:

1. Firm size significantly predicts job search effort: Employees in larger firms demonstrated lower job search effort compared to those in smaller firms.
2. Firm size moderates the relationship between organizational culture and job search effort: This underscores the critical role of firm size in shaping how organizational culture influences employee behavior.

5.1 Contributions to the literature

This study offers several significant contributions to the existing literature. First, while organizational culture is often studied as a determinant of organizational-level outcomes, such as financial performance, its role as a predictor of individual employee behaviors—particularly job search effort—has been largely overlooked. Building on prior research, such as Gialuisi and Coetzer (2013), this study posits that organizational culture encompasses attributes that influence employees’ decisions to voluntarily leave their firms. The findings confirm that the four dimensions of organizational culture—involvement, consistency, adaptability, and mission—significantly affect job search effort, with favorable organizational culture perceptions correlating with reduced job search behavior.

Interestingly, while previous studies, such as those by Denison and Mishra (1995) and Yilmaz and Ergun (2008), highlighted mission as the most critical dimension for organizational performance, the present study reveals that mission exerts the least influence on job search effort. In this context, regression weights for involvement, consistency, and adaptability were substantially higher, suggesting that these dimensions play a more prominent role in shaping individual behaviors. This finding aligns with Gillespie et al. (2008), who similarly reported lower importance ratings for mission in their study of customer satisfaction. These insights enrich the understanding of organizational culture’s nuanced effects on different outcomes, emphasizing that its impact varies depending on the context.

Second, the study contributes to addressing the scarcity of research on organizational culture in non-Western settings. Conducted in Sri Lanka, it responds to the growing demand for empirical studies that examine organizational culture in Asian contexts, where existing research often overlooks employee reactions like job search effort. This study’s findings are particularly relevant to scholars advocating for more diverse geographic perspectives, as noted by Denison, Haaland, et al. (2004).

Third, this study explores the dual role of firm size in shaping employee behavior. The findings confirm that firm size significantly predicts job search effort, with employees in larger firms exhibiting lower search effort. Furthermore, firm size moderates the relationship between all four dimensions of organizational culture and job search effort, reinforcing its importance as a contextual factor. These findings align with the arguments of Sirén et al. (2017) and Zona et al. (2013), who emphasize firm size as a critical moderator, as well as with Gabrielli and Balboni (2010) and Merrilees et al. (2011), who highlight firm size as a determinant of organizational practices. The study also underscores the need to avoid treating small- and medium-sized enterprises (SMEs) as a homogeneous group, as cautioned by Bordonaba-Juste et al. (2012). This distinction is particularly evident in the findings for the mission dimension, where significant differences between small-sized and medium-sized firms emerged.

Finally, this study makes a novel contribution by comparing organizational culture across firms of varying sizes in a single study. By considering organizational culture as the independent variable and firm size as the moderator, the study bridges gaps in the literature and provides context-specific insights. Denison and Mishra (1995) noted that the four dimensions of organizational culture can coexist in organizations in varying degrees. Prior research comparing organizational culture across firms of different sizes within a single study is rare. Accordingly, building on the existing literature, this study proposed hypotheses to explore these relationships, with the findings summarized as follows:

• Involvement: Smaller firms exhibited higher levels of involvement, reflecting their inherent flexibility due to less rigid structures and hierarchies. Significant differences were observed between small-sized and large-sized firms and between medium-sized and large-sized firms, but not between small-sized and medium-sized firms. These findings align with O’Reilly et al. (1991) and Zeng and Luo (2013).
• Consistency: Larger firms scored higher on consistency, characterized by formalized policies, procedures, and control systems. Differences were significant between small-sized and large-sized firms and between medium-sized and large-sized firms, but not between small-sized and medium-sized firms. This supports the work of Gialuisi and Coetzer (2013) and Zeng and Luo (2013).
• Adaptability: Small-sized firms demonstrated higher adaptability, reflecting their agility and risk-taking orientation. Differences were significant between small-sized and large-sized firms and between medium-sized and large-sized firms, but not between small-sized and medium-sized firms. These findings are consistent with Gray et al. (2003) and Zeng and Luo (2013).
• Mission: Large-sized firms excelled in mission, emphasizing long-term orientation and strategic focus. Significant differences were found between small-sized and large-sized firms and between small-sized and medium-sized firms, but not between medium-sized and large-sized firms. The findings suggest that medium-sized firms in Sri Lanka may be adopting more strategic approaches, as noted by Wickramasinghe (2022).

These findings collectively advance the understanding of how organizational culture dimensions influence employee behavior across firms of different sizes, highlighting the critical role of firm size as a contextual factor.

5.2 Contributions to practice

The findings of this study provide several practical implications for organizational leaders and managers. First, the functionalist approach underscores the critical role of leadership in shaping and transforming organizational culture (Chatman & O’Reilly, 2016; Denison & Mishra, 1995). Denison and Mishra (1995) argue that all four dimensions of organizational culture—involvement, consistency, adaptability, and mission—can coexist within an organization to varying degrees. While organizational culture tends to be stable, it is also dynamic and can be influenced by deliberate management interventions. Leaders can introduce targeted initiatives to refine existing cultural attributes or instill new ones, enhancing the organization’s capacity for survival and growth (Schein, 1985). From the perspective of reducing employees’ job search effort, such interventions might include revising operating practices, launching employee capability development programs, and addressing unmet employee expectations. These efforts aim to reshape the collective values, beliefs, and assumptions within the organization, fostering a more favorable perception of its culture. By strategically managing these cultural dynamics, leaders can create an environment that reduces employees’ intentions to seek alternative employment opportunities.

Second, attribution theory (Staw, 1975) highlights the responsibility of leaders in achieving positive organizational outcomes. Employee retention, as opposed to withdrawal, is a critical outcome directly influenced by organizational culture (Sheridan, 1992). Organizational culture can serve as a long-term preventive measure to control voluntary withdrawals, with favorable cultural characteristics preemptively reducing employees’ inclination to engage in job search efforts. This study, conducted on employees in entry-level and lower-managerial positions with at least three years of tenure, provides actionable insights for enhancing the four dimensions of organizational culture. For instance, organizations can foster involvement by making employees feel valued through practices such as prioritizing internal promotions, involving employees in ground-level decision-making, forming teams, engaging employees in developing team goals, and delegating task responsibility to teams. Similarly, consistency can be strengthened by effectively communicating organizational values during onboarding, reinforcing team relationships, and promoting inter-departmental communication to address operational bottlenecks. Adaptability can be enhanced by creating positive attitudes toward change, raising employee awareness of external shifts, and providing the necessary resources and skills to navigate these changes effectively. Finally, mission can be reinforced by involving employees in reviewing or crafting the organization’s vision, clearly communicating this vision and its competitive strategies, and establishing systems that integrate top-down target setting with bottom-up feedback mechanisms. By implementing these strategies, organizations can cultivate a cultural environment that reduces job search effort, promotes engagement, and supports long-term employee retention.

Third, the findings highlight that firm size not only directly affects employees’ job search effort but also moderates the relationship between organizational culture and job search behavior. Retaining employees is particularly critical for small- and medium-sized firms, where voluntary withdrawals can significantly disrupt operations and hinder growth. Awareness of the cultural attributes that drive employees to voluntarily leave is essential for these firms. Proactive measures, such as conducting exit interviews, can shed light on the organizational culture characteristics influencing employees’ decisions to leave. Similarly, annual employee surveys can provide valuable insights into the factors motivating employees to stay. These tools enable small- and medium-sized firms to refine their organizational culture, mitigate voluntary turnover, and foster stronger employee retention.

6. Limitations and future research

This study has several limitations that should be considered when interpreting its findings. First, the sample was restricted to employees in entry-level, lower-managerial positions with a minimum of three years of tenure in their current workplaces. Respondents were selected using convenience and snowball sampling techniques, which present inherent challenges. Employees with more extensive experience in their organizations might evaluate organizational culture differently, potentially influencing the results. Additionally, the use of non-probability sampling methods, such as convenience and snowball sampling, introduces risks of sampling bias and a higher margin of error (Berndt, 2020). To enhance generalizability, future studies could employ probability sampling techniques, such as random or stratified random sampling.

Second, job search behavior is a dynamic process that can span an individual’s entire career and vary across different life stages. This study focused on respondents’ job search effort within a three-month period. While this timeframe was chosen to balance the need for timely insights with broader applicability, shorter durations (e.g., one month) or longer periods (e.g., six months) could provide alternative perspectives. Future research could explore how varying timeframes affect findings, particularly when examining withdrawal intentions from an organizational standpoint (Blau, 1993).

Finally, this study identified firm size as a contextual factor influencing job search effort and moderating the relationship between organizational culture and job search effort. While this focus provides valuable insights, future research could examine additional contextual factors, such as industry type, organizational ownership structure, or geographic location, to further enrich our understanding of how organizational culture interacts with employee behavior. Expanding the scope of contextual variables could provide a more nuanced view of these relationships and their applicability across different organizational settings.

References