The Influence of Succession Planning, Knowledge Sharing and Innovation Capability to Enhance Sustainability of Small and Medium-Sized Family Businesses’ Socioemotional Wealth

The Influence of Succession Planning, Knowledge Sharing and Innovation Capability to Enhance Sustainability of Small and Medium-Sized Family Businesses’ Socioemotional Wealth

Lai-Kuan Kong¹, Soon-Yew Ju², Nurul Nadia Abd Aziz¹*, Nor Khairunnisa Mat Yunus¹, Zaidatul Nadiah Abu Yazid¹

¹Faculty of Business and Management, Universiti Teknologi MARA Pahang Branch (Raub Campus), Raub, Pahang, Malaysia.

²Faculty of Administrative Science and Policy Studies, Universiti Teknologi MARA Pahang Branch (Raub Campus), Raub, Pahang, Malaysia

*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2024.8090205

Received: 11 September 2024; Accepted: 17 September 2024; Published: 15 October 2024

ABSTRACT

Family businesses are known for prioritizing non-financial goals, such as socioemotional wealth (SEW). However, many small and medium-sized family businesses (SMFBs) face challenges like insufficient succession planning and reluctance to engage in innovation and knowledge sharing. While research on SEW is extensive, limited studies explore the relationship between succession planning and SEW, as well as the role of innovation capability in mediating the link between knowledge sharing and SEW in SMFBs. This study addresses these gaps by surveying 118 Malaysian SMFBs through non-probability sampling. In order to guarantee the data’s representativeness of SMFBs, the questionnaire was pre-tested by specialists who included numerous screening questions and inclusion criteria for sample selection. The IBM SPSS Statistics and Smart-PLS software were employed to analyze the data. The results indicated that SEW attainment was influenced by knowledge sharing, whereas SEW was not influenced by succession planning. It was also discovered that the relationship between knowledge sharing and SEW attainment was mediated by innovation capability. These findings challenge traditional views on succession planning and highlight the importance of innovation and knowledge sharing for the sustainability of family businesses. Individuals who are involved in family enterprises can make more informed decisions and take actions that contribute to the long-term success, sustainability, and well-being of their organizations by comprehending and implementing these findings.

Keywords: Innovation Capability; Knowledge Sharing; Malaysia Small and Medium-Sized Family Businesses; Socioemotional Wealth; Succession Planning

INTRODUCTION

Family businesses have a far-reaching impact on economies throughout the world. Although there is no single definition of a family business, there is a general agreement that one of its distinctive characteristics is the presence of family influence and involvement in the company, which has an impact on its internal operations (Astrachan et al., 2002; Klein & Kellermanns, 2008; Yu et al., 2012). Unlike non-family businesses that are profit-oriented, family businesses tend to prioritize non-financial goals due to family considerations. One of the common non-financial goals of family businesses is socioemotional wealth (SEW). In this regard, family members’ involvement and influence in the family business process is unavoidable to obtain or/and sustain SEW. However, many family businesses are also found to be less interested and prepared to do succession planning. Fortunately, recent studies indicated that younger generations are more ready for succession planning than their predecessors (PwC’s Family Business Survey, 2021; PwC NextGen Survey, 2022). As such, the influence of family business involvement and succession planning toward SEW attainment and sustainability is worth studying due to the scarcity of research, especially in the SMFBs context. Additionally, it would be interesting to examine how family members’ involvement in knowledge sharing and succession planning influences SEW in the family business along with the mediating effect of innovation capability toward the relationship between knowledge sharing and the SEW of small and medium-sized family businesses (SMFBs).

LITERATURE REVIEW

Socioemotional Wealth (SEW)

According to Gomez-Mejia et al. (2007), SEW refers to the non-financial elements of family-run businesses that satisfy the family’s emotional needs, including identity, the ability to exercise family influence, and the continuation of the family dynasty (p. 106). According to Gomez-Mejia et al. (2011), it frequently refers to the emotive endowments that family business owners build with the company, whether consciously or unconsciously, and how those endowments affect their decision-making. According to prior research, family firms frequently prioritize retaining SEW over financial profitability (Firfiray et al., 2018). Family firms are distinguished from non-family enterprises by their unique conduct (Berrone et al., 2012). Nonetheless, a number of scholars have approached the notion of SEW from a variety of non-economic angles, including family harmony, social standing, identity, emotional values, family sustainability, family responsibilities, and reputation (Debicki, 2012; Astrachan & Jaskiewicz, 2008). It has been discovered that these non-financial factors drive family enterprises, especially when family owners are eager to maintain their socioemotional wealth (Berrone, Cruz, & Gomez-Mejia, 2014; Gomez-Mejia et al., 2011; Gomez-Mejia et al., 2007).

The multidimensional SEW constructs have indicated its importance to family businesses. Thus, it is essential to utilize unique resources and capabilities that are devoted by family members to attain and sustain SEW. As such, this study assumes that the importance and attainment of SEW can be achieved through knowledge sharing and succession planning practice, while innovation capability can enhance the relationship between knowledge sharing and SEW.

Knowledge Sharing

Organizational knowledge is a priceless intangible resource critical to a firm’s competitive advantage, which ultimately drives its value (Grant, 1991, 1996). Competitors often face significant difficulties in replicating or imitating a firm’s expertise, thus positioning knowledge as an essential source of sustained competitive advantage and superior performance (Barney et al., 2001; Villalonga, 2004; Wiklund & Shepherd, 2003). In family businesses, knowledge sharing takes on an even more pivotal role, as these firms are typically characterized by strong familial ties and long-standing traditions. This unique environment fosters the development and application of specialized knowledge, which, when shared effectively, can enhance both innovation and performance over time (Cabrera-Suárez et al., 2001; Grant, 1996).

In the context of small and medium-sized family businesses, knowledge sharing becomes instrumental in safeguarding socioemotional wealth. The familial nature of these businesses facilitates the transfer of tacit knowledge—deeply embedded in the family’s history and relationships—that competitors struggle to replicate (Arregle et al., 2007; Carney, 2005). This enables family firms to create intangible resources that provide a long-term competitive edge (Habbershon & Williams, 1999; Habbershon et al., 2003). By sharing this knowledge among members, these businesses not only preserve but also enhance their socioemotional wealth, ensuring continuity and long-term success.

Furthermore, a key factor in promoting innovative capability is knowledge sharing. According to Kuruppuge et al. (2018), staff members in family businesses are more likely to share their knowledge when they have a strong sense of identity with the company. This increases the ability of the business to innovate. Maintaining high levels of innovation requires the capacity to gather, synthesize, and apply this knowledge—a skill that makes it challenging for rivals to copy (Lin, 2007). Accordingly, within the framework of this research, Knowledge sharing serves as both a catalyst for innovation and a cornerstone for maintaining the socioemotional riches of family businesses, ultimately bolstering their viability and prosperity.

Succession Planning

Previous research indicated that family businesses either lack succession planning or have not devoted time to create a formal plan (Allegretti, 2019; John, 2020). Fortunately, a recent survey showed that 30% of the current generation admitted to having a robust plan (PwC’s Global Family Business Survey, 2022). Furthermore, 61% of NextGens stated that their families have a succession plan; nevertheless, 39% of them reported a certain resistance in their companies to embrace leadership change (PwC NextGen Survey, 2022). Such phenomenon suggests that succession planning is still a ‘hanging’ issue in many family businesses. Family business owners need to realize that succession planning is the key to family business sustainability as it can help to align their short- and long-term goals, including SEW. Nonetheless, research on the influence of succession planning toward SEW among SMFBs remains scarce. This study aims to fill the knowledge gap.

Innovation Capability

According to Hartono and Sheng (2016), innovation capability is a complex concept with differing viewpoints on its application in innovation management. Chua (2012), for example, described a company’s inventive capacity as its capability to innovate across a variety of markets, products, processes, behaviors, and strategies. Lawson and Samson (2001) defined it as the ongoing capacity to convert concepts and information into new systems, procedures, and products that are advantageous to the business and its stakeholders. Numerous studies have shown that indicators like return on investment (ROI), return on assets (ROA), return on sales (ROS), and total profitability show a direct correlation between innovation and improved business performance (Calantone et al., 2002). Aside from increasing sales (Bagchi-Sen, 2001; Lin & Chen, 2007), financial performance, and market success (Salim & Sulaiman, 2011), it also improves internal process, open systems, reasonable goals, and human interactions (Van Auken et al., 2008).

In the context of small and medium-sized family businesses, innovation capability holds particular significance, as it not only improves overall business performance but also serves as a strategic mechanism to sustain socioemotional wealth (SEW). Given that these businesses are often motivated by non-economic goals—such as preserving family legacy and relationships—they tend to adopt diverse forms of risk-taking when pursuing innovation (Berrone, Cruz, & Gomez-Mejia, 2012; Chrisman & Patel, 2012). While the goal of innovation in non-family businesses may be purely economic, family firms often balance innovation with the need to protect their SEW, leading to a more cautious yet strategic approach (Chrisman et al., 2015; De Massis et al., 2013). This nuanced approach to innovation reflects a deeper connection between innovation capability and SEW preservation, where family firms seek to achieve long-term success without compromising their familial values.

In this study, innovation capability is considered a critical factor for enhancing the sustainability of small and medium-sized family businesses. It enables these businesses to adapt to changing market conditions, ensuring that they remain competitive while safeguarding their socioemotional wealth. By continuously turning ideas and knowledge into actionable innovation, family businesses can achieve not only financial success but also fulfill their non-economic aspirations, thereby maintaining their unique position in the market over the long term.

The role of innovation as a mediator in the relationship between innovation capability and knowledge sharing.

Previous research has presented data supporting the relationship between innovation capability and organizational performance, knowledge sharing and SEW, and knowledge sharing and innovation capability (Asbari et al., 2019; Ganguly et al., 2019; Saunila, 2020; Yang et al., 2018). Nonetheless, limited study has examined how innovation capability functions as a mediator in the relationship between SEW and information sharing, especially when it comes to SMFBs. Thus, the purpose of this study is to ascertain how innovative capability mediates the association between SEW and knowledge sharing. The conceptual framework for this investigation is displayed in Figure 1.

Figure 1: Conceptual Framework for Enhancing Socioemotional Wealth in Family Businesses (Source: Developed by the author)

Research Objectives

The research objectives of this study are as follows:

1. To examine the impact of knowledge sharing on the SEW of SMFBs.
2. To examine the impact of succession planning on the SEW of SMFBs.
3. To investigate the mediating effect of innovation capability on the relationship between knowledge sharing and the SEW of SMFBs.

Research Hypotheses

This study shall address the intended research objectives by testing the following hypotheses:

H1: Knowledge sharing has a positive impact on SEW of SMFBs

H2: Succession planning has a positive impact on SEW of SMFBs.

H3: Innovation capability mediates the relationship between knowledge sharing and the SEW of SMFBs.

METHODOLOGY

This cross-sectional study was carried out using a survey approach to gather pertinent data from small and medium-sized family businesses (SMFBs) in Malaysia. The information was centered on the owner-manager perceptions on how knowledge sharing, innovation capability, and succession planning affected these organizations’ potential to attain socioemotional wealth (SEW). Small and medium-sized enterprises (SMEs) in Malaysia were the study’s population. SMEs are categorized according to two factors: the number of full-time employees and annual revenue turnover.

SMEs account for approximately 98.5% of businesses in Malaysia, amounting to 907,065 companies as of 2019 (SME Corp Malaysia, 2021). Businesses in the manufacturing industry are classified as SMEs if they have a sales turnover of no more than RM50 million or employ no more than 200 full-time employees. Meanwhile, businesses in the services and other industries are considered SMEs if they have a sales turnover of no more than RM20 million or a full-time workforce of no more than 75 employees.

It is important to note that classification depends on both the industry and these thresholds. If a company exceeds the employee limit for one category but fits within the turnover criteria of another, the classification remains aligned with the specific industry of operation. For example, if a service industry business employs 200 full-time staff but has a sales turnover below RM20 million, it would still be classified under the service industry. This ensures that businesses are categorized based on the industry they operate in, rather than solely by numerical thresholds.

Given these factors and the lack of an easily accessible database for SMFBs in Malaysia, SMEs were chosen as the study’s sample frame. Small and medium-sized family enterprises were the unit of analysis; the analysis was done at the organizational level. This study specifically defined SMFBs as corporations, partnerships, sole proprietorships, or any other kind of business organization that fell within the SME category. Both Westhead and Cowling (1997) and Birdthistle and Fleming (2005, p. 732) state that when family members work for a company or are represented on the board of directors, owners or workers frequently view it as a family business. The survey was designed with multiple screening questions to ascertain whether family members were involved in the firm, in order to guarantee that the information was representative of small and medium-sized businesses.

This research was carried out in two stages. To ensure the content validity of the study instrument, a pre-test was conducted at the initial stage. Three professors with expertise in management and SME research took part in this phase where their feedback and suggestions were implemented into the survey instrument. It was followed by the second phase where the primary study was conducted using the updated survey instrument to gather the needed data.

Generally, no common understanding exists on what accounts for a “large” sample size (Marcoulides & Saunders, 2006). This is because the sample size required for a study is often dependent on various factors, including the power of the anticipated statistics, estimated effect sizes, alpha level, and the number of predictors of the research model (Kock & Hadaya, 2018; Tabachnick & Fidell, 2012). Smithson (2003) advocates on the importance of determining the sample size before a study is conducted. In this regard, G*Power has been propounded as a useful tool to determine the number of sample size needed for data collection purposes (Faul et al., 2007).

The sample size of this study was estimated using the priori power analysis (Faul et al., 2007; Faul et al., 2009) embedded in the G*Power software. The optimum sample size needed for this was 68 respondents, which was determined based on the input parameters of a medium effect size (f2) with α = 0.05 and a power of 0.80 for the research mediator model. However, the researchers decided to include more than 68 respondents in the data collection process to avoid the study being deemed underpowered in the post hoc analysis.

This study used SmartPLS to examine the hypotheses. It was assumed that useable data from more than 100 cases was generally sufficient and worked well for CFA at PLS-SEM (Reinartz et al., 2009; Russell, 2002) to achieve a statistical power of 0.80 and α = 0.05 with medium effect size. Nevertheless, this study collected data from 140 respondents, of which 118 sets were usable for further analysis. Prior to data analysis, 118 useable datasets produced a power of 0.9986 for four predictors, above the advised power of 0.80, according to the G*Power (Faul et al., 2007, 2009) post hoc power analysis. This demonstrated that there was sufficient power in the 118 useable data to reject the null hypothesis (Faul et al., 2007).

This study aimed to quantify the association between knowledge sharing and succession planning to the SEW of SMFBs as well as the role that innovation capabilities played as a mediating factor in the relationship between knowledge sharing and SEW. All of the model’s constructs were measured using multiple-item measures. According to Nunnally and Bernstein (1994), social science research can be considered credible if the reliability analysis score for each dimension is more than 0.70. Hence, well-validated measures were chosen.

The data of this study was collected through face-to-face questionnaire distribution. The questionnaire consisted of five sections (Parts A to E). Part A measured the Socioemotional Wealth Importance variable and consisted of nine items that were adapted from Debicki et al. (2016). It measured three aspects, namely family prominence (a = .824), family continuity (a = .863), and family enrichment (a = .830). The respondents were required to indicate the importance of these items in relation to their family business through a scale of “1 – Not Important” to “7 – Very Important”. Part B measured the Knowledge Sharing variable using four items that were adapted from Cunningham, Seaman, and Mcguire (2017). Similarly, the respondents were required to state the level of agreement with these items using a scale of “1 = Strongly Disagree” to “5 = Strongly Agree”. Part C measured the Succession Planning variable. It comprised two items (Cronbach alpha = .70) developed by Lansberg and Astrachan (1994), which asked whether “Succession has been explicitly planned in the family business” and “Explicit selection criteria have been developed for identifying the best successor”.

In the meantime, Part D used six items that were taken from Calantone et al. (2002) to measure the Innovation Capability variable. Using a 5-point Likert scale with 1 representing “strongly disagree” and 5 representing “strongly agree,” it examined the firms’ rate of innovation adoption. According to Lin (2007) and Calantone et al. (2002), all six items had Cronbach’s alpha values of 0.77 and 0.89. These items included (1) ‘Our company frequently tries out new ideas’, (2) ‘Our company seeks new ways of doing things’, (3) ‘Our company is creative in its operating methods’, (4) ‘Our company is frequently the first to market new products and services’, (5) ‘Innovation is perceived as not too risky in our company and is encouraged’, and (6) ‘Our new product introduction has increased during the last five years’. Finally, Part E elicited the respondents’ personal and business backgrounds that were used as the filter questions to identify their SMFBs characteristics.

A Malay and an English version of the questionnaire were developed. To guarantee that the meaning of each item is consistent, a professional translator back-translated the original English text into both Malay and English. Subsequently, three scholars who are actively engaged in research on Malaysian SMEs pre-tested the questionnaire in Malay. Any feedback and recommendations received from these experts were taken into consideration to further improve the questionnaire.

Data Analysis

Prior to inferential data analysis, issues of response bias and common method bias were tackled preceding the measurement model and structural model analysis as the existence of bias might produce doubts about the generalization of results (Yüksel, 2017). Additionally, the issues of missing value (Hutchenson & Pampaka, 2012; Marcoulides & Saunders, 2006), control variables (Green et al., 2016), as well as univariate normality and multivariate normality (Jackson et al., 2009) were also treated before embarking on data analysis. Once the data cleaning stage was completed, the study proceeded to analyze the data using two statistical software, namely Smart PLS (Ringle et al., 2015) and IBM SPSS Statistics. It began by examining the reliability and validity of the measurement model followed by an examination of the structural model to test the hypotheses.

Table 1: Background Information (n = 118)

*Screening questions to identify the SMFBs characteristics.

Several screening questions were incorporated to ensure that the data was representative of SMFBs (see Table 1). The questionnaire was distributed to a total of 140 prospective respondents; however, only 118 respondents (84.0%) perceived their businesses as a family business. From the figure, 94.9% of the respondents stated that the family was represented on the managerial level, 96.6% of them stated that between 1 to 10 family members were employed in the business, and 91.5% of them had between 1 to 10 full-time employees. The findings indicated that the data was representative of SMFBs. The results in Table 1 also revealed that female respondents (53.4%) were slightly higher than male respondents (46.6%). A majority of the business ownership belonged to multifamily (42.4%), followed by one owner (24.6%), married couple (18.6%), brother/sister (933%), and others (5.1%).

Measurement Model

Table 2: Measurement Model for Convergent Validity of the Reflective Indicators

Note 1: CR = composite reliability; AVE = average variance extracted.

Note 2: AVE = Σ(λ^2) / [Σ(λ^2) + Σ(δ)].

Note 3: CR = (sum of the factor loadings)² / [(sum of the factor loadings)² + (sum of the error variances)

Table 2 shows that all loadings of the indicators surpassed the recommended threshold of >0.70, as suggested by Hair et al. (2010). The loading values of the indicators varied from 0.544 to 0.963, indicating significant associations with their respective constructs and limited influence from other constructs (Henseler, 2017). Consequently, no indicators were excluded from the analysis.

The internal consistency of the measurements was assessed using composite reliability (CR). It reflects the extent to which a set of indicators demonstrates internal consistency with the construct (Hair et al., 2010). As shown in Table 2, the CR values for all constructs ranged from 0.842 to 0.937, surpassing the minimum recommended threshold of 0.7, as proposed by Nunnally and Bernstein (1994).

Furthermore, the study evaluated the average variance extracted (AVE) to assess the convergence of indicators from similar constructs, with the threshold values ideally exceeding 0.50 as suggested by Fornell and Larcker (1981). As reported in Table 2, the AVE values for the constructs ranged from .507 to .882, signifying an adequate degree of convergent validity.

In social research, the use of valid and reliable measures is of paramount importance (Cabrera-Nguyen, 2010). Consequently, researchers often rely on two primary criteria, namely reliability and validity, to assess the quality of their measurements (Henseler, 2017).

Table 3: Fornell-Larcker Criterion

Note: Diagonals (in bold) represent the squared root of AVE while the other entries represent the inter-correlation values between constructs.

Discriminant validity was assessed using two established criteria: the Fornell-Larcker criterion (1981) and the Heterotrait-Monotrait Ratio (Henseler et al., 2015). The application of the Fornell-Larcker criterion is shown in Table 3, where the square root of AVE for each construct exceeded the corresponding values of correlations with other constructs both horizontally and vertically. According to Fornell and Larcker (1981), the establishment of discriminant validity requires a construct to share more variance with its own indicators than with the indicators of other constructs.

The results presented in Table 3 confirmed that the diagonal elements of the square roots of AVE were higher than all the off-diagonal elements, both vertically and horizontally. This finding satisfied the Fornell-Larcker criterion and affirmed the validation of discriminant validity.

Table 4: Heterotrait-Monotrait Ratio (HTMT)

*Discriminant validity is established at HTMT 0.85.

The results in Table 4 revealed that the Heterotrait-Monotrait Ratio (HTMT) values ranged from .303 to .558, all falling below the recommended threshold of 0.85. This provides compelling evidence that the constructs under investigation exhibited distinct characteristics, substantiating the presence of discriminant validity (Henseler et al., 2017).

Based on the aforementioned criteria, both discriminant and convergent validity for the constructs are duly established. Construct validity, as articulated by Peter (1981, p. 134), pertains to the degree to which a measurement accurately assesses the intended construct. In this research, outcomes of the confirmatory factor analysis offer strong support for the distinct verification of the study variables, underscoring a satisfactory level of discriminant and convergent validity within the measurement model.

Structural Model

Table 5: Path Coefficient for the Main Model

Before delving into the structural model, it was imperative to address the potential threat of collinearity. As indicated in Table 5, the Variance Inflation Factor (VIF) values were found to be below the established threshold value of 3.0 (Hair et al., 2011), thus affirming the absence of collinearity concerns within this study.

For the calculation of the structural model (Table 5), beta values, standard errors (Se), t-values, VIF, and f2 were assessed through the bootstrapping technique with 5,000 resamples. The results demonstrated a significant relationship between knowledge sharing and socioemotional wealth (β = 0.240, t = 2.023: LL = 0.015, UL 0.473). Conversely, succession planning did not exhibit a significant relationship with socioemotional wealth (β = 0.004, t = 0.051, LL = -0.157, UL 0.182). Therefore, H1 was supported while H2 was rejected. Following Cohen’s (1988) recommendation, an f2 value of 0.02 signifies a small effect size, 0.15 indicates a medium effect size, and 0.35 represents a large effect size. Consequently, the findings of this study revealed that knowledge sharing was associated with a small effect size.

To detect the mechanism that caused an observed relationship between knowledge sharing and socioemotional wealth, the mediation variable (innovation capability) was introduced within the research framework. Preacher and Hayes (2008) proposed indirect effects hold when the results show the absence of zero between lower and upper levels of the confidence interval. Our results showed that the indirect effects of innovation capability toward the relationship between knowledge sharing and socioemotional wealth were positive and significant (β = 0.187, t = 2.930, p = 0.003). Since the results had no zero between the lower and upper levels, H3 was supported.

Figure 2. Measurement Model

Figure 3. Structural Model

Table 6: Hypotheses Testing Results

DISCUSSION

The research findings presented offer significant insights into the sustainability of small and medium-sized family businesses (SMFBs) concerning their socioemotional wealth (SEW). Through a series of statistical analyses, the study rigorously assessed the validity and reliability of its measurement model while examining the relationships among various constructs. A systematic approach was employed to explore the influence of succession planning, knowledge sharing, and innovation capability on the SEW of SMFBs.

The results indicate that knowledge sharing significantly contributes to the attainment of SEW in family businesses. However, succession planning does not appear to have a direct impact on SEW achievement. Importantly, innovation capability emerged as a mediator in the relationship between knowledge sharing and SEW attainment. This finding suggests that while knowledge sharing within family businesses is critical, it alone does not guarantee the full realization of SEW. Rather, innovation capability functions as a pivotal mechanism through which family businesses can enhance their SEW.

The role of innovation capability as a mediator can be understood in light of the fact that, although knowledge sharing is generally facilitated by the presence of altruism and stewardship orientations in family businesses (Corbetta & Salvato, 2004; Zahra et al., 2008), the knowledge often remains confined to the experiences and competencies of employees and family members. This limitation can restrict the business’s ability to fully realize SEW. Family businesses often adopt centralized control and knowledge management approaches (Basly, 2007; Zahra et al., 2007), making them less inclined to participate in broader knowledge networks (Ahmad & Daghfous, 2010) and fostering exclusive network structures that limit external involvement (Lin, 2013).

As a result, both employees and family members may encounter challenges in accessing critical external resources, including knowledge that is essential for fostering innovation (Miller et al., 2010). Key factors such as R&D intensity, the qualifications of personnel, and an openness to knowledge sharing are integral to enhancing innovation performance (Caloghirou et al., 2004). Additionally, external knowledge, particularly market knowledge, serves as a critical source of information for driving innovation (Ministry of Science, Technology, and Innovation Malaysia, 2011). Thus, the presence of innovation capability as a mediator becomes essential in overcoming these limitations and driving family businesses towards achieving SEW.

Innovation capability, by contrast, allows firms to be more responsive to customer needs through the frequent introduction of new ideas, creative operational methods, and early adoption of new products or services. It also supports the production of a wider variety of differentiated products (Zahra et al., 2000), contributing to the development of new capabilities. Therefore, it serves as an important mediator, strengthening the relationship between knowledge sharing and SEW, as supported by previous studies (Urgal et al., 2013; Wang & Wang, 2012). However, this study did not find that succession planning influences SEW attainment. SEW remains a priority for SMFBs, regardless of whether they have formal succession planning in place or intend to pass the business to the next generation.

In light of these findings, several avenues for future research are suggested concerning the sustainability of socioemotional wealth in SMFBs. Although this study did not identify a significant relationship between succession planning and SEW, further investigation is warranted. Future research could explore additional dimensions of succession planning, such as the extent of family involvement in decision-making or the effectiveness of different succession strategies in shaping SEW. Moreover, given the current findings on the role of family members in influencing knowledge sharing, innovation, and SEW, future studies might examine the influence of personal values on family business succession planning and innovation strategies, a topic that remains underexplored (Zapata-Cantu, Sanguino, & Barroso, 2023).

While the current study establishes a positive relationship between knowledge sharing and SEW, there remains considerable scope for further exploration of the underlying mechanisms. Future research could delve into the specific knowledge-sharing processes, such as the role of informal networks, mentoring programs, or technology-enabled platforms, and how these mechanisms contribute to the creation and preservation of SEW in SMFBs. Additionally, this study identified innovation capability as a mediator between knowledge sharing and SEW. Further research may focus on examining the distinct dimensions of innovation capability that influence SEW in SMFBs. Investigating how family businesses cultivate a culture of innovation, the impact of family dynamics on fostering or hindering innovation capability, and the effects of different types of innovation on SEW could provide valuable insights.

Moreover, comparative studies between SMFBs and non-family businesses, or among different types of family businesses (e.g., single-owner versus multi-owner), could offer a deeper understanding of the unique characteristics and challenges faced by SMFBs. Such studies could identify the distinct factors that influence SEW and offer tailored strategies to meet the specific needs of SMFBs. Overall, exploring these research avenues has the potential to expand the current body of knowledge on the sustainability of socioemotional wealth in small and medium-sized family businesses. By examining these factors and mechanisms in greater detail, future research could offer a more nuanced understanding of how SEW is achieved and sustained, ultimately helping SMFBs to thrive over the long term.

CONCLUSION

Despite family businesses being a dominant form of enterprise and the increasing volume of research on this subject worldwide, there remains a significant gap in the literature specifically focused on small and medium-sized family businesses (SMFBs) in Malaysia. This study aims to address this gap and expand the existing knowledge base. The findings reveal that knowledge sharing has a positive impact on socioemotional wealth (SEW) in Malaysian SMFBs, with innovation capability emerging as a key mediator that strengthens this relationship. In contrast, no significant link was found between succession planning and SEW. Consequently, it is recommended that family business owners and managers focus on fostering and sustaining innovation capability to protect and enhance their SEW.

The results of this study provide valuable theoretical insights into SEW within the context of SMFBs. Specifically, the research emphasizes the crucial role of both knowledge sharing and innovation capability in shaping SEW. The study offers solid empirical evidence supporting the positive association between knowledge sharing and SEW, while highlighting the essential mediating role played by innovation capability in this relationship. These findings contribute to the SEW literature by identifying specific mechanisms through which SMFBs can enhance their SEW. Moreover, the discovery that succession planning does not significantly impact SEW challenges conventional assumptions in the literature, suggesting that the relationship between succession planning and SEW may be more nuanced than previously understood. This highlights the importance of further investigation into the contextual factors and complexities influencing the succession process in SMFBs, contributing to a more refined theoretical understanding of these dynamics.

Moreover, the research findings discussed in the previous sections have implications for practical applications in the context of small and medium-sized family businesses. The positive relationship between knowledge-sharing and SEW suggests that practitioners and family business owners should emphasize knowledge-sharing practices within their organizations. Implementing strategies, such as creating knowledge-sharing platforms, fostering a culture of learning and collaboration, and encouraging open communication, can facilitate the preservation and growth of SEW in SMFBs. Additionally, the mediating effect of innovation capability highlights its significance in enhancing SEW in SMFBs. Practitioners can focus on developing innovation-oriented mindsets, implementing systematic processes for idea generation and implementation, and investing in research and development to enhance their innovation capability. This can enable SMFBs to adapt to changing market dynamics, create competitive advantages, and sustain their SEW.

Policymakers can also benefit from these findings in developing targeted policies and supporting the mechanisms for SMFBs. They can design targeted support programs for SMFBs that recognize the importance of knowledge sharing and innovation capability. This can include providing resources, training, and mentoring programs that facilitate knowledge transfer, encourage innovation, and enhance the long-term sustainability of SMFBs. While the current study did not find a significant relationship between succession planning and SEW, policymakers can still emphasize the importance of effective succession planning in SMFBs. This can be achieved by offering guidance, training, and incentives to support successful leadership transitions and ensure the continuity of SEW in family businesses.

By considering these theoretical and practical implications, researchers, practitioners, and policymakers can contribute to the sustainable growth and prosperity of SMFBs. Further research and collaboration among these stakeholders can help to refine strategies, policies, and interventions that support the unique needs of SMFBs and foster their long-term socioemotional wealth.

In conclusion, the research findings presented in this excerpt offer important insights into the factors that influence the sustainability of socioemotional wealth (SEW) in small and medium-sized family businesses (SMFBs). The study highlights the critical roles of knowledge sharing and innovation capability in sustaining and enhancing SEW within these businesses. Although succession planning did not demonstrate a significant relationship with SEW in this study, the findings challenge traditional assumptions and underscore the complexities involved in succession processes in SMFBs. Overall, this research contributes valuable knowledge regarding the determinants of SEW sustainability in SMFBs, providing a basis for further investigation and supporting informed decision-making in both academic and practical spheres.

ACKNOWLEDGEMENT

The authors would like to express their sincere gratitude to the Universiti Teknologi MARA (UiTM) for supporting this research through the Geran Penyelidikan Dana Dalam Negeri – Dana Lestari Khas Phase 3 (Project Code: 600-TNCPI 5/3/DDN (06) (013/2021)). This funding has been instrumental in the successful completion of the study, and we appreciate the opportunity to contribute to the advancement of knowledge in our field.

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