Exploring How Organizational Capabilities Contribute to the Performance of Social Enterprises: Insights from China

Abstract

The impact of organizational capabilities on the performance of social enterprises (SEs) has not been examined in the context of China. This study addresses the research gap by conducting a hypothesis-testing quantitative study. The questionnaire survey data of 206 Chinese SEs were analyzed by performing Pearson correlation and hierarchical linear regression analyses. The research findings show that four types of organizational capabilities have divergent effects on the social and economic performance of Chinese SEs. Specifically, stakeholder engagement capabilities and business planning capabilities make positive contributions to SE performance in economic and social domains, while human resource management capabilities have positive effects on social performance but not economic performance, and there is no statistically positive relationship between marketing capabilities and SE performance in economic and social domains. Our study provides important practical implications to managers of SEs in China or in another similar context, who should give priority to enhancing stakeholder engagement capabilities and business planning capabilities rather than human resource management capabilities and marketing capabilities as a booster of economic and social performance of SEs.

1. Introduction

Over the past decade, China has witnessed a burgeoning of social enterprises (SEs) due to the joint effects of several driving forces in the state, market, and non-profit sectors [1]. Viewing SEs as potential providers of social cohesion, public service delivery, and sustainable development, local governments at the municipal/city levels have successively enacted specific policies to promote the development of SEs in China. In 2015, the first certification scheme for Chinese SEs was launched by the China Charity Fair to help SEs enhance their legitimacy/publicity and obtain support/resources from multiple stakeholders. In 2019, the first national survey report of the SE sector of China was published, which estimated that the total number of SEs in mainland China had reached 1.75 million when a broad definition of SEs was adopted, which included rural cooperatives registered as farmers’ specialized cooperatives (nongmin zhuanye hezuoshe) and non-profit entities registered as civilian-run non-enterprise units (minban fei qiye danwei) [2].

As typical hybrid organizations, SEs pursue dual objectives and aim to achieve their social missions, scale their social impacts and maintain financial self-sufficiency and sustainability. However, such a simultaneous pursuit of dual objectives involves a “tricky balancing act” [3], and success is far from guaranteed [4]. Therefore, practitioners and policy makers have devoted greater attention to SE performance, and there is a growing body of literature exploring how various factors affect SE performance at the individual, organizational and environmental levels.

Organizational capabilities have been widely recognized as one of the most important determinants of SE performance. To become sustainable and viable organizations, SEs need to acquire valuable resources and develop capabilities that will maximize the utility of their resources [5]. From a resource-based perspective, organizational capabilities refer to the ability of SEs to build, combine, and apply resources efficiently and effectively and the actions through which resources are employed to accomplish the organization’s goals [5,6]. Empirical studies have demonstrated that a wide range of organizational capabilities play important roles in ensuring social enterprise success. Among them, two types of organizational capabilities have received significant attention, namely, marketing capabilities [4,7,8,9] and stakeholder engagement capabilities [5,10,11,12,13,14]. Other forms of organizational capabilities have also been considered performance determinants in existing quantitative studies, including business planning capabilities [15,16,17,18], human resources management capabilities [10,11], performance measurement capabilities [19], abilities to adapt [20], and knowledge absorptive capacities [7,21].

Although previous research has generated a wealth of insights about the effects of various types of organizational capabilities as predictors of SE performance, there are three major research gaps to bridge. First, despite the proliferation of quantitative empirical studies on this research theme, the overwhelming majority of them use data from industrialized countries, such as the US, UK, Canada, Italy, France, Spain, Australia, and Japan [4,5,6,8,9,10,11,15,18,19,21], but rarely collect data from developing or emerging economies, such as South Korea, Jamaica, Malaysia, and Singapore [12,13,14,16,20,22]. Although China has witnessed a noticeable growth in the SE sector over the past decade, almost no attention has been devoted to the issue in the Chinese context, except for Lee and Chandra’s [7] study on how marketing capabilities mediate the effects of absorptive capacity on the performance of SEs from Hong Kong and Taiwan.

Second, as mentioned above, although previous literature has examined the effect of organizational capabilities on SE performance, most of them focus on a single organizational capability in one managerial and operational dimension or solely shed light on the effect on economic or social performance, while none of them have explored the relationship between organizational capabilities and SE performance through a comprehensive analytical framework embracing all major capability dimensions and performance domains.

Third, despite the diversity of ways to measure the social and economic performance of SEs, almost all of the relevant quantitative empirical studies use scale instruments to measure the “subjective” social and economic performance of SEs, which are frequently based on the perceptions of managers or other internal stakeholders, who are the questionnaire survey respondents. However, prior research has devoted little effort to measuring the “objective” performance of SEs, and only a few studies include objective indictors [15,18,22] or objective–subjective mixed measures [7]. Noticeably, the limited studies that have used objective indicators rely heavily on secondary databases [7,18,22], which are often incomplete, inaccurate, or outdated [21,23]. A subjective measurement may be applicable for the assessment of the social performance of SEs, which is widely considered a process involving “insights and perceptions” of multiple stakeholders [7,24,25,26]. Conversely, the popularity of subjective measures for economic performance is more similar to a temporary expedient, simply due to the difficulty of obtaining objective data [8,13]. Therefore, as numerous SE scholars have suggested [13,27,28], future research on SE performance should incorporate more objective indicators to reveal more of the “actual reality” of organizational performance, not merely the “perceived situation” as a result of the subjective perceptions of respondents.

By acknowledging these research gaps, this article explores how organizational capabilities at four managerial and operational dimensions affect the economic and social performance of SEs in China by analyzing quantitative data obtained from an online questionnaire survey of 206 Chinese SEs. The results demonstrate that four types of organizational capabilities have divergent effects on SEs’ social and economic performance. Specifically, consistent with prior studies, both stakeholder engagement capabilities, and business planning capabilities contribute positively and significantly to both the economic and social performance of Chinese SEs. Conversely, marketing capabilities have no positive relationship with either economic or social performance, contrasting with current literature. Additionally, human resource management capabilities are positively associated with social performance but not economic performance.

This study addresses the research gaps in current literature regarding the analytical framework and measurement of SE performance and makes several theoretical contributions. First, the contribution of this paper lies in constructing a more comprehensive analytical framework to investigate the effect of organizational capabilities at four major managerial dimensions on SE performance in both economic and social domains. Second, this study, to our knowledge, is the first quantitative empirical study on the contribution of organizational capabilities to SE performance in the Chinese context, which differs from those in Western developed countries and even other Asian developing countries. Finally, this study contributes to the refinement of the measurement of SE performance by employing a more comprehensive and rigorous measurement approach involving both subjective and objective indicators.

In the next section, we first delineate the conceptual background of SE performance and reveal the landscape of organizational capabilities of SEs in the Chinese and Eastern Asian contexts. Then, in the hypothesis development section, we construct our theoretical model to closely examine the effect of organizational capabilities on SE performance. Next, in the methodology section, we provide information on the data, sample, and measures of key variables. Subsequently, in the results section, we test the hypothesis with survey data and present the results obtained. Finally, we summarize the main results, discuss the theoretical contributions and practical implications, acknowledge the study’s limitations and offer suggestions for future research.

2. Literature Review

2.1. Conceptualization of SE Performance

Although the terminologies and conceptualization approaches of SE performance remain diversified and controversial, it is widely accepted that there are three major concerns when developing a comprehensive conceptual framework on SE performance, namely, performance dimensions, analytical foci, and assessment criteria.

First, SE performance is increasingly recognized as a multi-dimensional construct to be captured in both economic and social domains. The conceptualizations of economic performance often focus on the notions of “economic viability” [29,30], “economic productivity” [31], “economic-financial efficiency” [23], or “economic value” [4]. Similarly, defining social performance includes diversified approaches. Most prior works take a broad definition of social performance to embrace organizational performance in social (or community) and environmental domains and involve a wide range of terminologies, such as “social performance” [4,14,30,31], “social impact” [32,33,34,35,36,37], “social value creation” [25,38,39] or “social effectiveness” [27,40].

Second, the assessment of SE performance needs to consider the issue of analytical foci to comprehensively measure the direct or indirect effects or short-term or long-term impacts of SE activities on various stakeholders, as an individual or on community or society, at higher levels. The “logic chain model” provides a relevant tool to choose the analytical foci of SE performance. According to Ebrahim and Rangan [41], measuring social performance refers to “a logic chain of results in which organizational inputs and activities lead to a series of outputs, outcomes, and ultimately to a set of societal impacts”. Academic works on the conceptualization and measurement of SE performance reveal divergence regarding the selection of analytical foci, concentrating on different stages in the logic chain of social performance. However, the majority of scholarly works employ metrics focusing on activities and/or output stages.

Third, the conceptualization of SE performance is often connected to three assessment criteria: effectiveness, efficiency, and scaling-up. In the literature on SE performance, the assessment of effectiveness occurs in both social and economic domains. Social effectiveness is widely related to the notion of “accomplishment of social mission” [18,25,27,40,42]; the satisfaction of the interests/needs of stakeholders [25,30,40,43,44,45,46]; and serving the interests/needs of vulnerable/disadvantaged people or social groups [12,22,27,29,46]. In the economic domain, scholars use the term “economic effectiveness” [18], “commercial effectiveness” [27], or “management effectiveness” [43] to refer to the degree of success in achieving the economic, commercial, financial, or managerial goals of SEs.

The second criterion to measure SE performance is efficiency, which is defined as obtaining the best results for a given amount of resources [42] or fulfilling the organization’s mission at the lowest cost [23]. Previous studies commonly recognize the importance of calculating economic/financial efficiency to verify entrepreneurship as a basic component of assessing the overall effectiveness of SEs, although scholars have emphasized different aspects when conceptualizing the notion, such as cost efficiency (profitability) [40], the efficiency of operation [47] or human resources efficiency (productivity) [31,40,48]. Therefore, economic/financial efficiency mainly concerns how economic resources are employed to achieve economic/financial results (e.g., revenues, profits). In contrast, social efficiency measures with which resources have social results/impacts been achieved [49]. Existing empirical studies use various indicators to measure social efficiency, including the number of beneficiaries served for a given level of labor and capital inputs [50], the ratio of users to employees [51], and the ratio of the number of employees with disabilities to three inputs (fixed tangible assets, contingent and operating costs) [52].

Scaling-up is the third criterion used to assess the improvement of SE performance over time. The growth of SEs has its commercial and social logic, i.e., improving economic performance on the one hand and scaling social impact on the other [53]. The improvement of economic performance is connected closely to the concept of “organizational growth” [4], which is defined as “achieving the necessary financial return to sustain and/or expand the venture” [54]. However, it is widely acknowledged that the scaling-up of SEs is primarily about magnifying organizations’ social impacts and contributing to social change rather than gaining competitive economic advantages [55] or achieving organizational growth [56,57]. According to Dees [33], scaling social impact is the process of increasing the impact a social-purpose organization produces to better match the magnitude of the social need or problem it seeks to address.

To achieve a comprehensive understanding of SE performance, we integrated the complementary contributions from previous studies and constructed a conceptual framework that considered performance dimensions, analytical foci, and assessment criteria. We defined SE performance as a multi-dimensional concept composed of mainly economic and social dimensions. Specifically, economic performance refers to the degree to which an SE creates economic value for its customers/investors and achieves its economic/financial goals effectively, efficiently, and in an improved way. Social performance refers to the degree to which an SE creates social value for its stakeholders and accomplishes its social missions effectively, efficiently, and at a growing rate. Furthermore, we operationalized the concept of social and economic performance with a multi-foci analytical lens, using both subjective and objective indicators, which measured the direct and indirect results of SE activities.

2.2. Organizational Capabilities of SEs in the Chinese and Asian Context

Social enterprises often face significant resource constraints, as their primary social missions usually drive them to forsake healthier margins to reach more beneficiaries. Additionally, they often operate in environments that make it difficult to acquire resources at reasonable costs [5]. Hence, cultivating and improving organizational capabilities through which SEs can create, develop and utilize limited resources more efficiently and effectively becomes a critical issue.

Unlike their counterparts operating in more favorable socioeconomic contexts, SEs in mainland China struggle to survive in an unfledged ecosystem that provides insufficient financial, intellectual, technical, and human resources [1]. Moreover, compared to their Western peers, Chinese SEs encounter more challenges and uncertainties in political and cultural senses, where the government consistently plays a dominant role, and SEs face difficulties in gaining legal recognition and public trust [58,59]. Bhatt et al.’s [60] study pointed out that “non-munificent institutional environments” post four types of institutional challenges to the development of SEs in China, namely, norms of a strong role for government, a misunderstood or unknown role for SEs, non-supportive rules and regulations, and a lack of sociocultural values and beliefs in support of social goals. Such a less favorable environment persisted in China until recent years when several local governments at the municipal/city levels (such as Beijing, Chengdu, Shunde District—Foshan— and Futian District—Shenzhen) enacted specific policies successively to promote the development of SEs. Although Chinese scholars have captured such a new dynamic as the emergence of a “policy-driven mode” of SE development [61], the number of SEs gaining government recognition and support remains very limited (46 SEs in Beijing and 39 SEs in Chendu by 2019).

Operating in a less favorable environment, the majority of SEs in mainland China are small nascent ventures that face constant difficulties in maintaining financial sustainability. It was reported in 2012 that 54% of SEs in China started within the last 3 years, and a large proportion of SEs were not able to mature from initial start-ups into established organizations. Moreover, 71% of SEs were small-sized operations, generating less than 500,000 RMB in annual revenues, and even mature SEs remained relatively small [62]. Similarly, it was documented in 2016 that 65% of Chinese SEs were less than five years old, and 52% of SEs earned less than 80,000 EUR (nearly 600,000 RMB) per year [63]. Additionally, it was reported that in 2017, 53.4% of Chinese SEs were small ventures with fewer than 10 employees, and 43.2% of Chinese SEs were in “loss-making” financial situations [2].

Lacking organizational capabilities has been recognized as one of the key determinants of the underdeveloped situation of SEs in mainland China. Given that there is no specific legislation for SEs, many SEs are transformed from NGOs [58], lack business expertise, are unable to plan a long-term strategy for having a social impact, and fail to demonstrate a sound business model that can help them attract legitimate investment [62]. Additionally, a low level of capabilities for human resource management is one of the key challenges faced by SEs in China. It has been reported that 58% of Chinese SEs cite access and retention of human resources as a severe or significant challenge [62].

In response, both SE practitioners and scholars consistently emphasize the importance of strengthening the organizational capabilities of SEs to compensate for resource constraints. Over the past decade, numerous “SE intermediary organizations” [64], including incubators/accelerators (e.g., British Council China, Non-Profit Incubator), impact investors (e.g., Narada Foundation, Yifang Foundation, Leping Social Entrepreneur Foundation), platform organizations (e.g., China Social Enterprises and Impact Investment Forum) and certification organizations (e.g., Star of Social Innovation), have launched various capacity building initiatives or managerial skills training programs to enhance the organizational capabilities of Chinese SEs. For instance, from 2009 to 2016, British Council China started the Social Enterprise Program to provide social entrepreneurs with skills training, mentoring, access to UK expertise, and social investment opportunities. During its seven years of operation, the program provided skills training to over 3200 social entrepreneurs and facilitated RMB 37 million in social investment opportunities to 117 SEs [65]. Additionally, Non-Profit Incubator, another prominent intermediary organization that has incubated over 1000 social organizations (including SEs) in China, initiated the Roc Social Enterprise Accelerating Program in 2015, which provided management training and investment opportunities to 27 SEs, and launched the HSBC Social Enterprise Supporting Program in 2018, which provided capacity building and incubating services to 20 SEs in 2019 [66].

The importance of enhancing organizational capabilities is also salient for SEs in other Chinese regions, such as Hong Kong, Macau, and Taiwan. As summarized by Lee and Chandra [7], SEs in the Chinese region often face many challenges in sustaining their operations because of deficiency in organizational capabilities, such as a lack of management skills or marketing capabilities, failing to find skilled workers, and having low public awareness. SEs in other Asian countries also encountered a similar challenge in cultivating organizational capabilities to achieve sustainable development. In Southeast Asian countries such as Malaysia, Singapore, and Thailand, SEs are usually tiny or small in size and are unable to self-sustain economically [16,67,68]. Therefore, various training initiatives are launched to strengthen SEs’ managerial capabilities. For instance, in Malaysia and Singapore, training support for SEs is provided by both local government agencies and non-profit organizations, such as the British Council [17]. In Eastern Asian countries, such as South Korea, many SEs lack managerial capacities and are financially dependent and understaffed. In response, after the adoption of the Second Social Enterprise Promotion Plan in 2012, the South Korean government diversified policy instruments beyond conventional subsidies to improve SEs’ managerial capacity and enhance the self-sufficiency of social enterprises [22].

Previous empirical studies have proven that organizational capabilities play important roles in creating long-term competence for SEs and scaling their social impact in both Chinese and Asian contexts. Among literature on the performance of Chinese SEs, Chandra [69] found that the practice of “bricolage” helps SEs in Hong Kong develop new opportunities amid resource constraints. Similarly, Leung et al. [70] concluded that in Hong Kong, SEs with commercial skills (regarding business management and financial planning) are more likely to survive and sustain their operations. More recently, Lee and Chandra [7] demonstrated in Hong Kong and Taiwan that the marketing capabilities of SEs have a mediation effect on the relationship between absorptive capacity and financial performance.

Meanwhile, the literature on SEs in other Asian counties has identified organizational capabilities as important predictors of SE performance. For instance, several studies on SEs in South Korea have revealed that SEs’ social and economic performance are improved as a result of better organizational capabilities in various forms, such as “managerial capacity” [22], capacities regarding stakeholder engagement in terms of “community networking” [12] or “social networks” [14]. Similarly, in a study on SEs in Malaysia and Singapore, Cheah et al. [16] concluded that business planning capabilities have positive effects on SEs’ social and financial performance and that the positive influence is more significant in a less favorable environment such as Malaysia. Similarly, Sinthupundaja and Chiadamrong [68] concluded that, in Thailand, a set of organizational capabilities (namely, mission-driven, stakeholder, cross-sector collaboration, and environmental management) provide core conditions for high social entrepreneurship, which consequently contribute to high social and economic value.

Although the effect of organizational capabilities on SE performance has been explored extensively in both Chinese (merely in Hong Kong and Taiwan) and Asian contexts, no empirical study has examined this issue in the context of mainland China. Our study aims to fill this research gap in the literature.

2.3. Hypotheses Development

2.3.1. Relationship between Marketing Capabilities and Performance

The existing quantitative studies have examined how specific organizational capabilities at different managerial and operational dimensions affect the performance of SEs. First, assuming that marketing capabilities are important determinants of SE performance, researchers have constructed divergent measures of marketing capabilities and have drawn inconsistent conclusions. By analyzing survey data collected from 534 SEs in the UK and Japan, the pioneering study by Liu et al. [8] revealed that certain types of marketing capabilities have significantly positive effects on SEs’ social and economic performance. However, marketing planning capability negatively affects the performance of British SEs, as marketing information management does for Japanese SEs. In addition, Bhattarai et al. [4], using empirical data collected from 164 SEs from the UK, found that “market disruptiveness capability” improves economic performance but not social performance.

More recently, researchers have developed a more complicated theoretical model to examine the mediation or interaction effect of marketing capabilities on the relationship between other predictors and SE performance. For instance, Bhattarai et al. [4] found that the interaction between market orientation and market disruptiveness capability has a positive effect on social performance but a negative influence on economic performance. Likewise, based upon a sample of 221 Spanish social-economic entities, Palacios-Marqués et al. [9] concluded that distinctive competencies in marketing play a mediating role between social entrepreneurship and organizational performance. Similarly, Lee and Chandra [7] examined the mediating role of marketing capabilities on the relationship between absorptive capacity and financial and social performance, using data from 109 SEs in Hong Kong and Taiwan. The authors argued that marketing capabilities mediate the relationship between absorptive capacity and financial performance but not the one between absorptive capacity and social performance.

To summarize, current studies have shown that marketing capabilities in various forms have diversified effects on SE performance in economic and social domains. Hence, we hypothesize the following:

Hypothesis 1a (H1a).

Marketing capabilities are positively related to the economic performance of SEs in China.

Hypothesis 1b (H1b).

Marketing capabilities are positively related to the social performance of SEs in China.

2.3.2. Relationship between Stakeholder Engagement Capabilities and Performance

Stakeholder engagement capabilities have also been widely identified as an important factor in ensuring SE performance through communication [10,11], network building [6,12,14], and partnerships [5,10,11,13] with multiple stakeholders. At the communication-performance nexus, Bloom and Smith [10], based upon a large-scale sample of more than 500 SEs in the US, demonstrated how communication with stakeholders (as one of seven SCALERs) positively relates to the scaling of social impact. Likewise, Cannatelli [11] provided an empirical test of situational contingencies of the SCALERS model with a sample of 179 Italian non-profit organizations and found a similar positive relationship between communication and performance.

At the network building-performance linkage, Jenner [6] conducted a mixed-methods study involving 93 SE leaders in Australia and Scotland and found that collaborative networks play an influential role in ensuring the sustainability of social ventures. Similarly, using a sample of 235 SEs in South Korea, Cho and Kim [12] noted that community networking has a stronger relationship with economic performance than social performance. Additionally, Shin and Park [14], through a survey of 100 South Korean social entrepreneurs, concluded how social networks positively correlate with economic and social performance.

In the partnership–performance relationship, research using the SCALERS model commonly revealed the effectiveness of alliance building and lobbying in helping SEs scale social impact [10,11]. Similarly, Bacq and Eddleston [5], using a sample of 171 SEs in the US, concluded that SEs rely on specific capabilities of stakeholder engagement and attracting government support to scale their social impact. Alternatively, Choi [13] conducted a survey of 73 SEs in South Korea and drew a different conclusion that all types of partnerships between SEs and their public, social and private partners can decrease the social performance of SEs when partners provide financial support to SEs.

Taken together, most of the prior research has shown that stakeholder engagement capabilities in the forms of communication, network building, and partnerships with multiple stakeholders have positive effects on SE performance. Consequently, we hypothesize the following:

Hypothesis 2a (H2a).

Stakeholder engagement capabilities are positively related to the economic performance of SEs in China.

Hypothesis 2b (H2b).

Stakeholder engagement capabilities are positively related to the social performance of SEs in China.

2.3.3. Relationship between Business Planning Capabilities and Performance

Prior research has also demonstrated that business planning capabilities have important contributions to SE performance. In their study of 129 WISEs from Spain, Sanchis-Palacio et al. [18] argued that the degree of professionalization of management positively affects WISEs’ social effectiveness but has a negative relationship with economic effectiveness. Additionally, Barraket et al. [15], based on a survey of 365 Australian SEs, revealed a significant correlation between business planning efforts and higher financial performance. More recently, Cheah et al. [16] conducted a survey of 181 Malaysian and Singaporean SEs and found that business planning has a positive relationship with social and financial performance. Their study also demonstrated a significant mediating effect of business planning between entrepreneurial orientation and SE performance. Using the same survey data, Cheah et al. [17] also discovered that business planning plays a dominant role in the relationship between external support and SE performance.

In summary, the majority of previous quantitative studies have identified business planning capabilities as a positive contributor to SE performance. Therefore, we hypothesize the following:

Hypothesis 3a (H3a).

Business planning capabilities are positively related to the economic performance of SEs in China.

Hypothesis 3b (H3b).

Business planning capabilities are positively related to the social performance of SEs in China.

2.3.4. Relationship between Human Resource Management Capabilities and Performance

The relationship between human resource management capabilities and SE performance has also attracted academic attention. Bloom and Smith [10] identified “staffing” as a type of organizational capability and defined it as “the effectiveness of the organization at filling its labor needs, including its managerial posts, with people who have the requisite skills for the needed positions”. Their study concluded that staffing is positively associated with the scaling of social impact among SEs in the US. Based on the work of Bloom and Smith [10], Cannatelli [11] tested the SCALERS model in the Italian context and found that staffing is positively related to the scaling of impact. Furthermore, the author examined how the two situational contingencies moderated or mediated the relationship between staffing and the scaling of impact and concluded that “the dispersion of beneficiaries” has a positive effect on the relationship, while “public support” negatively affects the relationship.

According to the above discussions, human resource management capabilities have been recognized as positive predictors for ensuring SE performance. Thus, we hypothesize the following:

Hypothesis 4a (H4a).

Human resource management capabilities are positively related to the economic performance of SEs in China.

Hypothesis 4b (H4b).

Human resource management capabilities are positively related to the social performance of SEs in China.

We summarize our proposed theoretical model in Figure 1.

3. Methodology

3.1. Sample and Data Collection

In China, no specific SE legislation exists, and SEs are defined divergently among academia and practitioners [1]. SEs utilize a variety of organizational forms, including non-profit organizations (registered as civilian-run non-enterprise units, associations, or foundations), for-profit companies, microfinance organizations, and farmers’ specialized cooperatives. Therefore, it is difficult to clearly delineate the conceptual boundaries and precisely estimate the total population of SEs in China. Accordingly, consistent with studies conducted in similar situations in other countries [16,71], we adopted a purposive sampling approach to obtain a relatively comprehensive SE sample that is theoretically or analytically relevant. First, we chose to adopt a broad definition, conceptualizing SEs as entities that utilize business approaches to solve social or environmental problems and provide products or services containing a blended commercial, social and environmental value. Next, we defined the typologies of Chinese SEs as entrepreneurial non-profits, social cooperatives, work integration social enterprises, social businesses, public-private partnerships, for-profit business corporations, and hybrids, which were also recognized as major typologies for SEs worldwide [72,73,74]. Then, we invited several leading SE-supporting organizations and research institutes to contribute name lists of SEs. After removing overlaps between the received lists, we arrived at a combined list of nearly 1000 SEs in total. Subsequently, SEs were purposively selected from the combined list to participate in the study if they met the following two criteria: first, self-identifying as a SE based on the definition of this study; second, representing at least one of the major typologies selected for this study. Finally, we obtained a sampling frame of 518 SEs.

The questionnaire focused mainly on various performance determinants (especially those regarding organizational capabilities), performance indicators, and organizational features of SEs. In order to enhance the content validity, the questionnaire was sent to experts in the field of social enterprise/entrepreneurship, and a pilot survey (a sample of 10 SEs) was administered. Based on the received comments, we revised the contents in the questionnaire that were considered ambiguous, inconsistent or too time-consuming, or financially sensitive.

An online survey was conducted over a period of four months, from June to October 2018. First, we contacted all 518 SEs in the sampling frame by telephone or email, providing information on the survey and inviting them to participate in the study. Then, the electronic copies of the questionnaires were distributed to 476 SEs that agreed to participate, identifying the targeted respondents as the founders, CEOs, or top managers of SEs who were supposed to have adequate knowledge of the operations of SEs. To maximize the response rate, the research team made several follow-up calls and facilitated the informants to complete the questionnaire. Therefore, we collected a total of 388 returned questionnaires, yielding a response rate of 74 percent. This response rate was acceptable and reasonable when compared to other SE surveys conducted in China from 2015 to 2017, which had response rates ranging from 57.5% [75] to 65.8% [76]. Next, we eliminated 125 incomplete or invalid responses that had missing or invalid data on key variables and 57 unusable responses obtaining no formal registration status, and these were too young (age less than 12 months) or too small (annual revenue less than 10,000 yuan, total assets less than 10,000 yuan, beneficiaries number less than 10, or had no salaried employee). Consequently, we obtained 206 usable responses to test the hypotheses.

To assess potential non-response bias, we employed the extrapolation method [77], comparing the responses of the early respondents with those of the late respondents that were somewhat similar to the theoretical non-respondents. As the responses of the survey were ordered sequentially by the date received, we selected the first quartile to represent the early respondents and the last quartile to represent the late or non-respondents. Then, we used t-tests to assess the differences in the mean scores of the four types of organizational capabilities, economic performance index, and social performance index between the early and late respondents. The findings show no significant differences (at the 0.05 level of significance) in the mean scores of all six variables between the early and late respondents, suggesting that there is no systematic non-response bias.

Given that the data on both dependent and independent variables were self-reported and collected from the same respondents in the same survey, they might be exposed to the risk of common method bias (CMB). We adopted several recommended strategies [78,79] to alleviate CMB, including placing the questions for the dependent and independent variables far apart in the questionnaire, guaranteeing the respondents’ anonymity and confidentiality, and implementing a web-based survey that may put less social pressure on the respondents. Next, we used Harman’s single factor test to assess the occurrence of CMB. The results show that no single factor accounted for more than 32% of the variance, indicating no serious problem with CMB.

3.2. Variables and Measures

3.2.1. Independent Variables: Organizational Capabilities

Existing studies have used a wide range of indicators to measure the organizational capabilities of SEs. The most often utilized indicators fall into four major domains of organizational operation. The first group of indicators is related to the marketing activities of SEs. In Liu et al. [8], the measurement of “marketing capability” covered eight market-based activities, namely, pricing, product development, channel management, marketing communication, selling, market information management, marketing planning, and marketing implementation. Instead, other scholars focus merely on specific domains of market-related activities. For instance, Bhattarai et al. [4] concentrated mainly on product development activities to develop indicators for “market disruptiveness capability”. The second category of indicators is connected to stakeholder engagement, including effective communication with key constituencies and stakeholders [10,11], network building [12,14], and partnerships with stakeholders [5,10,11]. The third type of indicator is linked to business planning, including the professionalization of the management [18], formal strategic planning, budget forecasting, regular income/expenditure reports, impact evaluation, and formal networking [16]. The final type of indicator is related to human resource management, including the competence of labor and managerial staff and the abundance of volunteers [10,11].

Most previous studies share a similarity in using a subjective measurement approach, employing multi-item indicators rated on 5-point or 7-point Likert scales [4,5,7,8,9,10,11,12,13]. However, a few studies prefer to use objective indicators to measure organizational capabilities, such as the proxy for business planning capabilities in Cheah et al. [16] and Sanchis-Palacio et al. [18], as well as indicators for network building in Shin and Park [14].

In line with the majority of quantitative studies on SE organizational capabilities, we took a subjective measurement approach and used a 5-point Likert scale, [1 = very week; 5 = very strong] to gather respondents’ perceptions of the development of marketing capabilities, stakeholder engagement capabilities, business planning capabilities and human resource management capabilities.

3.2.2. Dependent Variables: Social Performance and Economic Performance

Based on the conceptual framework for SE performance developed in the previous section and drawing on prior quantitative studies on the measurement of SE performance, we selected ten indicators according to three assessment criteria (namely, effectiveness, efficiency, and scaling-up) and aggregated them into social performance index (SPI) and economic performance index (EPI). As outlined in Table 1, SPI, as the composite index for overall social performance, consists of six indicators for social effectiveness, one for social efficiency, and three for scaling social impact. As outlined in Table 2, EPI, as the composite index for overall economic performance, consists of five indicators for economic effectiveness, two for economic efficiency, and three for organizational growth.

Given that the ten indicators forming SPI and EPI were of different measurement units, we used the Min–Max method, one of the most widely applied normalization approaches in the practice of developing composite indices to normalize the data. Thus, all normalized indicators obtained an identical score range [1]. Then, the ten normalized indicators were assigned equal weights; therefore, the overall scores of SPI and EPI became the sum of the normalized scores of the ten individual indicators, ranging from 0 to 10, respectively.

3.2.3. Control Variables

It is widely recognized in prior quantitative literature on SE performance that several factors related to SEs’ organizational characteristics, such as age and legal status, may affect their performance. First, current studies show that younger SEs are more likely than older SEs to be successful in scaling social impact [10], maintaining sustainability [80], achieving better organizational performance [24] and social performance [13,81], or obtaining a higher level of organizational efficiency [23]. Second, legal status is considered a predictor of SE performance. Battilana et al. [31] revealed that economic productivity tends to be lower in non-profit WISEs. Bacq and Eddleston [5] found that being organized as a for-profit is negatively related to the scale of social impact.

In line with previous research, we included age and legal status as two control variables in the analysis of the effect of organizational capabilities on SE performance to reduce the possible confounding effects. First, we controlled for the age of SEs, measured by the number of years an SE was in operation until 2018. Second, we controlled for the legal status of SEs via three dummy variables: non-profit [no = 0, yes = 1]; for-profit [no = 0, yes = 1]; hybrid [no = 0, yes = 1].

Table 1. Indicators of social performance index (SPI).

Assessment Criteria	Indicators	Measurements
Effectiveness	accomplishment of social missions [4,20,24,27,30,82]	subjective rating of the degree of achieving the social goals on a 5-point Likert scale
	satisfaction of beneficiaries [14,24,30,82,83]	subjective rating of satisfaction of beneficiaries on a 5-point Likert scale
	satisfaction of employees [14,24,29,82]	subjective rating of satisfaction of employee on a 5-point Likert scale
	serving the vulnerable as beneficiaries [12,46]	the ratio of the vulnerable to beneficiaries
	serving the vulnerable as customers [12,46]	the ratio of the vulnerable to customers
	serving the vulnerable as employees [12,22,29]	the ratio of the vulnerable to employees
Efficiency	service efficiency [30,50,51]	the ratio of beneficiaries to employees
Scaling-up	increase in beneficiaries [8,71]	‘1’ if yes; ‘0’ if otherwise
	increase in product/service types [8]	‘1’ if yes; ‘0’ if otherwise
	improvement of product/service quality [71]	‘1’ if yes; ‘0’ if otherwise

Table 1. Indicators of social performance index (SPI).

Assessment Criteria	Indicators	Measurements
Effectiveness	accomplishment of social missions [4,20,24,27,30,82]	subjective rating of the degree of achieving the social goals on a 5-point Likert scale
	satisfaction of beneficiaries [14,24,30,82,83]	subjective rating of satisfaction of beneficiaries on a 5-point Likert scale
	satisfaction of employees [14,24,29,82]	subjective rating of satisfaction of employee on a 5-point Likert scale
	serving the vulnerable as beneficiaries [12,46]	the ratio of the vulnerable to beneficiaries
	serving the vulnerable as customers [12,46]	the ratio of the vulnerable to customers
	serving the vulnerable as employees [12,22,29]	the ratio of the vulnerable to employees
Efficiency	service efficiency [30,50,51]	the ratio of beneficiaries to employees
Scaling-up	increase in beneficiaries [8,71]	‘1’ if yes; ‘0’ if otherwise
	increase in product/service types [8]	‘1’ if yes; ‘0’ if otherwise
	improvement of product/service quality [71]	‘1’ if yes; ‘0’ if otherwise

Table 2. Indicators of economic performance index (EPI).

Assessment Criteria	Indicators	Measurements
Effectiveness	financial situation [30]	loss-making = 1; break-even = 2; surplus-making = 3
	debt ratio [84]	total liabilities over total assets
	surplus margin [4,8,9,21,27,84,85]	revenue minus expenditures and over revenue
	return on assets [48,51]	earnings before interest and tax over total assets
	satisfaction of customers [8,12,21]	subjective rating of satisfaction of customers on a 5-point Likert scale
Efficiency	productivity [21,31,48]	total revenue over the number of employees
	overhead ratio [23]	the ratio of expenditures to revenue
Scaling-up	increase in employees [71,86]	‘1′ if yes; ‘0′ if otherwise
	increase in customers [71]	‘1′ if yes; ‘0′ if otherwise
	increasing rate of revenue [12,14,71,86,87]	total revenue of 2017 over that of 2016

Table 2. Indicators of economic performance index (EPI).

Assessment Criteria	Indicators	Measurements
Effectiveness	financial situation [30]	loss-making = 1; break-even = 2; surplus-making = 3
	debt ratio [84]	total liabilities over total assets
	surplus margin [4,8,9,21,27,84,85]	revenue minus expenditures and over revenue
	return on assets [48,51]	earnings before interest and tax over total assets
	satisfaction of customers [8,12,21]	subjective rating of satisfaction of customers on a 5-point Likert scale
Efficiency	productivity [21,31,48]	total revenue over the number of employees
	overhead ratio [23]	the ratio of expenditures to revenue
Scaling-up	increase in employees [71,86]	‘1′ if yes; ‘0′ if otherwise
	increase in customers [71]	‘1′ if yes; ‘0′ if otherwise
	increasing rate of revenue [12,14,71,86,87]	total revenue of 2017 over that of 2016

3.3. Sample Characteristics

Our sample was composed of SEs from different fields of work: education (22.8%), community development (14.6%), employment (13.1%), environment and energy (9.7%), elderly (6.8%), poverty reduction (5.3%), and other (20.4%). The industries of economic activities were also diverse: education (22.8%), agriculture (18%), social care (12.6%), medical and health (5.8%), wholesale and retail (4.9%), creative industry (4.4%), environment and energy (4.4%), culture and art (3.4%), IT and Internet (2.4%), and other (21.3%). Regarding legal status, 61.7% of the SEs registered as for-profit companies, 32% as non-profits, and 6.3% as hybrids that have both for-profit and non-profit legal forms. In terms of organization size, the SEs in our sample had, on average, 67 employees (SD = 305). In terms of organization age, the mean number of years of operation was 6 years (SD = 4).

Table 3. Descriptive statistics and correlations for variables.

Variables	1	2	3	4	5	6	7	8	9	10
Age	1	.
Legal status: non-profit	0.031	1
Legal status: profit	−0.009	−0.871 **	1
Legal status: hybrid	−0.042	−0.178 **	−0.329 **	1
Marketing capabilities	−0.082	0.034	0.035	−0.135	1
Stakeholder engagement capabilities	0.031	0.130	−0.122	−0.004	0.371 **	1
Business planning capabilities	−0.091	−0.014	−0.012	0.050	0.366 **	0.414 **	1
Human resource management capabilities	0.052	0.005	0.038	−0.086	0.429 **	0.482 **	0.368 **	1
SPI	−0.067	0.009	−0.049	0.080	0.116	0.199 **	0.245 **	0.293 **	1
EPI	−0.086	−0.180 **	0.138 *	0.069	0.069	0.181 **	0.224 **	0.103	0.278 **	1
Mean	6.42	NA	NA	NA	3.20	3.55	3.50	3.31	5.00	3.08
SD	4.06	NA	NA	NA	1.00	1.01	0.97	0.94	1.43	1.34

Note: * p < 0.05; ** p < 0.01.

presents the descriptive statistics of other key variables.

Table 4. Descriptive statistics of the normalized indicators of SPI.

Assessment Criteria	Indicators	Mean	Median	SD	Min.	Max.	Mean by Categories
Effectiveness	accomplishment of social missions	0.820	1.000	0.205	0.000	1.000
	satisfaction of beneficiaries	0.798	0.667	0.225	0.000	1.000
	satisfaction of employees	0.684	0.667	0.253	0.000	1.000	0.488
	serving the vulnerable as beneficiaries	0.320	0.115	0.374	0.000	1.000
	serving the vulnerable as customers	0.183	0.000	0.318	0.000	1.000
	serving the vulnerable as employees	0.124	0.000	0.229	0.000	1.000
Efficiency	service efficiency	0.039	0.004	0.129	0.000	1.000	0.039
Scaling-up	increase in beneficiaries	0.733	1.000	0.443	0.000	1.000
	increase in product/service types	0.641	1.000	0.481	0.000	1.000	0.678
	improvement of product/service quality	0.660	1.000	0.475	0.000	1.000

presents the descriptive statistics of the ten indicators used to evaluate social performance. In terms of the three assessment criteria, the social performance of the Chinese SEs in the scaling-up aspect is higher than the other two aspects, with an average of 0.678 out of 1.000, whereas the indicator of efficiency category has the lowest score, with an average of 0.039 out of 1.000.

Table 5. Descriptive statistics of the normalized indicators of EPI.

Assessment Criteria	Indicators	Mean	Median	SD	Min.	Max.	Mean by Categories
Effectiveness	financial situation	0.430	0.500	0.400	0.000	1.000
	debt ratio	0.407	0.250	0.315	0.000	1.000
	surplus margin	0.051	0.000	0.123	0.000	1.000	0.345
	return on assets	0.078	0.000	0.205	0.000	1.000
	satisfaction of customers	0.761	0.667	0.218	0.000	1.000
Efficiency	productivity	0.098	0.062	0.138	0.000	1.000	0.075
	overhead ratio	0.051	0.000	0.123	0.000	1.000
Scaling-up	increase in employees	0.485	0.000	0.501	0.000	1.000
	increase in customers	0.607	1.000	0.490	0.000	1.000	0.401
	increasing rate of revenue	0.111	0.035	0.188	0.000	1.000

shows the descriptive statistics of the ten indicators used to evaluate economic performance. Similarly, indicators for economic performance in scaling-up aspect outperform those of the other two performance categories, with an average of 0.401 out of 1.000, whereas the indicator of efficiency category has the lowest score, with an average of 0.075 out of 1.000.

To summarize, the Chinese SEs in our sample are relatively successful in scaling up their social impact or pursuing organizational growth but operate with a very level of organizational efficiency in the social and economic performance domain in terms of service efficiency, productivity, and overhead ratio.

4. Results

To evaluate the proposed relationships between the four types of organizational capabilities and the economic and social performance of SEs in China, we conducted Pearson correlation analyses with a two-tailed test of significance and hierarchical linear regression analyses.

Table 3 indicates that the relationship between marketing capabilities and social performance, and economic performance is positive but not significant (r = 0.116 and 0.069, p = 0.097 and 0.324, respectively). Alternatively, stakeholder engagement capabilities are positively and significantly correlated with both social performance (r = 0.199, p = 0.004) and economic performance (r = 0.181, p = 0.009). Similarly, a significant positive correlation is found between business planning capabilities and social performance (r = 0.245, p = 0.000) and economic performance (r = 0.224, p = 0.001). Finally, human resource management capabilities are positively and significantly correlated with social performance (r = 0.293, p = 0.000); however, the relationship between human resource management capabilities and economic performance is positive but not significant (r = 0.103, p = 0.142). As several pairs of independent variables are moderately correlated (r ranges from 0.366 to 0.482), we assessed the possibility of multicollinearity by calculating the variance inflation factors (VIFs) for the major explanatory variables. The results show that all the VIF values are 1.496 or lower, which are far below the recommended threshold of 5.00, indicating that our model is free of multicollinearity threats.

Table 6. Results of hierarchical regression analyses for economic performance.

Variables	Step1	Step2	Step3	Step4	Step5
Age	−0.079	−0.072	−0.085	−0.073	−0.072
Legal status: non-profit	−0.171 *	−0.172 *	−0.199 **	−0.191 **	−0.192 **
Legal status: hybrid	0.124	0.135	0.134	−0.117	0.117
Marketing capabilities		0.075	−0.006	−0.047	−0.044
Stakeholder engagement capabilities			0.212 *	0.157 *	0.161
Business planning capabilities				0.166 *	0.168 *
Human resource management capabilities					−0.011
∆R2	0.040 *	0.005	0.038 **	0.021 *	0.019
Total R2	0.040 *	0.046	0.083 **	0.104 **	0.104 **

Note: * p < 0.05; ** p < 0.01.

presents the hierarchical linear regression results regarding the effect of organizational capabilities on the economic performance of SEs. The results reveal that two types of organizational capabilities, namely, stakeholder engagement capabilities and business planning capabilities, are positively and significantly related to economic performance (β = 0.212 and 0.166, respectively). Hence, hypotheses H2a and H3a are supported. Additionally, the positive contributions of business planning capabilities are relatively stronger and more stable than those of stakeholder engagement capabilities. Therefore, when human resource management capabilities are entered into the model, the effect of business planning capabilities is constantly positive and significant, while that of stakeholder engagement capabilities becomes insignificant. However, the evidence also shows that marketing capabilities have a positive but not significant relationship with economic performance (β = 0.075, p = 0.284), while human resource management capabilities have a negative but not significant relationship with economic performance (β = −0.011, p = 0.891), leading to the rejection of hypotheses H1a and H4a.

Table 7. Results of hierarchical regression analyses for social performance.

Variables	Step1	Step2	Step3	Step4	Step5
Age	−0.064	−0.053	−0.064	−0.051	−0.070
Legal status: profit	−0.027	−0.025	−0.001	−0.011	−0.027
Legal status: hybrid	0.068	0.086	0.085	0.066	0.076
Marketing capabilities		0.124	0.055	0.010	−0.055
Stakeholder engagement capabilities			0.180 *	0.120	0.034
Business planning capabilities				0.183 *	0.145
Human resource management capabilities					0.258 **
∆R2	0.011	0.015	0.027 *	0.026 *	0.045 **
Total R2	0.011	0.026	0.053 *	0.079 *	0.124 **

Note: * p < 0.05; ** p < 0.01.

displays the hierarchical linear regression results regarding the effect of organizational capabilities on the social performance of SEs. The evidence shows that three types of organizational capabilities, namely, stakeholder engagement capabilities, business planning capabilities, and human resource management capabilities, positively and significantly affect social performance (β ranges from 0.180 to 0.258), leading to the acceptance of hypotheses H2b, H3b and H4b. Moreover, a comparison of standardized beta coefficients suggests that human resource management capabilities play a more important role (β = 0.258, p = 0.002) than the other two organizational capabilities variables in enhancing social performance. Thus, when human resource management capabilities are entered into the model, the effects of stakeholder engagement capabilities and business planning capabilities become insignificant. Nevertheless, the results also indicate that marketing capabilities have a positive but not significant relationship with social performance (β = 0.124, p = 0.080). Thus, we reject hypothesis H1b.

5. Discussion

Our research findings show that four types of organizational capabilities result in divergent social and economic performance in the context of China. Some of the findings are consistent with the previous empirical literature. First, our research presents strong evidence that stakeholder engagement capabilities play an important role in ensuring SEs’ success in economic and social domains, corroborating the existing understanding of the issue regarding SEs from the US [5,10], Australia, and Scotland [6], Italy [11], and South Korea [12,14]. Second, our results also reveal that SEs with higher levels of business planning capabilities achieve better economic performance and social performance, in line with the findings of prior studies on SEs in Spain [18], Australia [15], Malaysia, and Singapore [16].

However, our research finds no statistically significant evidence of the positive relationship between marketing capabilities and economic performance and social performance of Chinese SEs, contrasting with most current literature that has identified marketing capabilities as a primary driver of improved performance in the UK [4,8], Japan [8], Spain [9], Hong Kong and Taiwan [7]. To explain the exclusion of marketing capabilities among the significant predictors of performance for Chinese SEs, we need to examine specific features of the socioeconomic context of China. Prior studies have documented that the success of marketing strategies for SEs depends on the rise of ethical consumerism as a social contingency and hinges on the consumer advocacy initiatives launched to raise consumers’ awareness of SEs’ social value [88,89]. However, Chinese SEs were found to be operating in an environment where most Chinese consumers have no strong commitment to ethical consumerism, and the mainstream media and the general public fail to recognize the existence and salience of SEs [2]. Therefore, the immature situation of ethical consumerism and public recognition of SEs might be a possible interpretation for the insignificance of marketing capabilities as performance predictors in China.

Finally, human resource management capabilities have positive contributions to the social performance of Chinese SEs, in accordance with previous studies that have demonstrated a significant positive relationship between staffing and scaling of social impact in the US [10] and Italy [11]. In contrast, we found no evidence to support the hypothesis that human resource management capabilities are predictors of the economic performance of Chinese SEs. To our knowledge, there is no empirical work focusing on this topic for SEs in other countries. However, previous studies have identified a variety of factors related to SEs’ human resources as predictors of their economic performance, such as resource availability [51,90], resource access/acquisition [6], resource adequacy [20], and resource competitiveness [28]. It is likely that human resource management capabilities might interplay with these factors, jointly affecting the economic performance of SEs, probably through the effect of mediation, moderation, or other more complicated forms of interaction. Specifically, the effect of human resource management capabilities might take resource availability as a precondition, on the one hand, and might affect resource access/acquisition, resource adequacy, and resource competitiveness, on the other hand. However, the relative importance of human resource management capabilities as one performance determinant, compared with other factors, might vary among different countries. In countries where SEs face the scarcity of appropriate human resources, resource availability might become a more important performance predictor; thus, the effect of human resource management capabilities becomes marginalized. For instance, López-Arceiz et al. [51] found that the economic performance of Spanish SEs depends directly and exclusively on the volume of financial, human, and material resources available. Similarly, Bojica et al. [84] stated that for Mexican SEs, the effect of bricolage on organizational growth is contingent on the availability of resources, the degree of autonomy in using these resources, and the diversity of the top management team in organizational tenure. In mainland China, the insufficiency and unavailability of human resources (as employees and volunteers) have been identified as the major challenges encountered by SEs [2]. Thus, the dominance of resource availability as a determinant of economic performance might be a reason for the marginalization and insignificance of the effect of human resource management capabilities in China.

6. Conclusions

SEs generally face resource constraints, especially when they operate in less favorable environments where resources are scarce and expensive; thus, it becomes increasingly important for SEs to strengthen their organizational capabilities to improve organizational performance [24]. Previous studies have provided rich evidence regarding the effects of organizational capabilities on SE performance. However, the majority of current works have examined the issue in the context of industrialized and Western countries, while very few have provided evidence in the Chinese context [7], and none have focused on SEs from mainland China. Therefore, this study explores the impact of organizational capabilities at four major managerial dimensions on economic and social performance through a quantitative analysis of the questionnaire survey data of SEs from mainland China. The research findings show that stakeholder engagement capabilities and business planning capabilities make positive contributions to SE performance in economic and social domains, while human resource management capabilities have positive effects on social performance but not economic performance, and there is no statistically positive relationship between marketing capabilities and SE performance in economic and social domains.

6.1. Theoretical Contributions

This study offers several contributions to the literature on SE performance. First, previous literature has demonstrated that various types of organizational capabilities might contribute to SE performance, such as marketing capabilities [4,7,8,9], stakeholder engagement capabilities [5,10,11,12,13,14], business planning capabilities [15,16,17,18], and human resources management capabilities [10,11]. However, none of them has approached the issue from a holistic perspective to explain how different types of organizational capabilities have varying effects on economic and social performance. The originality of this paper lies in its construction of a more comprehensive analytical framework to analyze the effect of organizational capabilities at four major managerial dimensions on SE performance in both economic and social domains.

Moreover, this study enriches the quantitative empirical studies on organizational capabilities as determents of SE performance by providing evidence on the issue in the context of China. To our knowledge, although the country has witnessed significant growth in the SE sector over the past decade, no survey-based empirical studies focus on this issue for SEs from China.

Furthermore, the majority of current quantitative empirical studies on SE performance rely mainly on “subjective” scales to measure performance and use few “objective” indicators, which may more precisely reflect the “actual reality” of SE performance. This study contributes to the refinement of the measurement of SE performance by employing a more rigorous measurement approach involving both subjective and objective indicators.

6.2. Practical Implications

Our study has several important practical implications for SE managers. First, our findings show that four types of organizational capabilities have divergent contributions to the social and economic performance of SEs in China. This implies that SE managers need to prioritize strengthening particular types of organizational capabilities, such as stakeholder engagement capabilities and business planning capabilities, which are found to have positive contributions to the improvement of SE performance in both economic and social domains. In contrast, SE managers should be cautious about choosing to use marketing capabilities as a promoter of performance, as our findings show that marketing capability has no positive impact on either economic or social performance in the current context of China. Additionally, the results reveal that human resource management capabilities are positively associated with social performance but not with economic performance, suggesting that SE managers should make appropriate decisions regarding the applicability of human resource management capabilities with regard to their organizational objectives.

The findings of this study also have implications for other practitioners and policy-makers engaging in promoting the development of social entrepreneurship and impact investment in China. As we mentioned above, numerous capacity-building programs have been launched by SE intermediary organizations and Chinese government agencies to strengthen the organizational capabilities of SEs operating in China. However, failing to appropriately adjust the strategic focus and specific content according to the particular context of China, these training programs can hardly actualize the roles of organizational capabilities as enhancers of SE performance. Therefore, we recommend that, in the future, capacity building programs should focus more on stakeholder engagement capabilities, business planning capabilities, and human resource management capabilities, which are found to be positive performance predictors, but less on marketing capabilities, which are found to have no positive contribution to performance. Additionally, we found in this study that the immature situation of ethical consumerism and public recognition of SEs might impose restrictions on the role of marketing capabilities as a performance enhancer in China. Thus, we suggest that practitioners and policy-makers make more efforts to increase the visibility and publicity of SEs and launch more advocacy initiatives to cultivate ethical consumerism among Chinese consumers to create preconditions for marketing capabilities to work as performance enhancers in the future.

6.3. Limitations and Future Research

We also recognize a set of theoretical and methodological limitations for this study that also reveal promising areas for future research. First, current studies show there are mediation or interaction effects between marketing capabilities and other SE performance predictors [4,7,9] or between business planning capabilities and other performance determinants [16,17]. However, our study merely focuses on the direct effects of organizational capabilities on SE performance while providing no information on how and why such effects occur. Instead, future studies can further investigate the processes and reasons by examining the possible mediation and/or moderation effects between organizational capabilities and other performance determinants. Moreover, exploring the relationships among the different types of organizational capabilities is another promising avenue for future research.

Second, this study gives priority to improving the measurement of SE performance by constructing both SPI and EPI as a composite indicator, which involves ten indicators selected by three assessment criteria (namely, effectiveness, efficiency, and scaling up), respectively. However, our preliminary effort in index development has certain limitations in terms of the potential bias in the selection of indicators and the imperfection of the weighting scheme. Therefore, future studies should follow the suggested procedure of index development more comprehensively and conduct uncertainty and sensitivity analyses to ensure the robustness of the performance index. Meanwhile, the measurement of the four types of organizational capabilities is relatively simple, involving only subjective indicators. In order to construct more valid and reliable measures for organizational capabilities, future studies should more strictly adhere to the paradigms for measures development, such as developing a more comprehensive conceptual framework, increasing the number of items on the scale, and employing both subjective and objective measures.

Third, as the data for this study are drawn from SEs of China, the generalizability of the findings may be constrained to the Chinese context. In future studies, it would be interesting to replicate the study in other contexts. Specifically, collecting cross-country data will make it possible to comparatively investigate the relationship between organizational capabilities and SE performance under alternative circumstances across developed/developing or Western/Eastern countries.

Lastly, the sample size for this study is relatively small (206 SEs), and future studies can benefit from the samples on a larger scale. Additionally, future research can use longitudinal samples and closely examine how the effects of organizational capabilities may change over time, using lagged time to test the causal relationships between variables and to rule out any reverse causality effects.