Innovative Climate, a Determinant of Competitiveness and Business Performance in Chinese Law Firms: The Role of Firm Size and Age

Abstract

In the past few decades, a firm’s innovative climate has received much attention in the context of innovative behavior, competitiveness, and business performance. The existing literature has relied to a great extent on innovative climate as an interacting factor and overlooked its role as an antecedent of various organizational phenomena. Furthermore, the interaction effects of the firm’s size and age on the relationships between innovative climate and other organizational variables have gone unnoticed. This study adds to the literature by empirically assessing the effects of the firm’s innovative climate on organizational learning and employees’ innovative behavior as well as its consequences on the firm’s competitiveness and business performance. Additionally, it addresses the interaction impacts of firm size and age on the relationships between the abovementioned variables. This research achieves its goal by developing an integrative research design that analyzes complex relations using covariance-based structural equation modeling (SEM) and regression techniques on a dataset of 408 Chinese law firms. The results indicate that the firm’s innovative climate has a significant positive relationship with organizational learning and employees’ innovative behavior. It is also found that organizational learning has a significant positive influence on employees’ innovative behavior. Meanwhile, organizational learning and employees’ innovative behavior have a significant positive influence on firm competitiveness and business performance. Another important finding is that contextual factors, i.e., firm size and age, strengthen these relations. Theoretical and managerial implications, including links to firm size and age, are provided.

1. Introduction

Economic and technological development and globalization reveal that constant innovation is the determining factor of competitive superiority and business performance, regardless of the type of industry [1]. It is critical to carry out in-depth analysis of the organizational factors or mechanisms that help to promote innovative accomplishments and enhance a firm’s competitiveness and business performance. In the current globalized and dynamic business environment, practitioners and academics are agreed that a continuous innovation strategy is compulsory for a firm’s survival [2]. Researchers have utilized various theories for conceptualizing the contextual factors of the work environment that influence a firm’s competitiveness and business performance. Among these prominent theories are leadership member exchange theory [3], interaction theory [4], componential theory [5,6], multiple social domains theory [7], and organizational climate theory [8].

In the past few decades, a massive amount of research has been dedicated to identifying which factors are the most crucial for a firm’s competitiveness. Trends reveal that innovative climate is one of the most critical factors for the firm’s competitiveness and business performance [9]. Researchers have examined innovative organizational climate from different perspectives to find how it influences the firm’s overall performance [10]. An innovative organizational climate is considered a determinant factor of employee creativity, knowledge creation, and sustainable business performance [11]. An innovative climate is an imperative antecedent of a firm’s performance and other organizational phenomena [6,10].

Organizational learning is the process of knowledge creation by individuals in an organized manner followed by injecting the said knowledge into the organizational knowledge system [12]. Organizational learning is a major determinant of a firm’s performance and competitiveness. Furthermore, organizational learning depends on the firm’s absorptive capabilities [13]. Organizational learning is aimed at developing employees’ behavior toward innovations; hence, this process involves cognitive-behavioral change [12]. Employees’ innovative behavior is highly dependent on the workplace environment [14]. Human resources are the most critical asset of a firm and significantly influence the firm’s performance. An innovative climate and organizational learning encourage employees to learn, exchange, and interpret information and perform in the best possible way to achieve the firm’s shared goals [3]. However, little attention has been paid to the investigation of this critical phenomenon in relation to organizational learning, employees’ innovative behavior, firm competitiveness, and business performance in a single conceptual design.

This research investigates the firm’s innovative climate as an antecedent of organizational learning, employees’ innovative behavior, competitiveness, and business performance to fill the existing literature gap. Furthermore, firm size and age are considered as contributing factors in determining organizational learning, employees’ innovative behavior, and business competitiveness, which is marginally discussed in the literature. To address this issue, we choose Chinese law firms for conducting this research. China is one of the world’s largest economies with a high volume of global trade [15], which demands highly innovative legal services for smooth operations [16]. Furthermore, the Chinese legal market is relatively young compared to the Western market. Chinese law firms are more willing to adopt new business models, technology, and alternative fee structures, and are “less hindered by the traditional legal industry intransigence that has slowed large scale change in the legal markets in the West, especially in the United States” [17].

The Chinese legal market is growing at a rapid pace and is less bound by established institutional traditions and inertia. Reuters [16] reveals that 55% of Chinese law firms use an alternative fee arrangements structure, whereas this ratio is 17% in the USA. Approximately 93% of large Chinese corporations have international legal needs, while 62% of global multinationals have legal needs in China [18]. Shepherd [17] noted that China is taking hold of technology-enabled legal innovations such as workflow automation, delivery of legal services, and quick solutions as compared to the West. Chinese law firms are more willing to try new things and could “become the most sophisticated legal market in the world eventually” [16,17]. Thus, Chinese law firms represent a suitable case study for this research. Moreover, the legal industry and law firms are ignored to some extent in organizational studies [19]. Therefore, we assumed that the degree to which the employees of a firm perceived the organizational climate as more helpful and supportive of innovation would influence organizational learning capabilities and individual innovative behavior. In turn, organizational learning and innovative behavior impact firm competitiveness and business performance. This study answers the following questions:

• Does an innovative climate influence organizational learning in law firms?
• Does an innovative climate influence employees’ innovative behavior in law firms?
• Does organizational learning influence a law firm’s competitiveness and business performance?
• Does employees’ innovative behavior influence a law firm’s competitiveness and business performance?
• Do firm size and age influence the intra-relationship between innovative climate, organizational learning, innovative behavior, competitiveness, and business performance?

Based on these questions, we arranged the literature and developed our conceptual model and hypotheses. These hypotheses were tested on data collected from 408 respondents from Chinese law firms. Structural equation modeling and regression techniques were applied for the analysis. The findings reveal that the innovative climate significantly contributes to organizational learning and employees’ innovative behavior, whereas the latter two lead to the law firm’s competitiveness and performance. Moreover, this investigation found mixed influences of the firm’s size and age on various combinations of the abovementioned variables. The findings of this research make significant contributions to the literature on innovative climate as an antecedent of vital organizational phenomena that play a crucial role in the sustainable survival of a business firm. This research provides a conceptual design for how firms can improve their competitiveness and performance by the introduction of an innovative climate into the workplace. Thus, an innovative work environment encourages new knowledge creation, information sharing, resource allocation, facilitation, team collaboration, and generation and implementation of creative ideas, all of which is essential for sustainable competitive advantages over competitors and sustained performance. The theoretical and practical implications of the study are explored in detail in the Discussion section.

2. Literature Review and Hypothesis Development

Organizational and individual-level studies empirically support the impacts of climate on innovative behavior, organizational learning, innovative performance, and firm competitiveness [20]. Competent leaders create an innovative climate in which employees have the opportunity to improve and share their experience and expertise [21]. An innovative climate encourages training, brain-storming, and skill development. It is an innovative climate that stimulates creativity and leads to thinking outside the box to improve processes, take calculated risks, develop new products and services, and advance business model design [22]. Innovativeness is not only about the introduction of technology, but it is about newness and originality. In a business context, innovation means “the creation and capture of new values in new ways,” as well as “the successful introduction of new services, products, process, and business models” [23]. With the rapid change in technology and business models, the survival of law firms depends on competitiveness and innovative performance [24], whereas the innovative climate sets the stage for the innovative performance and competitiveness of a firm. Law firms are seeking innovation in terms of fresh ideas, processes, delivery, and improved business models for keeping themselves competitive in the market [23]. Trends show that like other businesses, law firms’ innovative climate depends on trust, risk management, trust and care for employees, clear vision, encouraging breaking the rules, supporting innovative ideas and processes, rewarding innovative champions, creating incentives, providing resources, and considering long-term business models [25]. The conceptual and hypothetical model of the present study is given in Figure 1.

2.1. Innovative Climate, Organizational Learning, and Innovative Behavior

An innovative climate has been regarded as an important contextual condition for organizational learning and employee innovative behavior [9]. Innovative climate refers to the organizational climate that fosters innovations [11]. An innovative climate is a firm atmosphere that fosters and propagates creative mechanisms to achieve its goals. Research on firm climate focuses on the employees’ perception of the work climate, which influences their attitudes and behaviors at work [10]. Climate has been viewed as a positive antecedent of creativity and learning [11,26]. There are various definitions of innovative climate; however, we have adopted a definition that is consistently and frequently used by researchers, which considers innovative climate as the “shared perceptions at an individual, team and organizational level as to the extent to which individual, team, and organizational processes encourage and enable innovation” [10,27,28]. Thus, the innovative climate is a combination of autonomy, leadership support, flexibility, encouragement for creative ideas, employee welfare, resource provision, trust, cooperation, communication, security, clarity of goals, outward focus, performance feedback, and reward [28,29,30]. An innovative climate focuses on individual intellectual activities and processes that create new ideas, insights, and innovative solutions to problems and concentrates on the adaptation, exploitation, application, and successful implementation of these ideas, solutions, and insights [6,10].

The innovative climate encourages employees toward knowledge acquisition, information distribution, information interpretation, and recalling organizational memory [31,32]. Thus, the innovative climate motivates employees to think outside the box, experiment, and use the existing knowledge of the firm in an innovative way to find solutions and enhance firm innovativeness. Researchers suggest that an innovative firm environment is positively associated with knowledge development, resource exchange, value creation, and product and service innovation [33,34]. Trends indicate that previous studies (e.g., [32,35]) have used an innovative climate as a moderator between organizational learning and innovative behavior, and creative self-efficacy. However, we believe that it is an innovative climate in itself that motivates and encourages individuals and teams to search for, share, interpret, and implement knowledge. Thus, this discussion leads us to propose the following hypothesis (Hypothesis 1):

Hypothesis 1 (H1).

Innovative climate is positively associated with organizational learning.

The innovative climate of a firm is regarded as an essential component of the employees’ innovative behavior [36]. The perception of a firm’s innovative climate has a strong influence on employees’ creativity and innovative work behavior [30]. Jaiswal and Dhar [37] found that innovative climate has a significant positive effect on team and individual innovative work behavior. A strong relationship between the various dimensions of an innovative climate at a group level (vision, support for innovation, task orientation) and employees’ innovative behavior was reported [38]. Furthermore, the innovative climate is regarded as a predictor of individual-level innovative behavior [39]. The support for creativity and innovation provides psychological safety to the employees to behave in innovative manners [40]. Thus, these references provide good support to assume that innovative climate is positively associated with employees’ innovative behavior; hence, we pose the following hypothesis (Hypothesis 2).

Hypothesis 2 (H2).

Innovative climate is positively associated with employees’ innovative behavior.

2.2. Organizational Learning, Competitiveness, Employees’ Innovative Behavior, and Business Performance

Organizational learning is a process defined as the acquisition of knowledge; distribution, interpretation, and analysis of information; and organizational memory. Knowledge acquisition is the process through which knowledge is obtained, such as knowledge available at the firm, learning from experience, observation, and searching for information in the firm’s internal and external environment [41,42]. Information distribution is the sharing of knowledge to understand existing and future phenomena; information distribution makes the learning process effective [42]. Employees interpret this information at the individual, team, and organizational levels to understand and clarify how the obtained information can influence a firm’s future strategy [31]. Organizational memory means recalling and storing knowledge for the firm’s future use [43]. Employees who feel a sense of autonomy, security, and environment conducive to innovative thinking are more motivated to learn and share information [32]. Trends suggest that firms by themselves are unable to produce knowledge and depend on individuals to create and share knowledge across the organization [44].

An organization’s ability to learn at the firm, team and individual levels determines its ability to compete in the modern market [45]. The transfer of individual knowledge occurs through social interaction, and as a result of shared interpretation, the accumulated knowledge allows individuals to learn from an organization; hence, this mutual exchange of information transfers knowledge between individuals, teams, and firms [46]. The competitiveness of an organization depends on its resources and ability to be valuable, rare, inimitable, and non-substitutable [45]. Organizational learning is valuable as it helps the firm to take advantage of the prevailing market opportunities and defend against competition threats; hence, it is a competitive tool in the market situation [47]. Moreover, organizational learning helps a firm to obtain real-time knowledge and to understand the firm’s environment efficiently through knowing customers’ needs; thus, organizational learning reduces environmental complexities and uncertainty. Organizational learning is a complex process that requires specific skills both in creating and adopting knowledge; hence, it is a rare capability [48]. Organizational learning is not easy to imitate or transfer as it is an intangible asset, although competitors may have to watch the general behavior [47]. Moreover, organizational learning cannot be substituted because it is difficult to replace the current market [49]. The flexibility characteristic of organizational learning allows firms to reallocate resources rapidly to the identified market opportunities [50]. Thus, a greater learning ability is essential for a firm to compete in the market due to the diversity of knowledge, changing market demand, and advanced technology. This discussion leads us to assume that the firm’s competitiveness is positively associated with organizational learning. Hence, we posit the following hypothesis (Hypothesis 3).

Hypothesis 3 (H3).

Organizational learning is positively associated with the firm’s competitiveness.

Organizational learning means that knowledge and competencies are available within the firm at any given time, regardless of the people involved [51]. Organizational learning helps in understanding customer demand, by learning from observation, mistakes, collaboration, experience, and current market trends [52]. Organizational learning provides opportunities for employees to learn and distinguish themselves by behaving creatively to solve organization problems or introduce new methods, procedures, products, and services [51]. Thus, organizational learning offers a chance to employees for career development, which motivates them to behave in innovative manners. When employees are more involved in organizational learning, such involvement benefits innovative behavior [32]. Trends show that employees’ innovative behavior is influenced by inner motives, social networks, knowledge, and cognitive ability [53]. Research indicates that knowledge sharing, communication, collaboration, socialization, and flow of information in the firm greatly influence employees’ innovative behavior [54,55]. This discussion leads us to assume that organizational learning is positively associated with employees’ innovative behavior. Thus, we propose the following hypothesis (Hypothesis 4).

Hypothesis 4 (H4).

Organizational learning is positively associated with employees’ innovative behavior.

Innovative performance has become one of the crucial elements for firm survival in global competitive markets [56]. Trends show that business performance is dependent on organizational learning capabilities [57]. The organizational learning concept allows a firm to learn about customer needs, market competitors, and market regulators, to identify opportunities in the marketplace, and to act upon them in light of the prevailing information [58]. Lopez, Peón, and Ordás [59] regarded organizational learning as the determining factor for business performance. Chung, Yang, and Huang [60] and Jiménez-Jiménez and Sanz-Valle [61] reported a relationship between organizational learning and business performance. Thus, it is assumed that organizational learning has a positive association with firm business performance (Hypothesis 5).

Hypothesis 5 (H5).

Organizational learning has a positive association with the firm’s business performance.

2.3. Innovative Behavior, Competitiveness, and Business Performance

Innovative behavior refers to the “introduction and application of new ideas, products, services, processes, and procedures to a person’s work role, work unit or organization” [62]. Employees’ innovative behavior has been identified as crucial for firm competitiveness and business performance [9]. Innovative behavior begins with problem recognition and the generation of solutions or ideas, either adopted or novel. In the next step, the employee seeks sponsorship for an idea to build an alliance of supporters. In the final stage of the innovation process, the innovative employee converts the idea by producing a prototype of the innovation, which is then diffused to mass production [20,63]. Employee innovative behavior helps in building the firm’s competitiveness. A firm’s ability to develop innovative processes and introduce innovation into the market depends on its employees’ innovative behavior; furthermore, employees’ innovative behavior is a determinant of a firm’s competitiveness and business performance [51]. Trends from empirical studies on the association between innovative behavior, competitiveness, and business performance provide evidence of positive relationships between these variables [64]. The porter’s competitive strategic model suggests that competitive advantage improves a firm’s financial health (such as profit, margins, and return on investment (ROI)) and market health (such as market share and sales) compared to its competitors [45,65]. Thus, this discussion leads us to believe that employees’ innovative behavior is essential for firm competitiveness and business performance. We propose the following hypotheses (Hypothesis 6 and 7):

Hypothesis 6 (H6).

Employees’ innovative work behavior has a positive association with the firm’s business performance.

Hypothesis 7 (H7).

Employees’ innovative work behavior has a positive association with the firm’s competitiveness.

2.4. Firm Size and Age Moderation Effects

This article utilizes firm size and age as moderators for studying the relationships between innovative climate, organizational learning, innovative behavior, competitiveness, and business performance. The literature trends suggest that these variables are often cited for moderation influence in Business and Organizational Studies [61]. Firm size has a positive impact on innovation and the firm’s performance, since large firms have more resources to invest in innovations and create an innovative climate [66,67]. Furthermore, firm size also has effects on organization competitiveness, with varying effects reported in different geographical areas [68]. Trends suggest that firm size is positively associated with sales, growth, and income [69]. However, a few studies indicate that although firm size favors innovation, it does not play a determinant role [70]. Jiménez-Jiménez and Sanz-Valle [61] reported that firm size and age moderate the relationship between innovation, organizational learning, and performance. Furthermore, firm age influences organizational learning and performance [71]. As age increases, the experience and competencies of a firm develop, which helps in running their operations effectively and efficiently [72]. Research also suggests firm age is negatively associated with innovation as older firms are mostly reluctant to adopt changes because of the status quo; furthermore, it is hard for large firms to change due to their complicated structure [73]. Therefore, this discussion leads us to believe that firm size and age may have an impact on the relationships between innovative climate, organizational learning, innovative behavior, competitiveness, and business performance. Thus, we propose the following hypotheses (Hypothesis 8a–9d):

Hypothesis 8a (H8a).

Firm size moderates the relationship between innovative climate and organizational learning.

Hypothesis 8b (H8b).

Firm size moderates the relationship between innovative climate and innovative behavior.

Hypothesis 8c (H8c).

Firm size moderates the relationship between innovative behavior and business performance.

Hypothesis 8d (H8d).

Firm size moderates the relationship between organizational learning and competitiveness.

Hypothesis 9a (H9a).

Firm age moderates the relationship between innovative climate and organizational learning.

Hypothesis 9b (H9b).

Firm age moderates the relationship between innovative climate and innovative behavior

Hypothesis 9c (H9c).

Firm age moderates the relationship between innovative behavior and business performance.

Hypothesis 9d (H9d).

Firm age moderates the relationship between organizational learning and competitiveness.

3. Methodology and Measurements

The purpose of this study is to examine the role of innovative climate in organizational learning, employees’ innovative behavior, firm competitiveness, and business performance in Chinese law firms. Moreover, we aim to investigate whether the firm’s size and age play any significant role in moderating the relationship between these variables.

3.1. Industry Setting

Massive disruption in the legal industry worldwide requires law firms to innovate for survival [74]. We choose the Chinese legal sector because China is one of the world’s trade giants, and “the legal market in China is evolving rapidly” [16]. Trends suggest that law firms in China are using a combination of strategies to meet market needs [19]. Chinese law firms are adopting innovation and innovative strategies more rapidly than the USA and UK. Statistics show that in China, “alternative fee arrangements (AFAs) are used in 55% of matters as compared to the USA, it is 17%” [16]. China’s legal firms are investing in legal technologies and business models to cope with their customers’ international legal needs [75]. Thus, to investigate innovative climate, organizational learning, innovative behavior, competitiveness, and business performance in law firms, China represents a suitable market for this study.

3.2. Sample

This study used a cross-sectional survey design for data collection. A random sample technique was applied to collect data from the respondents. The data were collected from managers and supervisor level positions as they work as a bridge in the flow of information from top to bottom and bottom to top. The number of employees working in a firm determined the firm’s size. This study followed European Union categorization criteria for firm size, where small <50, medium <250, and large ≥250 employees [3]. The data were collected from law firms in Beijing, Zhejiang, Shanghai, Habei, and Guangzhou. A questionnaire was developed and translated into Chinese, and we recruited candidates in each city to conduct the survey. The questionnaire was distributed to 900 respondents (face to face, through emails, or by wechat) with a self-explanatory letter. The survey was conducted in March and April 2019. We assured all the respondents that the data would be used for research purposes and that their privacy would be kept secret. It is worthy to mention that we collected data only from those firms that had introduced any one type of technological, service delivery, structural, data management, alternative legal fee structure, and business model innovations in the last five years.

By the end of April 2019, we had received a total of 408 complete responses; hence, the response rate was 45.3%. The demographic characteristics of the sample, as given in

Table 1. Demographics of the sample.

Characteristics	Frequency	Percentage
Gender
Male	253	62.0
Female	155	38.0
Education
Bachelor’s	133	32.6
Master’s	205	50.2
Ph.D.	28	6.9
Others	42	10.3
Firm size
Less than 50 employees (small)	42	10.3
Less than 250 employees (medium)	154	37.7
Greater than 250 employees (large)	212	52.0
Firm age
Less than 10 years (young)	49	12.0
Greater than 10 but less than 20 years (medium age)	86	21.1
Greater than 20 years (mature)	70	66.9

, show that 62.0% of the respondents were male and 38% were female. The education level of the respondents indicates that most of our sample respondents had a higher education degree, where 50.2% of the respondents had Master’s degrees and 32.6% had Bachelor’s degrees. The firm size consists of 10.3% small and 52.0% large firms. The distribution of the firm age shows that 12.0% of the firms were young, 21.1% belonged to medium age, and 66.9% were mature firms.

3.3. Measurements

The constructs’ measurement items were adopted after a careful literature review; however, we have made several changes according to the requirement of the study. All of the constructs were measured on a five-point Likert scale from 1 (strongly disagree) to 5 (strongly agree). The level of innovative climate was measured by using an eight-item scale adapted from Mathisen and Einarsen [22], Dunegan, Tierney [76], Ren and Zhang [9], and Daly, Liou [77]. The level of organizational learning was measured by seven items adapted from García-Morales, Jiménez-Barrionuevo [78], Jiménez-Jiménez and Sanz-Valle [61], Chung, Yang [60], and Francis and Bessant [79]. Innovative behavior was measured by five items adapted from Yuan and Woodman [80], and Scott and Bruce [20]. Competitiveness and business performance were measured by three items each adapted from Husain, Dayan [51], Hult, Ketchen [81], Song, Di Benedetto [82], Tippins and Sohi [42], and García-Morales, Jiménez-Barrionuevo [78]. The details of constructs and their items are given in

Table 2. Constructs and measurement items.

Variables	Code	Items	Reference
Innovative climate	IC1	Innovation is one of the most important values in this firm	Mathisen, Einarsen [22], Dunegan, Tierney [76]
	IC2	This firm encourages team collaboration	Ren and Zhang [9], Dunegan, Tierney [76]
	IC3	This firm provides support for innovation	Mathisen, Einarsen [22], Dunegan, Tierney [76]
	IC4	This firm clearly shares the firm’s vision with its employees	Nybakk, Crespell [11], Moolenaar, Daly [83]
	IC5	Employees are provided with autonomy and trusted	ZHENG, JIN [84], Daly, Liou [77]
	IC6	Information is shared in this firm	Ren and Zhang [9], Mathisen, Einarsen [22]
	IC7	Innovative ideas are rewarded	Nybakk, Crespell [11]
	IC8	Resources are provided to the employees	Dunegan, Tierney [76], Mathisen, Einarsen [22]
Organizational learning	OI1	The firm has acquired and shared much new and relevant knowledge that has provided a competitive advantage	García-Morales, Jiménez-Barrionuevo [78], Jiménez-Jiménez and Sanz-Valle [61]
	OI2	This firm focuses on acquiring knowledge about product/service strategies that involve experimentation	Chung, Yang [60], Francis and Bessant [79]
	OI2	This firm learns from observation	Husain, Dayan [51], Francis and Bessant [79]
	OI3	The employees attend fairs and exhibitions regularly	Perez Lopez, Montes Peon [57]
	OI4	The firm collects individual knowledge and shares it	Jiménez-Jiménez and Sanz-Valle [61], Francis and Bessant [79]
	OI5	Employees share knowledge and experiences by talking to each other	Jiménez-Jiménez and Sanz-Valle [61], Chung, Yang [60]
	OI6	Teamwork is a very common practice in this firm	Jiménez-Jiménez and Sanz-Valle [61], Francis and Bessant [79]
	OI7	The company has up-to-date databases of its clients	Jiménez-Jiménez and Sanz-Valle [61], Chung, Yang [60]
Innovative behavior	IB1	Individuals generate creative ideas	Yuan and Woodman [80], Scott and Bruce [20]
	IB2	The firm searches for new technologies, processes, techniques, and/or product ideas	Yuan and Woodman [80], Scott and Bruce [20]
	IB3	The firm promotes and champions ideas to others	Yuan and Woodman [80], Scott and Bruce [20]
	IB4	The firm investigates and secures funds needed to implement new ideas	Yuan and Woodman [80], Scott and Bruce [20]
	IB5	The firm develops adequate plans and schedules for the implementation of new ideas	Yuan and Woodman [80], Scott and Bruce [20]
Competitiveness	C1	Innovation capability makes us more competitive	Husain, Dayan [51], Hult, Ketchen [81], Song, Di Benedetto [82]
	C2	Technological flexibility allows us to choose innovative solutions	Husain, Dayan [51], Hult, Ketchen [81], Song, Di Benedetto [82]
	C3	Business partners’ support makes us more competitive	Husain, Dayan [51], Hult, Ketchen [81], Song, Di Benedetto [82]
Business performance	BP1	This firm retains and attracts customers	Tippins and Sohi [42], García-Morales, Jiménez-Barrionuevo [78]
	BP2	This firm earns good profit	Tippins and Sohi [42], García-Morales, Jiménez-Barrionuevo [78]
	BP3	This firm has a good market share	Tippins and Sohi [42], García-Morales, Jiménez-Barrionuevo [78]

. Firm age was measured in years; all the firms were classified into three categories. Those firms falling into the 10 years or less age group were considered young; firms falling between 10 years and 20 years were counted as medium age, and those falling above 20 years were considered mature firms.

4. Results and Analyses

4.1. Common Method Variance (CMV)

Data collected from single sources in a cross-sectional survey design lend themselves to the chance of common method bias or common method variance occurring [85,86]. This is the spurious variance that is associated with the measurement method rather than the construct measures, which are assumed to measure specific phenomena [19]. Podsakoff, MacKenzie [87] recommended controlling CMV as it influences the results in social sciences. Various tests have been used by scholars for checking the CMV in a dataset; however, Harman’s single factor test is applied the most in social science research [88,89]. The results show that the first factor explained 49% variance out of the total, which is less than the recommended threshold value of 50% [90]. Thus, Harman’s test suggests the absence of CMV in our dataset.

4.2. Validity and Reliability

The study proposed a conceptual model that was analyzed in two stages; first, we analyzed the measurement model and the structural model—an exploratory factor analysis with 26 items to unveil the underlying patterns in the participant’s responses. A five-factor rational solution with 23 items was obtained with a KMO value of 0.936 and significant Bartlett test (χ² = 8913.3, p = 0.000). Thus, confirmatory factor analysis with the maximum likelihood method was performed to establish the required convergent validity, discriminant validity, and reliability of the constructs. The construct reliability measures the degree to which items are free from random error [2]. The value of Cronbach’s alpha (CA) and composite reliability values are higher than 0.7 for the evaluation criteria (see

Table 3. Confirmatory factor analysis.

Constructs	Items	Loading	CA	CR	AVE	MSV
Innovative Climate (IC)	IC1	0.810	0.947	0.950	0.708	0.449
	IC2	0.918
	IC3	0.841
	IC4	0.942
	IC5	0.961
	IC6	0.795
	IC7	0.750
	IC8	0.672
Organizational Learning (OI)	OI1	0.924	0.935	0.941	0.730	0.449
	OI2	0.960
	OI3	0.902
	OI4	0.692
	OI5	0.674
	OI6	0.874
Innovative Behavior (IB)	IB1	0.889	0.886	0.883	0.662	0.342
	IB2	0.850
	IB3	0.917
	IB4	0.542
Competitiveness (C)	C1	0.820	0.915	0.917	0.787	0.342
	C2	0.903
	C3	0.934
Business Performance (BP)	BP1	0.812	0.838	0.841	0.727	0.227
	BP2	0.891

CA = Cronbach’s alpha, CR = composite reliability, AVE = average variance extracted, MSV = maximum shared variance.

), which suggests the internal consistency of the items within a construct [19].

All the items’ estimated factor loadings are significant and higher than 0.5, as shown in Table 3, which is acceptable [91] and suggests good convergent validity. The convergent validity measures the consistency across multiple constructs [2]. The value of composite reliability (CR) > 0.7, average variance extracted (AVE) > 0.5, and CR > AVE, which suggests the convergent validity of the constructs. Furthermore, to measure the discriminant validity of the constructs, the extent to which various constructs deviate or diverge from one another, we used two criteria; first, AVE > maximum shared variance (MSV), and second, the square root of AVE for each construct (diagonal values of the correlation matrix in

Table 4. Mean, standard deviation, and correlations.

Variables	Mean	SD	C	IC	OI	IB	BP
C	4.182	0.667	0.887
IC	4.066	0.532	0.571	0.841
OI	4.653	0.632	0.585	0.670	0.855
IB	4.127	0.762	0.585	0.491	0.460	0.814
BP	3.651	0.679	0.371	0.371	0.353	0.476	0.852

Notes: SD = Standard deviation, C = Competitiveness, IC = Innovative climate, OI = Organizational learning, IB = Innovative behavior, and BP = Business performance.

) should be greater than the absolute value of inter-construct correlations (off-diagonal elements) [92,93]. Thus, the AVE > MSV as indicated by the values in Table 3, and the square root of AVE values at a diagonal in Table 4 is greater than any correlation between the constructs, hence suggesting the discriminant validity of the constructs—these results for the measurement model support the use of the proposed model in this study.

4.3. Measurement Model

This study analyzed the model fit of the measurement model with three criteria suggested by Hair, Ringle [94], namely, absolute fit, incremental fit, and parsimonious fit. The values of the measurement model lie within the defined threshold criteria suggested by Hair, Black [95] and Hu and Bentler [96]. The model fit indices suggested a good fit for the measurement model as χ²/DF = 2.903, CFI = 0.95, NFI = 0.93, TLI = 0.94, IFI = 0.95, RMSEA = 0.068, and SRMR = 0.045 as presented in

Table 5. Measurement and structural model comparison.

Model	Absolute Fit	SRMR	RMSEA	PCLOSE	Incremental Fit	PNFI	Parsimonious Fit	IFI	TLI
	χ2/DF				NFI		CFI
MM	2.903	0.0448	0.068	0.000	0.930	0.809	0.953	0.953	0.946
SM	2.939	0.0527	0.069	0.000	0.928	0.818	0.951	0.951	0.945

Notes: CFI = Comparative fit index; NFI = Normed fit index; TLI = Tucker-Lewis index; IFI = Incremental fit index; RMSEA = Root mean square error of approximation. SRMR = Standardized Root Mean Square Residual.

.

4.4. Structural Model

This study aimed to examine the relationship between innovative climate, organizational learning, innovative behavior, competitiveness, and business performance in Chinese law firms. We performed structural equation modeling (SEM) with the maximum likelihood method, as proposed by Hoyle [97] and Hair Jr, Babin [98]. The results of SEM indicate a good fit as the fit indices fall within the threshold values suggested by Hair, Black [95] and Hu and Bentler [96], where χ²/DF = 2.94, CFI = 0.95, NFI = 0.92, TLI = 0.94, IFI = 0.95, RMSEA = 0.069, and SRMR = 0.053 as shown in Table 5.

4.5. Hypothesis Testing

This study examines the proposed hypotheses through the path coefficients of SEM. All the paths were analyzed with standardized coefficients, t-values (CR = critical ratio), and p-values by using Amos 24, as shown in

Table 6. Path analysis.

Path	Standard Coefficient	t-Value (CR)	p-Value	Hypotheses	Remarks
Innovative climate is positively associated with organizational learning	0.67	12.224	0.000	H1	Supported
Innovative climate is positively associated with employees’ innovative behavior	0.35	5.267	0.000	H2	Supported
Organizational learning is positively associated with the firm’s competitiveness	0.40	8.394	0.000	H3	Supported
Organizational learning is positively associated with employees’ innovative behavior	0.23	3.588	0.000	H4	Supported
Organizational learning has a positive association with the firm’s business performance	0.17	2.994	0.003	H5	Supported
Employees’ innovative behavior has a positive association with the firm’s business performance	0.40	6.445	0.000	H6	Supported
Employees’ innovative behavior has a positive association with the firm’s competitiveness	0.41	8.247	0.000	H7	Supported

. The results indicate that innovative climate has a significant positive association with organizational learning, where β = 0.67, t = 12.22, and p = 0.000; thus, hypothesis H1 is supported. Innovative climate shows a significant positive relationship with innovative behavior, where β = 0.35, t = 5.27, and p = 0.000; hence, hypothesis H2 is validated. Organizational learning exhibits a significant positive association with the firm’s competitiveness, where β = 0.40, t = 8.39, and p = 0.000; therefore, hypothesis H3 is confirmed.

Moreover, organizational learning shows a significant positive relationship with employees’ innovative behavior, where β = 0.23, t = 3.58, and p = 0.000; hence, the proposed hypothesis H4 is verified. Organizational learning has a significant positive association with the firm’s business performance, with β = 0.17, t = 2.99, and p = 0.003; thus, hypothesis H5 is validated. Employees’ innovative behavior has a significant positive association with the firm’s business performance, with β = 0.40, t = 6.44, and p = 0.000; thus, hypothesis H6 is confirmed. Employees’ innovative behavior also shows a significant positive association with the firm’s competitiveness, where β = 0.41, t = 8.25, and p = 0.000; hence, hypothesis H7 is confirmed. A path diagram of the confirmed hypotheses is shown in Figure 2.

We used Andrew Hayes SPSS process macro 3.1 [99] to examine the proposed moderation hypotheses (H8a–H8d, H9a–H9d). The results reported in

Table 7. Moderation analysis.

Paths	Coefficient	SE	t	Significance (p)	Bootstrapping
					LLCI	ULCI
Moderation Model 1 (dependent OI)
Innovative Climate (IC)	1.1124	0.1099	10.117	0.0000	0.8963	1.3286
Firm size	1.0476	0.2226	4.7065	0.0000	0.6100	1.4852
IC × Firm size	−0.2169	0.0542	−4.0024	0.0001	−0.3234	−0.1103
Conditional Effects
Small	0.7338	0.0472	15.535	0.0000	0.6410	0.8267
Medium	0.5884	0.0566	10.386	0.0000	0.4771	0.6996
Large	0.4619	0.0787	5.8676	0.0000	0.3071	0.6166
Moderation Model 2 (dependent IB)
Innovative Climate (IC)	0.5557	0.1176	4.7232	0.0000	0.3244	0.7870
Firm size	1.3164	0.2813	4.6803	0.0000	0.7635	1.8693
IC × Firm size	−0.1491	0.0666	−2.2369	0.0258	−0.2801	−0.0181
Conditional Effects
Small	0.3157	0.0570	5.5427	0.0000	0.2038	0.4277
Medium	0.2115	0.0762	2.7737	0.0058	0.0616	0.3613
Large	0.1084	0.1123	1.9652	0.0335	0.1124	0.3293
Moderation Model 3 (dependent OI)
Innovative Climate (IC)	0.9956	0.1045	9.5290	0.0000	0.7902	1.2010
Firm age	1.0507	0.1963	53531	0.0000	0.6649	1.4366
IC × Firm age	−0.1903	0.0487	−3.9093	0.0001	−0.2860	−0.946
Conditional Effects
Young	0.6437	0.0448	14.368	0.0000	0.5556	0.7317
Medium	0.5106	0.0535	9.5453	0.0000	0.4054	0.6158
Mature	0.4248	0.0681	6.2350	0.0000	0.2909	0.5587
Moderation Model 4 (dependent C)
Org Learning (OI)	0.1927	0.0987	1.9534	0.0515	−0.0012	0.3867
Firm age	−0.5179	0.2632	−1.9677	0.0498	−1.0353	−0.0005
OI × Firm age	0.1719	0.0553	3.1059	0.0020	0.0631	0.2807
Conditional Effects
Young	0.5107	0.0509	10.029	0.0000	0.4106	0.6108
Medium	0.6309	0.0934	7.5851	0.0000	0.4870	0.7747
Mature	0.7084	0.0934	7.5851	0.0000	0.5248	0.8920

suggest that firm size moderates the relationship between innovative climate and organizational learning with β = −0.22, t = −4.00, and p = 0.0001; hence, hypothesis H8a is supported (for more detail, see model 1 in Table 7). The moderation effects of firm size between innovative climate and innovative behavior suggest the firm’s size as a significant moderator with β = −0.15, t = −2.14, and p = 0.0258; therefore, hypothesis H8b is confirmed. The results indicate that the firm’s age moderates the relationship between the innovative climate and organizational behavior with β = −0.19, t = −3.91, and p = 0.0001; hence, hypothesis H9a is validated. It is also found that the firm’s age moderates the relationship between organizational learning and the firm’s competitiveness with β = 0.17, t = 3.11, and p = 0.0020; thus, hypothesis H9d is supported. However, we failed to find support for H8c, H8d, H9b, and H9c; therefore, these hypotheses are rejected. The moderation plots of H8a, H8b, H9a, and H9d are given in Figure 3, Figure 4, Figure 5 and Figure 6.

5. Discussion and Theoretical Implications

There is extensive literature on the relationships between innovative climate and organizational learning, innovative behavior, business competitiveness, and performance. However, this is the first study that combines all these variables into a single conceptual model. Previous literature suggests that innovative climate may act as a moderator or mediator between various variables. For instance, García-Buades, Martínez-Tur [100] found that innovative climate moderates the relationship between team engagement and business performance. However, little attention has been paid to innovative climate as an antecedent of several organizational phenomena. This research extended prior conceptualizations of the relationship between innovative climate, competitiveness and business performance, as well as identifying critical variables such as organizational learning and innovative behavior that create a strong bond between the abovementioned variables. We argue that a detailed understanding of the link between the innovative climate, the firm’s competitiveness, and business performance can be achieved through the inclusion of organizational learning and employees’ innovative behavior. Moreover, we introduced firm size and age as moderators between various variables for understanding these relationships in a much deeper sense. Thus, this study offers a more comprehensive understanding of innovative climate than that previously reported in the literature.

The structural equation model in Figure 2 indicates that innovative climate significantly contributes to organizational learning and innovative behavior in Chinese law firms. The findings of this study reflect those of Ren and Zhang [9] and Nybakk, Crespell [11], who proposed that an innovative climate is a strategic driver of employees’ innovative behavior and a firm’s performance. These findings support the notion of psychological climate theory that hypothesizes that individuals “respond primarily to a cognitive representation of the environment” [20]. The climate provides signals to individuals as to what kind of behaviors and potential outcomes are expected from them. Thus, individuals respond to these expectations by regulating their behaviors to highlight positive self-evaluation, satisfaction, and pride and to be rewarded. Leadership sets an innovative climate to provide better chances for learning and to encourage employees to use the firm’s existing and prevailing market knowledge and their experiences for the generation, processing, and implementation of new ideas to find innovative solutions. Thus, the findings of this study also support leadership member exchange theory [3]. Furthermore, the firm’s innovative climate ensures knowledge acquisition, information sharing, provision of adequate resources and facilities, and time for critical innovations [11,26]. This study also provides immense support to work contextual theories such as interaction theory [4], componential theory [5,6], and multiple social domains theory [7]. Thus, our findings support the conceptualization of the firm’s innovative climate as a determinant of organizational learning and innovative behavior. Therefore, this study predicts that the degree to which a firm’s members perceive the firm climate to be innovative would affect organizational learning and innovative behavior.

Sun, Zhao [1] found that firm innovative climate in China includes leader support, vision, resource supply, learning, knowledge, and skill development. The findings of this study show that firm innovative climate → innovative behavior → firm business performance. Moreover, firm innovative climate → organizational learning → innovative behavior →firm business performance. These findings indicate that the firm’s innovative climate encourages organizational learning and innovative behavior, which leads to the firm’s business performance. These findings provide support to organizational climate theory [8,101]. The findings of this study further reveal that firm innovative climate → organizational learning → firm competitiveness, and that firm innovative climate, organizational learning → innovative behavior → firm competitiveness. Thus, this study provides support to the “Asset–Processes–Performance” (APP) model [102]. The findings of this study reflect those of the authors of [103], who suggest that organizational learning and innovative behavior mediate the relationship between the variable of interest and the firm’s competitiveness.

Moreover, the findings of this study, as shown in Figure 2 and Table 7, show that firm size and age moderate the relationship between various pairs of variables given in the structural equation model. This study finds that the firm size significantly moderates the relationship between innovative climate and organizational learning. The plots in Figure 3 suggest that when the firm size increases, the relationship between innovative climate and organizational learning is strengthened. However, we have a negative moderation coefficient; this is because of the effect size, and we found that the effect size of innovative climate on organizational learning is higher in small firms than in medium and large firms. The plots in Figure 4 and the results of model 2 in Table 7 show that firm size moderates the relationship between innovative climate and employees’ innovative behavior; however, the effect size is higher in small firms. Moreover, the moderation plots in Figure 5 and the results of model 3 in Table 7 show that firm age is a significant moderator between the firm’s innovative climate and organizational learning. The plots in Figure 6 and the results of model 4 in Table 7 show that firm age is a significant moderator between organizational learning and the firm’s competitiveness. Thus, this study makes significant theoretical contributions to the existing literature on firm innovative climate, business performance, and competitiveness through the introduction of organizational learning, innovative behavior, and firm size and age.

5.1. Managerial Implications

This research work offers several managerial implications for law firms specifically and for other industries in general. The legal sector is passing through an age of innovative disruption, and clients are demanding innovative services at a low cost [74]. Furthermore, paralegals, artificial intelligence, and management professionals have entered the legal market, which was served only by lawyers in the past. This emerging competition in the legal market is forcing legal firms to introduce structural, technological, alternative fee structure, and business model innovations if they wish to survive. The findings of this research lead us to recommend that leaders/managers/CEOs should develop an innovative climate in law firms to encourage employees to behave innovatively, as well as searching for new knowledge and/or using the firm’s existing knowledge to find creative solutions to problems. For instance, one example would be engaging billing specialists that work directly with clients to resolve e-billing issues (online shopping).

This study proposes that an innovative climate is a key to competitiveness and excellent business performance, where employees feel safe, have the autonomy, trust leaders, share information, and believe in teamwork cohesion. Thus, lawyers and law firms should apply innovative climate system and process-oriented approaches to legal work. Individual lawyers and law firms should identify creative legal tasking, functions, and delivery systems that can be process-mapped to drive efficiency and consistency and reduce risk, whether it be in the negotiation of contracts, supporting immigration services, or reviewing documents for investigation, discovery, or due diligence. This study proposes that law firms should align their human resources policies with the firm’s goals for innovation to perform better than their competitors. This research informs law firms that for developing an innovative work climate, leaders/managers should be trained to be more supportive and encouraging, acting as facilitators and role models, with fair rewards for innovation that motivate employees to think outside the box for innovative solutions.

Law firms should also focus on learning to enhance their employees’ skills and ability to behave innovatively. Thus, for achieving better performance and competitive advantages, law firms should promote innovators and disruptors by creating new teams and roles. These new roles should consist of data scientists, statisticians, artificial intelligence and software developers, and user interface (UI) designers to support innovation. This kind of diverse thinking would bring real change to law firms to help solve client problems. Thus, an innovative climate and organizational learning would be the foundation stones of the incubation, processing, and implementation of new ideas in law firms.

Moreover, law firms should equip their working environment with technologies; this would encourage employees to learn for self-satisfaction and rewards, and to achieve the firm’s goals. Legal technologies would help in designing applications that could assist clients in finding answers to simple legal issues, such as drafting applications. Thus, by making an innovative climate (autonomy, resources, technology) and learning environment (knowledge acquisition, sharing, collaboration), law firms can equip their employees to analyze and synthesize huge data to provide useful advice and solutions to their clients. However, technology should be taken as a good process rather than a solution to the problem; hence, lawyers and law firms should be supported in processing data.

5.2. Implications regarding Firm Size and Age

The moderation effects of firm size and innovative climate on the firm’s learning among Chinese law firms are greater in small firms than in large firms; however, Figure 3 shows that when the level of innovative climate is high, there is organizational learning in large firms. The interpretation of model 1 in Table 7 suggests that small firms are more flexible to change than large firms. Small law firms are more open to new ideas, adoption of legal technologies, alternative fee structures, and innovative business models. However, large firms have more human capital, financial resources, and massive research and development capacity for innovations. Although small firms lack essential resources and know-how to invest in innovation, their structure allows them more independence from institutional bureaucracy and more flexibility. Thus, the findings of this study reveal that organizational learning depends on influence from internal contextual variables such as firm size. It is recommended that large firms should develop a network relationship with small and medium firms (such as paralegals, online law, contract management, legal artificial intelligence, virtual law, and secondment firms) for developing innovative services and processes. This strategy will benefit both ends; the small firms will benefit from the resources, mature knowledge, and market research. In contrast, the large firms, through collaborations, will avoid the challenges of radical organization structure, and after a pre-test of innovations through their partners, can adopt the innovations. Large and mid-size firms should experiment in their firms on how to enhance firm competencies and business performance through the exercise of creating an innovative climate and focusing on inculcating knowledge sharing and innovative behaviors by thinking workshops, internal innovation contests, and redefining their purpose as lawyers.

Firm size also moderates the relationship between innovative climate and innovative behavior. Thus, it is recommended that through collaboration and partnership, small legal firms can get the resources required to implement disruptive ideas in reality. Large law firms should outsource more work in specific areas from small firms who are more willing to disrupt, such as in e-discovery, litigation and investigation support, nonlegal research, document automation, document review and coding, and advance delivery solutions. Managers/leaders in large firms should develop organizational communication and pay more attention to employees’ ideas with respect to make them feel that their creative ideas are worthy to the firm. Small law firms can benefit from large law firms’ expertise. Both large and small firms can collaborate in developing innovative labs, where they can train their associates and be innovative in specific practice areas. Mid-size firms can benefit through collaboration by the top–bottom approach; they can collaborate with large firms for resources and expertise; however, cooperation with small firms will lead them to market disruption. The legal market has become more diverse than ever, where clients are demanding more specific and low price services; thus, it is almost impossible for a single firm to serve each segment of the market. Each firm size has its own expertise and competencies; hence, collaboration and outsourcing between the different firm sizes will lead them to better business performance.

The moderation of firm age shows significant effects on the relationship between innovative climate and organizational learning, as well as on the relationship between organizational learning and competitiveness. Literature trends indicate that mature firms have more knowledge and expertise; however, their traditional organizational structure and status quo often pose a threat for the rejection of new and creative ideas. Thus, it is recommended that mature firms should develop more flexible and innovative business models that offer autonomy and flexibility, and encourage knowledge acquisition and sharing, technological knowledge creation, and adaptability to meet the clients’ demands. Managers in mature firms should devote much time to knowledge acquisition, information sharing, and organizational memory as firm age is positively associated with organizational learning and competitiveness. Mature firms should use their existing available knowledge and expert human resources for radical and long-lasting innovations.

Young and mid-age firms can develop a collaborative network of small and mid-size firms to invest in combined with knowledge creation to enhance their competitiveness, as well as knowledge sharing between the network firms. The merits and deficiencies of different sizes and ages of firm offer opportunities and threats; however, this opens up many areas for cooperation and collaboration between different sizes and ages of law firm. It is recommended that younger, mid-age, and mature firms can develop alliances for knowledge sharing according to their area of expertise. Mature and large-size firms with immense capital and human resources can develop knowledge creation and implementation platforms where they can share their existing expertise and knowledge with young and mid-age firms to develop innovative and cost-effective services and flexible business models. The young and mid-age firms who are more inclined towards an innovative climate and have a better communication infrastructure should play an active role in service design, delivery systems, quality, and the application of different technologies.

5.3. Limitations and Future Research

Like any other investigation, our research also suffers from some limitations that can be addressed in the future. First, the data collection method reflects the views/opinions of a single person. Future research should consider research designs that allow data pooling from multiple respondents within the same firm at the same time. Second, we have used Harman’s single factor technique for common method bias, which has often been criticized, so future research should use more reliable methods. Third, we have used subjective measures for measuring firm performance; hence, it is recommended that scholars could use objective indicators. Fourth, we have used a cross-sectional research design that provides a static picture of the innovative climate affecting organizational learning, innovative behavior, competitiveness, and a firm’s performance. Moreover, this research design makes it challenging to address the issue of how innovative climate as an antecedent and its importance may change over time. Therefore, future researchers are recommended to use a longitudinal research design that could enhance the findings. Fifth, we have used a random sample technique; future research should use snowball sampling or non-random sampling techniques; this will enable us to give equal representation to each firm size. Thus, the results for different firm sizes may be different. Although this study provides theoretical support to various theories as mentioned in the Discussion section, it is recommended that other approaches are used such as person situation theories, attraction-selection-attrition theory, regulatory focus theory, and situational strength theory.