Abstract
Purpose
The purpose of this paper is to examine the links between organizational culture, innovation and banks’ performance in Palestine.
Design/methodology/approach
Data were gathered from 186 employees working in the Palestinian banking sector. The data gathered were analyzed using the PLS-SEM approach.
Findings
The findings of the study show that organizational culture and marketing innovation have a positive impact on banks’ performance. Moreover, it was found that marketing performance partially mediates the relationship between organizational culture and banks’ performance.
Practical implications
The paper may be of use for banks managers to create an organizational culture, which fosters both innovation and performance.
Originality/value
The paper is unique as it examines organizational culture, innovation and performance links in a non-western context.
Keywords
Citation
Aboramadan, M., Albashiti, B., Alharazin, H. and Zaidoune, S. (2020), "Organizational culture, innovation and performance: a study from a non-western context", Journal of Management Development, Vol. 39 No. 4, pp. 437-451. https://doi.org/10.1108/JMD-06-2019-0253
Publisher
:Emerald Publishing Limited
Copyright © 2020, Mohammed Aboramadan, Belal Albashiti, Hatem Alharazin and Souhaila Zaidoune
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
Nowadays, organizations need to operate in business environments, which are characterized by fast technological changes, intensive international competition and continuous changing client’s preferences (Droge et al., 2008). Given these complexities, innovation is seen as one of the critical factors for achieving organizational success and sustaining competitive advantage (Damanpour and Gopalakrishnan, 2001). It is well documented in the literature that innovative organizations have more flexibility and can respond quickly to changes, in order to take advantage of business opportunities (Drucker, 1985). Innovation is considered as a competitive mechanism for organizations’ performance and success, and is regarded as an important instrument to adapt to a continuously changing business environment (Blackwell, 2006). Furthermore, previous studies provide evidence that innovation can positively affect performance (e.g. Baker and Sinkula, 2002; Damanpour and Gopalakrishnan, 2001; Luk et al., 2008; Naranjo-Valencia et al., 2016; Uzkurt et al., 2013).
Because of the critical role innovation plays in different organizational settings, several scholars have attempted to determine the factors that are associated with influencing innovation (Koc and Ceylan, 2007). One of the factors that seems to have an impact on innovation is the organizational culture (Büschgens et al., 2013; Lin et al., 2013; Martins and Terblanche, 2003; Tushman and O’Reilly, 1997).
On the other hand, organizational culture has been studied in terms of definitions, theoretical scopes, conceptualizations, characteristics and types (e.g. Lavine, 2014; Schein, 1996). Although organizational culture was argued to contribute to achieving common values promotion (Naranjo-Valencia et al., 2016), competitive advantage (Calciolari et al., 2018) desirables employees’ behaviors (Nazarian et al., 2017; Zhang and Li, 2016) and innovation (Lin et al., 2013), empirical support is still limited (Hartnell et al., 2011; Kim and Chang, 2019).
Regardless of the important role organizational culture plays in promoting innovation, most of the studies were carried out in western contexts. Moreover, a very limited number of studies examined the association between organizational culture and performance through the intervening mechanisms such as innovation (e.g. Martins and Terblanche, 2003; Naranjo-Valencia et al., 2016; Uzkurt et al., 2013).
Our study contributes to the literature in several ways. First, we attempt to investigate the “black box” of the organizational culture-performance relationship through the mediating effects of marketing and technology innovation. Based on a critical review of previous empirical studies, very limited research (e.g. Naranjo-Valencia et al., 2016; Tseng et al., 2008; Uzkurt et al., 2013) examined the role of innovation as a mediator between organizational culture and performance. Second, our study responds to the different scholarly calls to advance empirical research on innovation and organizational culture (McLaughlin et al., 2008; Nakata and DiBenedetto, 2012; Tellis et al., 2009). Finally, most of the studies examining organizational culture and performance were carried out in western setting. For instance, Budhwar et al. (2019) suggested that there is a need to enrich the literature of HRM and organizational behavior research in the Middle Eastern region. Among the suggestions made by Budhwar et al. (2019) was to investigate the mechanisms which govern the relationship between OB, HR factors and organizational performance. Given this discussion and to respond the scholarly calls to advance the organizational behavior and HR research in the Middle East, our study aims at investigating the relationship between organizational culture and banks performance via the mediating role of innovation. Moreover, we argue that more studies are needed in diverse non-western settings, in order to better understand the relationship between organizational culture and performance.
Theory and hypotheses
Organizational culture, definitions and models
Chang and Lin (2007) consider culture as one of the vital factors for organizations and their activities. In literature, many definitions were given to organizational culture, each from a different perspective. Overall, organizational culture commonly represents the routine activities taking place in an organization (Lundy and Cowling, 1996). More specifically, it refers to the shared set of values and behaviors inside an organization (Deshpande and Webster, 1989). It is also used to describe the set of assumptions and behaviors employees within an organization have adopted (Martins and Terblanche, 2003). Many researchers were interested in the field of organizational culture assuming it is a driving factor to the organization’s innovation, productivity and financial performance (Blackwell, 2006).
Many studies were conducted to determine the different categories of organizational culture (Blackwell, 2006; Martins and Terblanche, 2003). Some of them have considered that organizational culture can be divided into four categories, namely, clan, hierarchy, adhocracy and market (Cameron and Freeman, 1991; Deshpande et al., 1993; Quinn, 1988). Quinn and Spreitzer (1991) have suggested that organizational culture is composed of four different cultures: development culture, group culture, rational culture and hierarchal culture. Similarly, Chang and Lin (2007) believe that organizational culture follows the four concepts of: innovativeness, cooperativeness, effectiveness and consistency. In addition, Wallach (1983) suggested a simpler classification of the organizational culture following its functions: bureaucratic, innovative and supportive perspectives. A further classification for the culture was presented in the organizational culture profile suggesting that it is related to seven main values: innovation, aggressiveness, result orientation, stability, people orientation, team oriented and a detail focus culture. The organization’s culture can be also classified according to being a: service culture organization that focuses on providing the highest value to its customers, or a safety culture that focuses on having strong work-place standards, or both (O’Reilly III et al., 1991). Moreover, according to Robbins (2001), characteristics like leadership, risk aversion, amount of detail, result focus, people focus, team focus, hostility and stability are the main characteristics of organizational culture.
Organizational culture and performance
In the literature, several studies were interested in analyzing the association between organizational culture and organizations’ performance (Chan et al., 2004; Glisson, 2007; Lau and Ngo, 1996; Ngo and Loi, 2008; Wilderom et al., 2000). Most of the previous empirical studies have found an existing relationship between performance and culture (e.g. Daft, 2007; Denison and Mishra, 1995; Fey and Denison, 2003; Gordon and DiTomaso, 1992; Kotter and Heskett, 1992; Ngo and Loi, 2008) and that culture has a direct influence on performance, because it affects the conduct of the people (Galves and Garcia, 2011; Hofstede, 1988; Martins and Terblanche, 2003). For instance, Kim and Chang (2019) found that adhocracy, clan and market cultures are positively associated with performance. Salimi and Aveh (2016) found that culture predicts performance in the Irani context, while Kraśnicka et al. (2018) found a positive relationship between organizational culture and enterprise performance in polish firms. This suggests enough evidence to relate culture to performance (Chan et al., 2004) and that it is a significant predictor of market related performance (Ngo and Loi, 2008). In addition, organizational culture might be seen as a source for competitive advantage for the company, especially since it is hard to copy (Coyne, 1986). Furthermore, Denison and Mishra (1995) developed a model that presents four traits (“involvement, adaptability, mission and consistency”) that are in fact positively linked to a set of subjective measures including: “quality, satisfaction of employee, and the performance of the organization.” Based on the previous discussion we posit the following hypothesis:
Organizational culture has a significant impact on banks’ performance.
Innovation
Innovation, on the other hand, is used to refer to new products, services, processes or technologies that require acceptance and eventually adoption and implementation (Damanpour, 1991; Thompson, 1965; Zaltman et al., 1973). Innovation is the factor that enables the innovative processes to produce new products and services, new technologies and new concepts (Sutanto, 2017).
According to Padilla-Meléndez and Garrido-Moreno (2012), knowledge of innovation needs more communication, and interaction between not only researchers, but also stakeholders affected by this, as well as, leaders. This way new ideas, processes and interactions can have an economic and commercial benefit. Hence, leaders, managers and researchers in organizations and universities should be aware of the different ways of innovation.
Innovation, in the literature, can be divided into different types. The most popular typology of innovation divides it into three types: “administrative vs technical,” “product vs process” and “radical vs incremental” (Gopalakrishnan and Damanpour, 1997). Another classification of the typologies of innovation was developed by Jensen et al. (2007). According to this classification, innovation can be classified as: “Science, Technology and Innovation” (STI) that is based on analytical knowledge and “Doing, Using, and Interaction” that is subject to knowledge retrieved from the engineering field (Coenen and Asheim, 2006; Lorenz and Lundvall, 2006). Innovation can be divided into three groups: product-related, technology-related and behavior-related perspectives. The technology-related innovation is related to the readiness to adopt current technologies and processes and the tendency of the organization to adopt new technologies and processes internally (Kitchell, 1995). Behavior-related innovation relates to the speed, at which the organizational system is ready to adopt new ideas relative to competitors (Rogers, 1995). Lastly, product-related innovation is about the ability of an organization to generate new ideas, products, services and processes, or to buy them (Stalk et al., 1992). Moreover, as innovation is responsible for implementing totally new or ameliorated versions of products, services or processes within the organization, or in the external relations (OECD and EUROSTAT, 2005), innovation can be classified into four categories. First, product innovation, which refers to the radical changes or ameliorations done to products and services. Second, process innovation, which refers to the major changes done to the production system or to the delivery mode. Third, organizational innovation, which refers to the adoption of new business processes that affect the business process within the organization and or on external relations. And fourth, marketing innovation, which refers to any change made to one of the four marketing Ps (product, price, placement and position) (OECD and EUROSTAT, 2005).
Organizational culture and innovation
As innovation plays a significant role in determining an organization’s success, several studies attempted to examine its antecedences (Crossan and Apaydin, 2010). Different studies found that organizational culture and organizational design are the most influential determinants (Mumford, 2000).
Organizational culture can affect the innovative attitude in two ways. The socialization process teaches individuals how to behave and act toward one another. Moreover, the organization’s structure, policy system, procedure and management orientation can be affected by the basic “values, beliefs and assumptions” (Martins and Terblanche, 2003). Hence, culture can encourage innovation among employees, because it drives them toward accepting innovation as a philosophy of the organization (Hartmann, 2006). Different values of culture were regarded as means to foster innovation. Examples of these cultural values were creativity and initiative (Jamrog et al., 2006), entrepreneurial mindset (McLean, 2005), freedom and autonomy (Ahmed, 1998), risk taking (Wallach, 1983), teamwork (Arad et al., 1997), marketing orientation and flexibility (Martins and Terblanche, 2003).
Research has given enough evidence for an existing relationship between organizational culture and innovation (Büschgens et al., 2013; Chang and Lee, 2007; Lau and Ngo, 2004; Lin et al., 2013; Miron et al., 2004; Naranjo-Valencia et al., 2016; Rezaei et al., 2018; Tseng et al., 2008; Uzkurt et al., 2013). Given this discussion, we can posit the following two hypotheses:
Organizational culture has a significant impact on marketing innovation.
Organizational culture has a significant impact on technology innovation.
Innovation and performance
Research has found that innovation plays a significant role in organization performance (Higgins, 1995; Hult et al., 2004). Organizations able to innovate are more capable to deliver new products and services, improve processes in a faster way to fit the market’s needs and capitalize on opportunities better than non-innovative organizations (Jiménez-Jiménez et al., 2008). Moreover, innovation has been associated with higher levels of growth and profitability (Li and Atuahene-Gima, 2001).
In the literature, several studies have been conducted to confirm the positive relationship between innovation and performance (Afcha, 2011; Artz et al., 2010; Baker and Sinkula, 2002; Chen et al., 2009; Damanpour, 1991; Damanpour and Gopalakrishnan, 2001; De Clercq et al., 2011; Droge et al., 2008; Eisingerich et al., 2009; Farley et al., 2008; Gálvez and García, 2012; Jimenez-Jimenez and Sanz-Valle, 2011; Luk et al., 2008; Prajogo, 2006; Roberts and Amit, 2003; Rosenbusch et al., 2011; Subramanian and Nilakanta, 1996; Tseng et al., 2008). Therefore, the following two hypotheses can be posited:
Marketing innovation has a significant impact on banks performance.
Technology innovation has a significant impact on banks performance.
Methods
The present study is a quantitative study applied to the Palestinian banking sector with the purpose of examining the hypothesized positive relationships between organizational culture, marketing innovation, technological innovation and banks’ performance. Data were gathered using a self-administered questionnaire distributed to the employees of banking sector located in Gaza strip. The distribution and collection method were the drop-off and pick up approach. A total of 320 employees were invited to fill the questionnaire. A total of 186 filled and usable questionnaires were gathered and valid for statistical analysis. The response rate in our study is 58 percent.
Respondents’ profile
Most of the respondents were male (70 percent). In total, 25.8 percent of the respondents were aged higher than 44 years, 25.8 percent were aged less than 30 years, 38.7 percent were aged from 30 to 38 years and 9.7 percent were aged from 38 to 44 years. Regarding experience, 32.3 percent had 5–10 years of experience, 16.1 percent had 10–15 years of experience, 22.6 percent had an experience of more than 15 years and 29 percent had less than 5 years of experience. Concerning education, most of the respondents had a bachelor’s degree (87.1 percent).
Measures
Organizational culture
This scale is measured using 22 items adopted from previous studies, such as Claver et al. (1998), Denison and Mishra (1995), Jamrog et al. (2006), McLean (2005) and Wallach (1983). These items were “teamwork, communication, openness, work autonomy, commitment, employee’s involvement, flexibility, creativity, responsibility, objective orientation, customer focus, continuous learning, risk taking, adaptability, entrepreneurial mindset, performance incentives, excitement, work engagement, decision making, marketing orientation, and high standards and values.” The internal consistency was 0.956. A five-point Likert scale was used to assess the items of this construct.
Marketing and technology innovation
Marketing innovation and technological innovation were measured by a three-item scale for each. Both scales were adopted from Hogan et al. (2011). A sample item for marketing innovation is “Our bank develops, revolutionary for the industry, marketing programs for our services/products” and a sample item for technology innovation is “Our bank adopts the latest technology in the industry.” The values of international consistency for marketing and technological innovation were 0.848 and 0.765, respectively. A five-point Likert scale was used to assess the items of these two constructs.
Banks’ performance
Respondents assessed this measure using a seven-item scale adopted from Agbényiga (2011). Examples of this self-reported assessment were “effective services, customer satisfaction, organizational reputation, quality of the service.” The internal consistency value was 0.921. A five-point Likert scale was used to assess the items of this construct.
Initial analysis
Table I shows correlations and descriptive statistics of the research variables. The means and SDs for the examined variables were (Mean: 4.15, SD: 0.55) for organizational culture, (Mean: 4.44, SD: 0.48) for marketing innovation, (Mean: 4.56, SD: 0.45) for technology innovation, and (Mean: 4.30, SD: 0.60) for banks’ performance. According to the results, correlations were significant between marketing innovation, organizational culture and performance.
Assessing the measurement model
For the purpose of checking the internal consistency of the items, factor loading was calculated for each variable. Three items of organizational culture were removed from the model due to their low loading. All other items loadings were retained as their factor loading was higher than 0.5 as presented in Figure 1. Furthermore, we have checked for the variables’ reliability by calculating the average variance extracted and composite reliability (Hulland, 1999). As presented in Table II, AVE values for all variables were higher than 0.5 and CR values were higher than 0.7 (Hulland, 1999). Hence, all variables in the model can be regarded as internally reliable and consistent.
For the purpose of examining discriminant validity, two approaches were utilized. First, the heterotrait–monotrait (HTMT) method was used, in which the results (Table III) show that HTMT values are lower than the value of 0.90, as suggested by Henseler et al. (2015). The second method was the Fornell and Larcker (1981) technique by estimating the square root of the AVE and comparing it with the correlations between latent variables. The results in Table IV show that all square roots of the AVE are higher than the correlations between the examined variables. Hence, the discriminant validity condition was met.
Assessing the structural model
Table V shows that the R2 values for banks’ performance and marketing innovation exceed the acceptable moderate ratio as suggested by Chin (1998). Banks performance has an R2 value of 0.561, marketing innovation an R2 value of 0.112. Technological innovation had a week value of R2 of 0.055. On the other hand, the effect size f² for the research variables was also calculated. Results of f² values presented in Table VI showed medium effects for the following relationships: organizational culture on performance, organizational culture on marketing innovation and marketing innovation on performance. On the contrary, the effect was week for the technological innovation and performance link.
Testing the hypotheses: direct and mediating effects
For the purpose of testing the research hypotheses H1–H5, we have calculated the direct effects. Table VII shows all the hypotheses were supported expect for H5. Organizational culture is positively related to banks’ performance (β=0.596, p=0.000). Organizational culture is positively related to both marketing innovation (β=0.334, p=0.000) and technology innovation and (β=0.234, p=0.000). Marketing innovation was found to exert a positive effect on performance (β=0.297, p=0.000). The relationship between technology innovation and performance was not significant (β =−0.001, p=0.982).
For the purpose of testing the mediating effects of both marketing and technology innovation, we have calculated the indirect effects. The results show that marketing innovation mediates the relationship between organizational culture and banks performance (P=0.007, t=2.698***). Technology innovation did not exert a significant mediating effect between organizational culture and performance.
Discussion and implications
The purpose of our study was to examine the links between organizational culture, innovation and banks’ performance in a non-western context (Palestinian context). The findings of our study provide evidence for the relationship between organizational culture and banks performance, supporting H1. The results of our study are in line with previous studies demonstrating a positive relationship between organizational culture and performance (e.g. Daft, 2007; Fey and Denison, 2003; Kim and Chang, 2019; Kraśnicka et al., 2018; Ngo and Loi, 2008; Salimi and Aveh, 2016). The results imply that the values and philosophy adopted within Palestinian banks contribute positively to the banks performance.
Concerning the relationship between organizational culture and innovation, our results show that organizational culture is a significant predictor of both marketing and technology innovation at Palestinian banks, lending a support for H2 and H3. The results are consistent with previous studies, which investigate organizational culture-innovation links (Büschgens et al., 2013; Chang and Lee, 2007; Lau and Ngo, 2004; Lin et al., 2013; Miron et al., 2004; Naranjo-Valencia et al., 2016; Rezaei et al., 2018; Tseng et al., 2008; Uzkurt et al., 2013). The results imply that organizational culture fosters both marketing and technology innovation.
Although our results provide empirical evidence on the links between marketing innovation and banks’ performance (H4) and are in line with previous empirical support (Afcha, 2011; Artz et al., 2010; Baker and Sinkula, 2002; Damanpour, 1991; Farley et al., 2008; Luk et al., 2008; Tseng et al., 2008), technology innovation did not exert any significant effect on banks performance, lending no support for H5. These results can be justified by the fact that in a developing country like Palestine, technology-related innovation might not attract customers, due to the lack of culture and trust in using different technologies (ATM machines, online banking, etc.). This means that innovating at the technological level does not necessarily contribute to higher performance in the Palestinian banking sector.
Finally, our results show that marketing innovation plays an intervening role in the relationship between organizational culture and banks performance. Marketing innovation partially mediates this relationship, suggesting that organizational culture affects marketing innovation and marketing innovation, in turn, generates higher performance.
Implications
Our results contribute both to the theory and practice. Theoretically, the study is one of the very few studies conducted in a non-western context in the banking sector. In Middle Eastern region and specifically in Palestine, there is a lack of research on the culture-innovation-performance relationships.
Practically, our results provide useful recommendations to banks’ senior management on the significance of organizational culture and innovation and their contribution to performance. Our findings provide fertile grounds for the banking sector in Palestine on the importance of organizational culture as a tool for encouraging innovation and banks performance. The presence of a strong culture that is characterized by teamwork, communication, openness, work autonomy, commitment, employee’s involvement, flexibility, creativity, responsibility, etc., will positively contribute to innovation and firm performance alike. The existence of a climate that is characterized by objective orientation, customer focus, continuous learning, risk taking, adaptability, entrepreneurial mindset, performance incentives, excitement, work engagement, decision making, marketing orientation, and high standards and values, is of extreme importance to the firm success at different levels. Moreover, the results provide insights to the banking sector which is striving to be responsive to challenging environments through successfully adopting innovation.
The Palestinian banking sector encountered several environmental complexities in the last years, hence, innovation can be very useful in order to sustain competitive advantage. Managers in Palestinian banks should encourage their staff members to create innovative ideas and provide them the right reward to establish an innovative culture in the organization. Furthermore, communication between banks’ employees at the horizontal and vertical level can be very beneficial to find the best ways to implement innovation at different levels.
Limitations and future research
Like any other study, our study has some limitations. First, marketing innovation, technology innovation and banks’ performance were assessed by subjective measures. Future research might consider using more objective measures of innovation. Second, data were collected only from the Palestinian banking sector and this might restrict the generalizability of the results to other sectors. Hence, future research might replicate and extend this study to other sectors in Palestine and similar national contexts in the region such as Jordan and Lebanon. Future research using larger data and across different sectors will give more insights on the association between organizational culture and performance through innovation. Third, our research design does not allow the researchers to establish cause and effect links between the examined variables, hence, longitudinal research is recommended for future devours. In general, organizational culture research conducted using only quantities techniques provide restricted understanding. Hence, future studies might consider using qualitative methods to provide better explanation of the organizational culture, innovation and performance associations. Finally, our research analyzed only the role of marketing and technology innovation in the banking sector. Future studies might consider examining the role of other forms of innovation. Finally, it would be also interesting for future studies to investigate the different types of organizational culture and their impact on innovation and performance in the Middle Eastern region.
Figures
Means, standard deviation and correlation matrix
| Mean | SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 | |
|---|---|---|---|---|---|---|---|---|---|
| Age | 2.35 | 1.13 | 1 | ||||||
| Experience | 2.32 | 1.12 | 0.782** | 1 | |||||
| Education | 2.06 | 0.35 | 0.105 | −0.053 | 1 | ||||
| Organizational culture | 4.15 | 0.55 | −0.079 | −0.052 | 0.106 | 1 | |||
| Marketing innovation | 4.44 | 0.48 | 0.029 | 0.095 | 0.212** | 0.278** | 1 | ||
| Technology innovation | 4.56 | 0.45 | 0.033 | 0.090 | 0.111 | 0.141 | 0.597** | 1 | |
| Performance | 4.30 | 0.60 | −0.010 | 0.135 | 0.297** | 0.634** | 0.485** | 0.233** | 1 |
Note: **Correlation is significant at the 0.01 level (two-tailed)
AVEs and CRs for the research variables
| Composite reliability | Average variance extracted (AVE) | |
|---|---|---|
| Organizational Culture | 0.960 | 0.559 |
| Marketing innovation | 0.907 | 0.765 |
| Technology innovation | 0.854 | 0.669 |
| Performance | 0.936 | 0.677 |
Heterotrait–monotrait ratio for the research variables
| Marketing innovation | Organizational culture | Performance | Technology innovation | |
|---|---|---|---|---|
| Marketing innovation | ||||
| Organizational culture | 0.325 | |||
| Performance | 0.543 | 0.671 | ||
| Technology innovation | 0.724 | 0.278 | 0.305 | |
Fornell–Larcker criterion for the research variables
| Marketing innovation | Organizational culture | Performance | Technology innovation | |
|---|---|---|---|---|
| Marketing innovation | 0.875 | |||
| Organizational culture | 0.334 | 0.748 | ||
| Performance | 0.496 | 0.695 | 0.823 | |
| Technology innovation | 0.523 | 0.234 | 0.294 | 0.818 |
R2 values
| R2 | R2 adjusted | |
|---|---|---|
| Marketing innovation | 0.112 | 0.107 |
| Performance | 0.561 | 0.554 |
| Technology innovation | 0.055 | 0.050 |
f2 values
| Marketing innovation | Organizational culture | Performance | Technology innovation | |
|---|---|---|---|---|
| Marketing innovation | 0.136 | |||
| Organizational culture | 0.126 | 0.715 | 0.058 | |
| Performance | ||||
| Technology innovation | 0.011 |
Direct and mediating effects analysis
| Path coefficient | T-statistics | p-values | ||
|---|---|---|---|---|
| Direct effects | ||||
| Organizational culture → performance | 0.596 | 9.943 | 0.000 | Supported |
| Organizational culture → marketing innovation | 0.334 | 4.738 | 0.000 | Supported |
| Organizational culture → technology innovation | 0.234 | 3.621 | 0.000 | Supported |
| Marketing innovation → performance | 0.297 | 4.463 | 0.000 | Supported |
| Technology innovation → performance | −0.001 | 0.023 | 0.982 | Non-supported |
| Mediating effects | ||||
| Organizational culture → marketing innovation → performance | 0.099 | 2.698 | 0.007 | Partial mediation |
| Organizational culture → technology innovation → performance | 0.000 | 0.021 | 0.983 | No mediation |
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