**5. Explanation of latent constructs**

In this section of the chapter, complex hierarchical constructs, sub-constructs, and related subset variables are disentangled and discussed.

#### **5.1 Integrated quality management**

**Table 3** presents the result of an orthogonal (VARIMAX) rotation of the factor matrix underlying the quality management items. Based on the six-independent factor solution suggested by the eigenvalue pattern (i.e., greater than 1.0), 25 items were identified so that each of which loaded at least cleanly on only one of the six factors. A cut-off of 0.50 was used for item-scale selection. These factors accounted for over 78% of the variance in the quality management scale items. Following an inspection of the factor loadings, the six factors were subsequently labeled:


**Table 4** shows an examination of the Kaiser-Meyer Olkin measure of sampling adequacy suggested that the sample was factorable. The results reasonably describe each set of items as being indicative of an underlying factor for quality management.

(KMO = 0.833); χ<sup>2</sup> = 3485, df, 300, sig 0.000).


*a A VARIMAX orthogonal rotation is performed on the initial factor matrix.*

*b Factors derived from quality management.*

*c Loadings above 0.50 are in boldface.*


#### **Table 3.**

*Factor analysis of quality management scales.<sup>a</sup>*

*Exploring the Effects of Learning Capability and Innovation on Quality Management… DOI: http://dx.doi.org/10.5772/intechopen.102503*


#### **Table 4.**

*KMO and Bartlett's test of quality management variable.*

Results of second-order confirmatory factor analysis (**Table 3**) present the scale reliability on quality management dimensions that reached statistical significance. This indicates that criteria had a significant correlation with appropriate dimensions and scales had convergent validity [42].

*Association of the latent constructs and quality management.*

Findings (shown in **Table 5**) also indicated that integrated quality management is positively and significantly associated with human resource development through continuous education and training (*B* = 0.94). Findings also indicted executives' commitment to coordinate and support continuous improvements, post quality management implementation (*B* = 0.73), and employee involvements in implementation decision making (*B* = 0.33). Furthermore, findings indicated that top managers encouraged exploring new ideas and innovation (*B* = 0.70). Results revealed that managers were cognizant about immediate factors in the organization industry environment by managing supplier relationships (*B* = 0.70), focusing on customer relations (*B* = 0.54).

*Analysis of subset variables and their relationship with quality management.*

*Education and training.* Further analysis of the subset variables shows that longterm quality management training programs (*B* = 0.96) and employee know-how about the developments and changes in the industry (*B* = 0.95) as the most important variables. Work conditions and environment (*B* = 0.76) and customer relations (*B* = 0.67) were important factors in the implementation of quality management.

*Top management support.* As shown in **Table 5** top managers strategy, post quality management implementation focuses on continued investment in quality management programs (*B* = 0.91), coalignment of quality management strategies with changes in the industry (*B* = 0.98), and employee involvement in the implementation process (*B* = 0.88).

*Continuous improvements.* Top managers encouraged the employee for both input for new products and existing product improvements (*B* = 0.94), and research and development activities focusing on products and services improvements (*B* = 0.75). Furthermore, employees were encouraged to participate and suggest work environment improvements (*B* = 0.88).

*Managing supplier relations.* Results revealed top managers included supplier relations in their strategic plans for the long term (*B* = 0.86). Such a strategic plan was based on information sharing with the suppliers (*B* = 0.88), and assessment of the supply chain based on the long-term trend in the quality of the services and products the organization received (*B* = 0.86).

*Customer focus.* Top managers' decision-making process prioritized customer expectation (*B* = 0.83), contentedness with the quality of the product (*B* = 0.84), and importance to the organization (*B* = 0.88).

*Employee involvement in decision-making processes.* According to the results, employees were encouraged to form improvement circles and teams (*B* = 0.96) and


*Exploring the Effects of Learning Capability and Innovation on Quality Management… DOI: http://dx.doi.org/10.5772/intechopen.102503*


**Table 5.**

*Results of the first-order and second-order confirmatory factor analysis of integrated quality management.*

provide input about the supplier selection based on the quality of services and products (*B* = 0.96).

#### **5.2 Organizational Learning capability**

Results of an orthogonal (VARIMAX) rotation of the factor matrix (**Table 6**) indicate underlying organizational learning capability items. Based on the fourindependent factor solution suggested by the eigenvalue pattern (i.e., greater than 1.0), 15 items were identified so that each of which loaded at least cleanly on only one of the four factors. A cut-off of 0.50 was used for item-scale selection. These factors accounted for over 75% of the variance in the organizational learning capability scale items. Following an inspection of the factor loadings, four factors were subsequently labeled "management commitment," "system perspectives," "organizational experiment," and "knowledge transfer initiative." After the initial component analysis number of items was reduced to 15 which explained the highest variation in organizational learning.

**Table 7** shows the Kiser-Meyer-Olkin, and Bartlett test of sphericity utilized to measure four organizational learning dimensions, with each of the dimensions being measured by responses to several items. The results reasonably describe each set of items as being indicative of an underlying factor for learning capability (KMO > 0.818; χ<sup>2</sup> = 1843, df, 120, sig 0.000).

Results of second-order confirmatory factor analysis (**Table 6**) present the scale reliability on organizational learning dimensions that reached statistical significance. This indicates that criteria had a significant correlation with dimensions and scales had convergent validity [42].

Furthermore, results (shown in **Table 8**) indicated that organizational learning capability positive and significant relationship with management commitment to long-term investment in human resources development and organizational learning



#### **Table 6.**

*Factor analysis of organizational learning Scales.<sup>a</sup>*


#### **Table 7.**

*KMO and Bartlett's test of organizational learning variable.*

(*B* = 0.88). Moreover, to enhance learning capability at all levels within organizations, top managers promoted a culture of information sharing and knowledge transfer at all levels (*B* = 0.63). Results showed that top managers encouraged individuals and teams to explore new ideas through open experimentation (*B* = 0.80)*.* Findings also indicated that subunits were encouraged to adopt a system perspective notion, as it relates to the understanding of organizational goals and strategic orientation (*B* = 0.72).



#### **Table 8.**

*Results of the first-order and second-order confirmatory factor analysis of organization learning.*

#### *Analysis of subset variables and their relationship with quality management.*

*Management commitment.* Results shown in **Table 8** revealed that investment in human capital through learning programs (*B* = 0.78) will be considered a key success factor in the organization (*B* = 0.77). Furthermore, the analysis indicated that

employees participating in the management decision-making process will be important (*B* = 0.81) and can contribute to decisions on how to adapt to changing industry environment (*B* = 0.73). Management also implemented a program to reward novel ideas by individuals and teams (*B*0.86).

*Knowledge sharing and cross-functional transfer.* Knowledge sharing within a subunit and among various subunits contributes to the generation of new ideas among employees (*B* = 0.83), proper documentation of work processes (*B* = 0.78), creates a culture of teamwork (*B* =0.44), also generates productive discussions about the subunits and top management shortcomings (*B* = 0.82).

*System perspective.* Establishing a system perspective requires a lateral and flexible organizational structure. Results of the data analysis showed that top executives implemented integrated quality management by designing a lateral organizational structure which enabled departments and divisions to participate in the strategic goals setting process of the organization.

(*B* = 0.88). Furthermore, lateral structural design facilitated a more effective communicate cross-functionally to co-align division objects and goals (*B* = 0.94), and from conferences to educate employees about organizational strategic direction (*B* = 0.83).

*Exploration and open experimentation.* According to March [2], organizations engage in exploration to find a new way of doing things, creating products and services. The data analysis in the present research indicated that organizations pursued both internal strategy and external monitoring to explore and experiment with novel ideas. Data analysis showed that the organization created a culture of welcoming and accepting new ideas by employees (*B* = 0.76), also, employee job expansion employees were enabled to explore and experiment with new ideas (*B* = 0.85). Within business environment, results indicated that organizations monitored and adopted best practices (*B* = 0.84) and consulted with experts in the field outside the organization to improve learning capability (*B* = 0.85).

#### **5.3 Organizational innovation**

**Table 9** presents the result of an orthogonal (VARIMAX) rotation of the factor matrix underlying organizational innovation items. Based on the three-independent factor solution suggested by the eigenvalue pattern (i.e., greater than 1.0), 17 items were identified so that each of which loaded at least cleanly on only one of three factors. A cut-off of 0.50 was used for item-scale selection. These factors accounted for over 74% of the variance in the organizational innovation scale items. Following the factor loadings, the three factors were subsequently labeled "product/services initiatives," "product innovation," and "overall organizational innovation."

**Table 10** shows the Kiser-Meyer-Olkin and Bartlett test of sphericity. Results reasonably describe each set of items as being indicative of underlying factors for organizational innovation (KMO > 0.891; χ<sup>2</sup> = 2.418E3, df, 136, Sig, 0.000). Furthermore, results are indicative of a relationship among the innovation components, "product innovation," "process innovation," and "organizational innovation."

**Table 9** shows the results of second-order confirmatory factor analysis and the scale reliability on organizational innovation dimensions that reached statistical significance. This indicates that criteria had a significant correlation with dimensions and that the scales had convergent validity [42]. Results (Shown in **Table 8**) were also indicative of a significant and positive correlation between innovation and the introduction of new products and services (*B* = 0.92). Moreover, top managers allocated resources for


*Exploring the Effects of Learning Capability and Innovation on Quality Management… DOI: http://dx.doi.org/10.5772/intechopen.102503*

*b1PS <sup>0</sup> b2PR <sup>0</sup> b3OOI <sup>0</sup> <sup>c</sup> Loadings above 0.50 are in boldface*

#### **Table 9.**

*Factor analysis of organizational innovation Scales<sup>a</sup> .*


#### **Table 10.**

*KMO and Bartlett's test of innovation variable.*

continuous process innovation (*B* = 0.78). Findings also revealed that top managers coordinated subunits efforts to enhance overall organizational innovations (*B* = 0.77).

*Analysis of subset variables and their relationship with quality management.*

*Products and services innovation.* Results for the subset variables of the innovation dimension (**Table 11**) reveal that executives place strategic importance on the first-


*\**p *< 0.001.*

#### **Table 11.**

*Results of the first-order and second-order confirmatory factor analysis of organization innovation.*

mover advantage and faster generation of new products and services compare to other rivals (*B* = 0.94). Furthermore, the first-mover advantage enabled the organization to present customers with products and services that best served their needs compared to other rivals in the marketplace (*B* = 0.92), at a higher rate of market presentation of *Exploring the Effects of Learning Capability and Innovation on Quality Management… DOI: http://dx.doi.org/10.5772/intechopen.102503*

innovative products compared to other rivals (*B* = 0.79). Results also indicated that as a first-mover strategy, top managers placed strategic emphasis on R&D and allocated greater resources toward research and development (*B* = 0.72). Congruent with results presented in the learning capability segment, flexible and lateral structural design and greater cross-functional communication and knowledge sharing, reduced process costs associated with the higher production improvements and efficiency, compared to other competitors (*B* = 0.82), and generating new products and services for customers (*B* = 0.75).

*Innovation performance.* Findings reveal that designing a lateral flexible organizational structure was highly correlated with innovations in the organization (*B* = 0.89). enabled subunits to transform the novel ideas into products and services and present them to the marketplace in a timely fashion (*B* = 0.88). Moreover, resources are to be allocated and reallocated cross-functionally (*B* = 0.68), with lower costs and more efficiency (*B* = 0.78). Findings also indicated that top managers focused on human resource development and management (*B* = 0.81) and acquire high-quality resources in the production processes (*B* = 0.80).

*Organizational innovation.* The results of the analysis of innovation showed that there are two important aspects of organizational innovation. The financial aspect indicated that innovation leads to a reduction in costs per unit (*B* = 0.84). Moreover, innovation enhances the employee productivity (*B* = 0.79), efficient resources allocation cross-functionally (*B* = 0.77), and prospects of healthier finances (*B* = 0.79).

#### **5.4 Organizational performance**

**Table 12** presents the result of an orthogonal (VARIMAX) rotation of the factor matrix underlying organizational performance items. Based on the four-independent factor solution suggested by the eigenvalue pattern (i.e., greater than 1.0), 16 items were identified so that each of which loaded at least cleanly on only one of four factors. A cut-off of 0.50 was used for item-scale selection. These factors accounted for over 77% of the variance in the organizational performance scale items. Following an inspection of the factor loadings, the four factors were subsequently labeled "customer satisfaction," "employee satisfaction," "environmental performance," and "environmental sustainability."

Kaiser-Meyer-Olkin and Bartlett test of sphericity (shown in **Table 13**) was utilized to measure four organizational performance dimensions, with each of the dimensions being measured by responses to several items. Results (shown in Table E) reasonably describe each set of items as being indicative of an underlying factor for organizational performance (KMO > 0.862; χ<sup>2</sup> = 1.971E3, df, 120, Bartlett's Test of sphericity with significant of 0.000 (less than 0.05).

**Table 12** shows the results of second-order confirmatory factor analysis and the scale reliability on organizational performance dimensions that reached statistical significance. This indicates that criteria had a significant correlation with dimensions and that the scale had convergent validity [42].

Results of path analysis indicated top echelon focus on reduced turnover rate by instituting a high remuneration policy and employee satisfaction (*B* = 0.75). Moreover, the data analysis indicated that customer contentment with products and services was high with little or no defect returns (*B* = 0.59). Findings also indicated that top managers monitored the industry environment and continuously selected best practices (*B* = 0.63). Furthermore, top managers were cognizant of the organization's


*Loadings above 0.50 are in boldface*

#### **Table 12.**

*Factor analysis of organizational performance Scales<sup>a</sup> .*


#### **Table 13.**

*KMO and Bartlett's test of organizational performance variable.*

impact on the environment and negative externalities and pursued a sustainability strategy as a priority post integrated quality management implementation (*B* = 0.93).

*Analysis of subset variables and their relationship with quality management.*

*Human resource management*. Analysis of the subset variables (shown in **Table 14**) revealed that executives place strategic importance on employee retention (*B* = 0.88)


*Exploring the Effects of Learning Capability and Innovation on Quality Management… DOI: http://dx.doi.org/10.5772/intechopen.102503*

#### **Table 14.**

*Results of the first-order and second-order confirmatory factor analysis of organizational performance.*

and reducing absenteeism (*B* = 0.83) by offering employees competitive remunerations (*B* = 0.87), and overall employee satisfaction of their jobs (*B* = 0.86).

*Customer contentment.* Results of data analysis indicated that investment in the introduction of new and high-quality products and services (*B* = 0.80) tend to reduce the rate of defected products (*B* = 0.75), consumer complaints (*B* = 0.89), maintain the market share (*B* = 0.82), and assure consumers are contented with the products and services (*B* = 0.81).

*Monitoring environmental conditions and sustainability strategy.* The analysis outcome also revealed that top executives were cognizant about the company's reputation by maintaining sustainability by considering environmental renewable energy

projects (*B* = 0.74), reducing the negative externalities caused by production pollution (*B* = 0.85). Integrating the sustainability strategy with quality management enhanced the company's legitimacy and reputation for social responsibility by planning for environmentally friendly projects and sustainability (*B* = 0.89).

## **6. Results and discussion**

*Macro model.* As shown in **Table 1** (**Figure 1**), the standard regression weight for the overall model indicated a positive and significant relationship between main variables, quality management, organizational learning, and innovations. According to the results, organizational integrated quality management is positively and significantly associated with organizational learning capability (*B* = 0.95, *p* < 0.05). Similarly, results showed a positive and significant relationship between innovation performance and integrated quality management.

(*B* = 0.91, *p* < 0.05). Results indicated that when parsing the main effects of learning capability and innovation performance, the association between quality management and organizational performance remains positive but statistically nonsignificant (*B* = 0.43, n.s.) and does not explain significant variance (*R*<sup>2</sup> = 0.18) in organizational performance. A detailed analysis revealed that organizational learning capability is positively and significantly associated with organizational performance (*B* = 0.58, *p* < 0.05). Furthermore, innovation performance, according to findings, is also positively and significantly associated with organizational performance (*B* = 0.62, *p* < 0.05). Findings are congruent with hypotheses H1a and H1b. Findings, however, being partially congruent with hypothesis a, H1.

*H1: There will be a positive and significant relationship between quality management, organizational and organizational performance.*

*H1a: There will be a positive relationship between quality management, organizational learning.*

#### *H1b: There will be a positive relationship between quality management, organizational, and innovation.*

A detailed analysis revealed that organizational learning capability is positively and significantly associated with organizational performance (*B* = 0.58, *p* < 0.05). Furthermore, innovation performance, according to findings, is also positively and significantly associated with organizational performance (*B* = 0.62, *p* < 0.05).

Findings also supported hypotheses H2 and H3.

*H2: There will be a positive relationship between organizational learning and organizational performance.*

*H3: There will be a positive relationship between innovation and organizational performance.*

#### **6.1 Interaction effects**

As managers attempt to identify factors that influence organizations' performance, this research argued that it is important to gain a deeper understanding as to how interaction effects of quality management, learning capability, and innovations matter in influencing organizational performance. The hypothesis H4 specified that organizational performance would be affected by an interactive effect of quality management and organizational learning capability. The hypothesis H5 specified that organizational performance would be affected by an interactive effect of quality

*Exploring the Effects of Learning Capability and Innovation on Quality Management… DOI: http://dx.doi.org/10.5772/intechopen.102503*

management and innovation. To test these hypotheses, I employed structural equation modeling analysis to reduce the number of variables and to capture the interrelations of measured variables and latent constructs, as suggested by Tarka [43]. Results indicated that compared to the effects of quality management and organizational performance (*B* = 0.43, n.s., *R*<sup>2</sup> = 0.18), the multiplicative interaction term for quality management and organizational learning capability increased explanatory variance in organizational performance (*R*<sup>2</sup> = 0.34, *<sup>p</sup>* <sup>&</sup>lt; 0.05), significantly (0.95 0.58) = (0.55, *p* < 0.05). Similarly, the multiplicative term between quality management and increased the variance (*R*<sup>2</sup> = 0.38, *<sup>p</sup>* <sup>&</sup>lt; 0.05) significantly (0.91 0.62) = (0.56, *P* < 0.05). Results of the analysis were congruent with H4 and H5.

*H4: The interactions between quality management and organizational learning positively influence the relationship between quality management and organizational performance.*

*H5: The interactions between quality management and innovation positively influence the relationship between quality management and organizational performance.*

#### **7. Discussion**

There are several important theoretical and practical implications that emerge from this research. Findings underscore the importance of the interaction of quality management elements. Over the past decade, researchers have systematically underplayed the interaction effects of quality management elements. The present research showed that the dominant impact on organizational performance, beyond external resource considerations, is the intersection of forces associated with quality management, organizational learning capability, and innovations within these organizations. It was argued earlier that within quality management theory and methodology, the need to consider the contingency approach might result in an in-depth understanding of the strategic allocation of resources and managing and coordinating among the interrelated constituent elements within quality management. Results suggested that organizational performance is positively influenced by the interaction of quality management and innovation and learning capability at organizational levels. It is also clear that there are distinct differences between parsed and integrated constituents within quality management with respect to explaining variations in organizational performance. This finding is of some theoretical significance.

As a strategy, quality management appears to have coordination challenges associated with learning capability and application of such learning to innovations of new products and services. This study found that organizational performance is significantly impacted by the interaction between quality management and learning capability. Similarly, findings indicated that interaction between innovation and quality management positively and significantly influences organizational performance. The strength of these findings, particularly in light of incorporating external environmental factors such as sustainability considerations, points to the potential importance of revitalizing the contingency theory perspective pertaining to integrated quality management. Such a revival would not necessarily imply that researchers "pit" internal elements influencing performance against external forces. Instead, more direct integration of contingency variables within quality management is suggested to better balance internal and external perspectives on organizational performance.

Nevertheless, any resurrection of this perspective within quality management theory and methodology may require changes in how contingency theory may be employed (e.g., Pfeffer 1997). This study did not limit its focus to examining the main effects of organizational learning capability, innovations, and quality management on performance. As I argued in theoretical development, one cannot easily specify the nature of these main effects. Instead, what may be as, if not more, important to consider is the interaction of these variables as previous organizational researchers have argued that internal and external characteristics of organizations and their members may cluster together in predictable patterns to explain a variety of micro to macro-level organizational processes and relationships [44]. Congruent with Meyer et al.'s findings on organizational learning capability showed top managerial commitment to implement a complex set of policies on the development of human resources. Such policies included learning based on system perspectives, learning associated with experimentation and exploration of a novel way of doing things, and knowledge transfer at various levels of individuals, teams, and organizational subunits. Furthermore, findings revealed managerial efforts to coordinate and co-align subunits'strategies with the organization at the macro level. Similarly, findings on innovations showed managerial commitment to implementing flexible resource allocation strategies for subunits to explore novel processes and ideas. Findings were congruent with the notion that integrating interrelated constituents of quality management at the micro and macro level require greater structural flexibility and high levels of coordination among organizational activities. While the explicit consideration of interactive variables in quality management theory adds complexity to the understanding and application of contingency theory, this type of complexity is what managers must face. Rarely, is there the luxury of focusing exclusively on one aspect of quality management, as has been the themes of previous research, in isolation from others? For the contingency theory to develop as a theoretical perspective and be relevant to the practical concerns of managers and executives, researchers may need to provide further attention to how constructs in quality management and their subset variables interact to influence organizational performance over time.

Employing contingency theory to conduct future research in the quality management field will also require making more direct connections between the results of studies and the organizational design concerns of managers. One important vehicle for doing this is by considering how quality management research findings can be connected to process considerations at various levels of organization. It is often organizational processes that are of most direct concern to managers adopting quality management practice. Perhaps, the most direct implication relates to the enhanced importance of managing and integrating complex processes within and between each constituent of quality management.

Therefore, it is critical for an organization adopting quality management to develop an organizational capability or competence for managing internal complex and interrelated process models. Without this capability, managerial policies and efforts can become misguided and create greater conflict, thereby undermining the effectiveness of coordination efforts among complex processes to achieve timely policy and strategy adjustments. Successful corporations such as Boeing and car manufacturers recognized the need to employ quality management and, as the corporation evolves, developed organizational capabilities to manage complex processes.

Future researchers may wish to create a matrix that examines the contingent effects of long-term variations in learning capability on innovations and assess variations in long-term innovations on organizational performance.

*Exploring the Effects of Learning Capability and Innovation on Quality Management… DOI: http://dx.doi.org/10.5772/intechopen.102503*
