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1 Innovative Culture and Total Quality Management as a Tool for Sustainable Competitiveness: A Case Study of Turkish Fruit and Vegetable Processing Industry SMEs, Sedef Akgüngör Hatice Camgöz Akdağ Aslı Tuncay Abstract: The paper aims to explore the dimensions of quality management practices as a tool for innovativeness and determine the which dimensions of the quality management practices best differentiates the firms with low innovative culture from the firms with high innovative culture. A mail survey with a sample of processed fruit and vegetable product exporters in Turkey was conducted using a structured questionnaire. Factor analysis is used to reduce the total quality management practices into a smaller set of dimensions. The resulting dimensions (factors) were used as independent variables for discriminant analysis. Discriminant analysis follows from the findings of previous research in which two independent firm clusters were identified through cluster analysis using quality management variables. Following the cluster definitions of the previous research, the dependent variable of the discriminant function measures whether the firm is characterized by low innovativeness or high innovativeness. Factor analysis reduced quality management practices into 6 factors. The quality management dimension that best discriminates the two groups is standardication of work. Presence or absence of ISO certificate did not reveal much power to differentiate the two groups.

2 . Introduction Competitiveness of a firm in today's rapidly changing business environment depends on its capacity to innovate. To maintain competitive advantage and to sustain ongoing business improvement, the firm has to take action to implement a company wide process of continuous innovation. Corporate culture as an aspect of the software of the organization is an important determinant of quality and productivity improvement. Firms whose shared values are represented by innovative culture have increased probability of long run success and business excellence. Total quality management (TQM) is a management philosophy in which predetermined consumer needs and wants are met through improvements in the work processes. This philosophy covers not only the product or services, but the production process as a whole, including workers at all levels and contributes to the creation of an innovative culture within the firm. The concept of total quality and innovation has a common objective of delighting customers with continuous improvement. Previous research have demonstrated that as the firms become more focused on the market, emphasise on learning and development, practice participative decision making, emphasise collaboration between the departments, share power, establish communicative links within the departments and have greater tolerance for risk are more innovative and thus have higher capacities to innovate (Deshpande and Webster, 99; Hurley and Hult, 99). Total quality management includes an essential whole array of techniques, management principles, technologies and methodologies which are put together for the benefit of the end customer. It can be said that innovativeness plays an important role in quality. If the term TQM is replaced with continuous improvement, it will be easier to understand the strong relationship between quality and innovativeness. For a company to improve continuously it has to continuously innovate in order to be able to compete in the rapidly changing global market. And this innovation will only succeed if the quality practices, techniques, and

3 methodologies are used efficiently and effectively. So, it is clear that quality culture and innovative culture overlap with each other as the goal of both terminologies are the same which, is to gain a sustainable competitive advantage in the rapidly changing environment. Given that quality management practices and innovative culture are overlapping concepts, the paper aims to answer the following questions:. Do innovative culture lead to higher innovative capacities?. Which quality management practices determine the firm's innovativeness? 3. Which quality management practices best distinguish the firms with high degree of innovativeness and firms with low degree of innovativeness?.analysis Method The analysis follows from the findings of previous research in which two firm clusters were identified through cluster analysis using the cultural variables that measure the degree to which the firm employs quality management practices (Akgüngör, Barbaros and Kumral, ). The variables that measure the firms' quality management practices are presented in Table. Quality management practices were operational zed by using an instrument developed by Burke to measure the people's perceptions of group culture (Hurley and Hult, 99). All measures used a five point scale ranging from =strongly agree; = agree; 3=neither agree nor disagree; 4=disagree; 5=strongly disagree. Following the assumption that quality management practices and innovative culture (innovativeness) are overlapping concepts, we were able to divide the sample of firms into two clusters using the quality management variables. Cluster analysis of firms' quality management practices led us to divide the sample of firms into two independent clusters. Cluster represents firms with low degree of innovativeness ( firms) and cluster represents firms with high degree of innovativeness (49 firms) (for details of the analysis, see, Akgüngör, Barbaros and Kumral, ). Innovative capacities of the firms were measured by the firms' innovative activities during the last three years. Innovative capacities defined as in organizational outcome relate to the implementation of innovations. Following 3

4 Hurley, capacity to innovate was operationalized as the number of new ideas that had been adapted by the organization and focuses on technical innovation. Within such context, the innovative capacities of the sample of firms were operationalized by variables that measure the presence or absence or activities such as, introduction of a new product, renewing the production technique, merging or acquisition, make a major investment, initiate exporting. To determine whether a systematic association exists between innovativeness (a cultural variable) and innovative capacity (an outcome variable), we test the statistical significance of the observed association in a cross tabulation if innovativeness and innovative culture. Discriminant analysis is used to determine the quality management practices that help differentiate between the two firm clusters: cluster : firms with low degree of innovativeness; cluster : firms with high degree of innovativeness. The categorical dependent variable of the discriminant analysis measures the classification of the firm based on cluster analysis using the cultural variables presented in Table. To find out which quality management practices help to distinguish between the two firm clusters, the same variables are used as independent variables in the discriminant analysis. 4

5 To overcome a possible multicollinearity in estimating the discriminant scores, the number of cultural variables was reduced using factor analysis. The resulting factors represent various dimensions of the firm's quality management practices, such as communication, formalization and teamwork. The subsequent quality management practices that are identified by factor analysis were used as independent variables in discriminant analysis. 3. Data The data is based on a mail survey of processed fruit and vegetable exporters in Turkey. Three subgroups of products with highest shares in Turkey's total fruit and vegetable exports are selected (for distribution or fruit and vegetable exports according to product groups, see Table ). The groups with highest share in total fruit and vegetable exports are, tomatoes, raisins and citrus fruits. The survey sample consists of the total of 4 processed tomato, raisin and citrus exporting firms from the member list of Ege Region Union of Exporters. A mail survey is conducted through a structured questionnaire among which a total of 3 firms responded. surveys out of 3 surveys were usable for analysis. 4. Empirical Results 4.. Firm Profile The survey sample reveals that the majority of the firms are small-scale enterprises. Table 3 summarizes the distribution of firms with respect to number of employees. 6% of the firms employ less than 5 employees. Further analysis of firm size and innovativeness shows that no systematic association exists between firm size and innovative culture. Table 4 reports the distribution of the firms with respect to innovative capacity and innovativeness. Firms whose culture is represented by high degree of innovativeness are more likely to 5

6 develop new products, new production technologies and make a major investment. 4.. Quality Management Practices The finding that innovativeness and innovative capacities are statistically dependent leads us to further explore and classify thet variables that determine the firms' innovativeness. The cultural variables related with quality management practices were reduced into a new set of salient variables by factor analysis Factors with eigenvalues greater than. are retained. Inspection of scree plot and eigenvalues enabled us to reduce the quality management variables into 6 factors. Table 5 reports the factors and corresponding quality management practices. Table 6 presents rotated component factor martix. The interpretations of the factors that summarize quality management practices are as follows. FACTOR : OPEN INFORMATION- PARTICIPATIVE STRUCTURE Decision making is delegated to the lowest possible level of authority The employees are involved in the decision making process. Decisions are openly discussed at all levels. After the decision is made the management communicates the results and the reasons of the decision with all departments. There is willingness for employee empowerment, which provides a medium for cooperation and teamwork. are the components explained in this factor. Variable, which explains the decision making style has the highest loading which shows that open information and participative strategy is kept important in this industry. The next highest loading is variable 9, which gives importance to open information and does not hide the decisions to them. This factor explains.49% of the total variance, which indicates that the greatest portion is explained in this factor. 6

7 FACTOR : STANDARDIZATION OF WORK There are written procedures and rules for implementation of each work type. Our firm has an organization chart. We have written job descriptions. There are written rules and regulations directly for the shop floor employees. are the components explained in this factor. The highest loading in this factor is variable, which measures the presence of written procedures and rules for implementation of each work type. Presence of written procedures shows that the companies give importance to standardization of work through written rules and procedures. With the help of these standard implementation styles the percentage of doing mistake was reduced. The second highest loading is variable, which measures the degree to which the companies pay importance to job descriptions. Factor explains 6.93% of the total variance. FACTOR 3: MARKET MONITORING We frequently and systematically measure the customer satisfaction. We try to meet and satisfy the customer's expectations while setting our marketing strategies. We regularly analyze and observe our competitors marketing strategies. The functional departments such as marketing, finance, manufacturing and distributing, of the firms cooperate while we develop new products. are the components explained in this factor. The highest loading was on variable that focuses on the importance of customer satisfaction. The next highest loading was about meeting customer satisfaction, which again implies the importance of monitoring customers. The loadings also prove that the organization do their market monitoring by giving the most importance to their customers. This factor explains 4.64% of the total variance.

8 FACTOR 4: WORKING IN HARMONY The employees have a tendency towards helping and supporting each other. There is a willingness to accept responsibility for failure. There is willingness for mutual collaboration across organizational units within the firm. are the components explained in this factor. The variable that measures the degree to which the employees are able to put a burden of failure on themselves (variable 3) has the highest loading among other variables that explains factor 4. The second highest loading in factor 4 was explained by the third variable, which measures the degree to which the units formed in the organization are not competing with each other and has the comfort of working together. Factor 4 explains.5% of the total variance. FACTOR 5: TEAMWORK AND PARTICIPATION Factor 5 includes only one variable and explains 6.4% of the total variance. We talk about teamwork and participation but people do claim their power and authority in silence. FACTOR 6: ORGANIZATIONAL STRUCTURE Factor 6 includes only one variable and explains 5.5% of the total variance. Authority is centralized. Factors through 5 are variables that are consistent with the nature of learning organizations. However factor 6 verifies that firms in the survey sample are likely to finalize their decisions at the top management level Quality Management Practices and Innovative Culture Factor analysis enables us to reduce the number of dimensions with respect to the quality management practices from variables to 6 uncorrelated sets of variables. The new set of variables was used in subsequent analysis. Using the new set of variables, we use two-group discriminant analysis to explore which variables are best able to explain the variations in innovativeness of the firms. The results of running two-group discriminant analysis are presented

9 in Tables through. The dependent variable of the discriminant function is a measure of the firms' innovativeness. The categorical dependent variable of the discriminant analysis measures the classification of the firm based on cluster analysis using the cultural variables presented in Table. Group consists of firms in cluster (firms with low degree of innovativeness) and group consists of firms in cluster (firms with low degree of innovativeness). Out of observations, 6 observations were used. For validation purposes, 5 firms consisted of analysis sample, 6 firms were treated as holdout sample. Table Reports the frequencies of the holdout sample and analysis sample used in the discriminant analysis. Intuitive examination of the group statistics reveals that the two groups differ with respect to each variables (Table ). The group with high degree of innovative culture has negative mean values for each of the standardized factor scores that measure the quality management practices. The second group with low degree of innovativeness has positive mean values for the discriminating variables (factor scores). The pooled within group correlation matrix indicates low correlations between the predictors. This implies that that multicollinearity is unlikely to be problem (Table 9). Because there are two groups, only one discriminant function is estimated. The eigenvalue (the ratio of the between groups sum of squares to the within groups sum of squares) associated with the discriminant function is.435, and it accounts for % of the explained variance. The canonical correlation coefficient that shows the association between the discriminant scores and the group is.6, which indicates a strong correlation between the discriminating scores and the group. The square of the canonical correlation is.59 and it indicates that 5% of the variance in the dependent variable (innovativeness) is explained by the model. Table tests the hypothesis that the means of the functions listed are equal across groups. The null hypothesis that, in the population, the means 9

10 of all discriminant functions in all groups is equal. The result, based on Wilk's l is based on a chi square transformation of the statistic. In testing for significance of the discriminating power of the quality management scores, the Wilk's l value associated with the function is.4, which translates to a chi square statistics of 34.. The resulting statistics with degrees of freedom rejects the null hypothesis that the means of the functions listed are equal across groups. The result implies that the two groups (low level of innovativeness and high level of innovativeness) are statistically different with respect to the discriminating quality management practices. The group centroids, giving the value of the discriminant function evaluated at group means, are also shown in Table Group (low level of innovativeness) has a positive value and group (high level of innovativeness) has a negative value. The signs of the coefficients associated with all the predictor variables are all positive, which suggests that higher factor score values results with the firm more likely to belong to the group with low level of innovativeness. The analysis results reveal that factor score (standardization of work) is the most important predictor in discriminating between the groups, followed by factor score 3 (market monitoring) and (open information and participative structure). The rank order of importance as determined by the relative magnitude of the canonical loadings, is presented in the first column (Table ). The presence or absence of ISO certificate has a low discriminating power between the two groups of firms. This result indicates that the presence of ISO certificate is irrelevant to the firm's innovativeness. The firms with high degree of innovativeness and low degree of innovativeness are best discriminated by the factors that summarize quality management practices and not by the presence or absence of ISO certificate. Classification results confirm the validity of the discriminating power of

11 the estimated discriminant function. 9.9% of the selected original grouped cases were correctly classified and 4.6% of the unselected original grouped cases were correctly classified. The results indicate that the validity of the discriminant analysis is judged as satisfactory. 5. Conclusion The results of the paper can be summarized under the following two subheadings: General findings Quality management and innovative capacities, defined as new product development, new process development and making new investments, are parallel concepts. Factor analysis reveals that quality management variables can be summarized under six related subgroups of activities (factors) among which, open information and participative structure, standardization of work and market monitoring are the three factors explaining more than half of the total variance of the sample. The result indicates that innovativeness can best be explained by the above three groups of quality management activities. Results of the discriminant analysis are consistent with the factor analysis findings. Discriminant analysis reveals that quality management practices that best discriminates firms with respect to innovativeness are standardization of work, market monitoring and open information and participative structure. Furthermore, the findings suggests that to improve innovative capacities of the firms, certain quality management practices matter most and the presence or absence of an ISO certificate has only a minor contribution on innovativeness. Implications for Further Research The research was limited to only three subgroups of products in fruit and vegetable processing industry. For generalization purposes it is needed to increase the sampling universe.

12 The innovativeness and innovative capacity measures depends on technical implementation of innovations. The paper does not focus on research and development based innovations and does not discriminate patents and product/process adoptions. In further research a number of patents should be taken into account. In addition to the points stated above, the paper is restricted with only SME's, while it should also be looked at large scale firms for a comparative purpose. References:. Akgüngör, Sedef, R. Funda Barbaros and Neşe Kumral (). Sustainable Competitiveness of Turkish Fruit and Vegetable Industry. Agricultural Economics Research Institute Project Report -3.. Deshpande, Rohit and Robin Webster (99). Assessing Advantage: A Framework for Diognising Competitive Superiority. Journal of Marketing 5(April): Hurley, Robert, F. and G. Thomas M. Hult. (99). Innovation, Market Orientation and Organizational Learning: An Integration and Empirical Examination. Journal of Marketing 5(3) (July): Hurley, Robert, F. (995). Group Culture and Its Effect on Innovative Productivity. Journal of Engineering and Technology Management (July): 5-5.

13 Table : Quality Management Variables We frequently and systematically measure the customer satisfaction. We try to meet and satisfy the customer's expectations while setting our marketing strategies. 3 We regularly analyse and observe our competitors marketing strategies. 4 The functional departments such as marketing, finance, manufacturing, and distributing, of the firms cooperate while we develop new products 5 Market information is shared across all functional departments 6 Our firms use written contracts for recruitment There are written procedures and rules for implementation of each work type. Our firm has written production plans and programs. 9 Our firm has an organization chart. We have written job descriptions. There are written rules and regulations directly for the shop floor employees. The employees have a tendency towards helping and supporting each other. 3 There is a willingness to accept responsibility for failure 4 There is willingness for mutual collaboration across organizational units within the firm. 5 Decision making is delegated to the lowest possible level of authority 6 The employees are involved in the decision making process. Decision making is based on research and technical criteria rather than politics Decisions are openly discussed at all levels 9 After the decision is made the management communicates the results and the reasons of the decision with all departments. There is willingness for employee empowerment, which provides a medium for cooperation and teamwork. We talk about teamwork and participation but people do claim their power and authority in silence. Authority is centralized 3

14 4

15 Table : Distribution of Fruit and Vegetable Exports (SITC classification) P r o d u ct c o d e Product Name 99 Export Rate ($) 999 Export Rate ($) 9-99 Export Rate ($) % 4,36,49 4,59,66 3,935,.6 55,59,3,9,9 3,5, ,64,4,3,4 3,53,49.3,, 9,4,335,. 34,6 59,63 9,6.,9,4,69,9,,5.3 6,56,94 3,55,553 4,9,94.4 4,44,446,435,44,44,45. 9,69,4 6,4,56,9,5.55 6,59 3,54,44.,9 5,955 3,6. 4,636 5,94 3,. 5

16 ,4,39,3,59 3,6, Citrus fruits 3,95,9 5,34,93,653,4 5. Grape/raisin 4,43,43,6,45 6,349, ,4,64 3,369,339 4,36,.3 33,,5,6,4,944,3.9 36,3, 43,3, 39,66, ,59, 9,45,94,49,39.3 6,46,5 5,4,9 5,4,56.5,,39 33,93,5 5,45,.4 359,44 3,6 4,9. 9,4,,336,439,9, Tomatoes 33,9,5 3,64, 33,3,45.5 6, 5,66 3,4.,9,43 3,6 34,65.6 6

17 9 43,55,56 4,,59 4,63, ,66,664 69,,6 6,9,4 5.3 Total,,3,696,,6,4,5,,49

18 Table 3. Size Distribution of Sample Firms Size (number of employees) Frequency % Less than Total. Table 4. Distribution of Firms with Respect to Innovative Capacities and Innovativeness (frequencies) Innovativeness Innovative Culture Low High Yes No Yes No Introduce a new product 3 9 Pearson chi square statistic: 9.55 * Renew the production technique Pearson shi square statistic: 4.994* Buy another enterprise 3 Pearson shi square statistic:.3 Make an important investment Pearson shi square statistic: 5.39* Begin to export 5 Pearson shi square statistic:.9 * Indicates that the null hypothesis that no systematic difference exists between the two groups with respect to innovative capacities is rejected at the a³.5 level.

19 Table 5: Quality Management Practices and Corresponding Factors FACTOR Quality Management Practices FACTOR 5, 6,, 9, FACTOR, 9,, FACTOR 3,, 3, 4 FACTOR 4, 3, 4 FACTOR 5 * FACTOR 6 * Note that quality management practices are reported in Table. * Indicates reverse order questions 9

20 Table 6 Rotated Component Matrix Variables Component ,,34 3,5 4,63 5 6,3 9,5,53,6,63 3,3 4, 5, 6,6,49 9,59,36 -,36,93 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Analysis Table Analysis and Holdout Sample in Discriminant Low degree of innovativeness High degree of innovativeness Total Analysis Sample Holdout Sample 4 6 Total 49 6

21 Table. Summary Statistics of the Groups Used in Discriminant Analysis (Group : Low Degree of Innovativeness; Group : High Degree of Innovativeness) Independent Variables Mean Std. Deviation Valid N (list wise) Gro Factor,6439,69 3 up Factor,3366, Factor 3,555, Factor 4,33539,3 3 Factor 5,456,9 3 Factor 6,969,956 3 Presence or absence of ISO,, 3 Certificate Gro Factor -,33,94 3 up Factor -,46494, Factor 3 -,364, Factor 4 -,6E-,534 3 Factor 5-5,693566E-,636 3 Factor 6 -,4399E-,66 3 Presence or absence of ISO Certificate 9,649E-,353 3 Table 9. Pooled within group correlation matrix Factor Factor Factor 3 Factor 4 Factor 5 Factor 6 Presence or Absence of ISO certificate Factor, -,59 -,3 -, -,6 -,9,463 Factor -,59,, -,5 -,5,9 -,5 Factor 3 -,3,, -,46 -,35 -, -,9 Factor 4 -, -,5 -,46,, -, -, Factor 5 -,6 -,5 -,35,, -,5,46 Factor 6 -,9,9 -, -, -,5,,

22 Presence or Absence of ISO certificate,463 -,5 -,9 -,,46,, Table. Canonical Discriminant Function Eigenvalues Function Eigenvalue % of Variance Cumulative % Canonical Correlation,435,,,6 Wilks' Lambda Test of Wilks' Lambda Chi-square df Sig. Function(s),4 34,, Table. Unstandardized canonical discriminant functions evaluated at group means (Functions at Group Centroids) Group Function, -,5 Table. Standardized canonical discriminant function coefficients sand canonical loadings Standardized Coefficients Canonical Loadings Factor Factor Factor Factor Factor Presence or Absence of ISO certificate Factor Note: Rank order of importance is based on the magnitude of the canonical loadings.

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