Measurement of Quality Costs in the Turkish Food Industry

An Expert's View about Food Processing in Turkey

Posted on: 12 Apr 2010

The measurement of the quality costs is a good indicator of the quality and the overall performance of a firm. There have been many attempts in measuring quality costs both in theoretical and empirical researches. However, there is a lack of research about the measurement of quality costs as far as the food industry is considered. Therefore, the purpose of this study is to measure quality costs with specific reference to the Turkish food manufacturing industry.

This article was downloaded by: [T BTAK EKUAL] On: 4 June 2009 Access details: Access Details: [subscription number 786636097] Publisher Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Total Quality Management & Business Excellence Publication details, including instructions for authors and subscription information: http://www.informaworld.com/smpp/title~content=t713447980 A research on the measurement of quality costs in the Turkish food manufacturing industry Mine Omurgonulsen a a Department of Business Administration, Hacettepe University, Ankara, Turkey Online Publication Date: 01 January 2009 To cite this Article Omurgonulsen, Mine(2009)?A research on the measurement of quality costs in the Turkish food manufacturing industry?,Total Quality Management & Business Excellence,20:5,547 562 To link to this Article: DOI: 10.1080/14783360902863739 URL: http://dx.doi.org/10.1080/14783360902863739 PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf This article may be used for research, teaching and private study purposes. 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Total Quality Management Vol. 20, No. 5, May 2009, 547?562 A research on the measurement of quality costs in the Turkish food manufacturing industry  Mine Omurgonulsen Department of Business Administration, Hacettepe University, 06800 Beytepe, Ankara, Turkey The measurement of quality costs is a good indicator of the quality and the overall performance of a firm. There have been many attempts to measure quality costs in both theoretical and empirical research. However, there is a lack of research about the measurement of quality costs as far as the food industry is concerned. Therefore, the purpose of this study is to measure quality costs with specific reference to the Turkish food manufacturing industry. In contrast to many previous studies made with cross-section or time series regression, panel regression method has been used to analyse the relation between conformance costs and non-conformance costs in seven leading Turkish food manufacturing firms, for the period 2000?2005. It has been found that when the conformance costs are increased by 1%, the non- conformance costs decline by 0.83%. This also means that the basic premise of the traditional quality cost model has been confirmed. That is to say, there is a trade-off between conformance and non-conformance costs and the non-conformance costs can be reduced by increasing conformance expenditures. In conclusion, the negative relation found between conformance and non-conformance costs can rather be attributed to external failure costs than internal failure costs. Keywords: quality costs; conformance costs; non-conformance costs; internal failure costs; external failure costs; Turkish food manufacturing industry; panel regression method Introduction As a result of severe competition and changing and diverse customer expectations in today?s global world, firms can hardly compete in the marketplace without controlling their costs. The losses resulting from poor quality are more critical meaning that the firms will lose their competitive chances. Quality costs, in this context, represent the hidden portion of the cost iceberg, which will create a great competitive advantage to the firms, as long as they are detected and controlled. Therefore, the measurement of the costs of quality is worth taking into consideration not only at firm level, but also for the industry and economy as a whole. In general, quality costs fall into two major categories: the cost of achieving good quality, also known as the cost of conformance, and the cost associated with poor- quality products also referred to as the cost of non-conformance (Russell & Taylor, 1995). There are some models in the quality costs literature, which discuss the relation between conformance and non-conformance costs, which are also known as ?the traditional quality cost model?, ?quality-based learning model? and ?the new model of quality costs?. This paper examines the effect of the cost of conformance on the  Email: mergun@hacettepe.edu.tr ISSN 1478-3363 print/ISSN 1478-3371 online # 2009 Taylor & Francis DOI: 10.1080/14783360902863739 http://www.informaworld.com Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009 548 M. Omurgonulsen non-conformance costs in the leading firms of the Turkish food manufacturing industry by using panel regression to test which model is valid for the sample firms. Within this frame- work, first the quality costs concept and the relation between quality cost components are discussed. The remainder of this paper is dedicated to hypotheses development; the measurement of quality costs in the food manufacturing industry; discussion of the meth- odology including the sample, the data collection and the empirical results. A discussion, the managerial implications, and directions for future research conclude the paper. The concept of ?quality costs? In today?s global competitive situation for business firms, quality is a good weapon to sustain customer satisfaction and to adjust to the market conditions. Therefore, the concept of ?quality costs? is an important indicator of the quality and, therefore, the overall performance of a firm. Quality is defined in terms of the degree of the product?s conformance to its require- ments to sustain customer satisfaction and in terms of a product that contains no defects (Juran, 1988). The customer-based approach to quality focuses on satisfying the customer, while the manufacturing-based definitions evaluate quality as conformance to specifica- tions (Garvin, 1984). Among the non-customer-oriented quality definitions, there also exists the definition of quality as eliminating waste and doing it right the first time (Tamimi & Sebastianelli, 1996), which also points out the common denominator of the concepts of quality and quality costs. Quality and quality costs are, therefore, two concepts that share the same perspective of a way of sustaining customer satisfaction by producing goods and services in the right way the first time they are produced. The concept of ?quality costs? has largely been discussed in operations management lit- erature especially after the 1950s (Bajpai &Willey, 1989). This was due to the fact that there has been a common belief in the past that quality could not be measured in terms of costs. It was J.M. Juran who first introduced the concept in Quality control handbook, which was originally published in 1951 (Juran, 1988) and then Feigenbaum, another pioneer of quality cost thinking, in his article named ?Total quality control? in Harvard Business Review of 1956 (Feigenbaum, 1956). It was Feigenbaum who defined quality costs as: Those costs associated with the definition, creation, and control of quality as well as the evaluation and feedback of conformance with quality, reliability, and safety requirements, and those costs associated with the consequences of failure to meet the requirements both within the factory and in the hands of customers. (Feigenbaum, 1983, p. 110) Feigenbaum was the first to categorise quality costs into three components as preven- tion, appraisal and failure costs (Feigenbaum, 1956). P. Crosby divided quality costs into two as the sum of prevention and appraisal costs as the cost of conformance and the sum of the internal and external failure costs as cost of non-conformance (Crosby, 1983; Williams et al., 1999). There are different ways of collecting and reporting quality costs, one of which is called the quality costing approach (Campanella, 1999), also known as the PAF (prevention- appraisal-failure) method (BSI, 1992; Campanella, 1999; Juran, 1998; Russell & Taylor, 1995), which consists of four basic elements: . Prevention costs: Costs that result from the efforts of the company during product design and manufacturing that prevent non-conformance to specifications, like quality planning; quality review and verification of design; process planning; supplier assurance; calibration and maintenance of quality measurement and test Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009 Total Quality Management 549 equipment; quality audits; administration and training; quality improvement 1 programmes; quality certification costs. . Appraisal costs: Costs incurred to determine the degree of conformance to quality requirements, like pre-production verification; laboratory acceptance testing; incom- ing inspection and tests; in-process inspection and tests; final inspection and tests; field performance testing; inspection and test equipment; record storage. . Internal failure costs: Costs incurred when poor-quality products are discovered before they are delivered to the customer, like scrap; rework and repair; trouble- shooting or defect/failure analysis; re-inspection and retesting; downgrading. . External failure costs: Costs incurred after the customer has received a poor-quality product and that are primarily related to customer service, like returned material; customer complaints; product liability; warranty claims; loss of sales. It can be inferred that internal failure costs are the costs that occur when the quality is not sustained from the perspective of the producer, whereas external failure costs result from not being able to sustain quality from the viewpoint of the customer. Although these interpretations draw the general outline of the concept, it would certainly be better to define quality costs in terms of the sector where the measurement would be made. Indeed, there are some studies in the literature that strongly support the idea of defining the concept of quality costs not only at the industry level, but even at the firm level (Juran & Gryna, 1988). After the indepth literature survey, it has also been found out that the term ?quality costs? has been used interchangeably with the term ?poor-quality costs? by many writers (Asokan & Pillai, 1998; Chiadamrong, 2003; Halevy & Naveh, 2000; Harrington, 1987; Juran, 1998; Juran & Gryna, 1988; Tatikonda & Tatikonda, 1996). Some writers define quality costs as the cost of non-quality, which is the sum of resources, such as capital and manpower, wasted due to inefficient planning design, planning and manufacturing processes plus the investment in order to prevent this waste (Naveh & Halevy, 1999). It was also pointed out by some of the writers that the term refers to the costs that occur due to inferior quality (BSI, 1992; Gupta & Campbell, 1995; Juran & Gryna, 1988; Naveh & Halevy, 1999; Tatikonda & Tatikonda, 1996). In this paper, the term ?quality costs? is used instead of ?costs of poor quality? to cover the meaning of the costs of attaining quality as well as the costs of not attaining the quality. It is worth mentioning that the sub-elements of internal failure costs like scrap, repair or the sub-elements of external failure costs like returned material represent the defective pro- ducts. As the defective products are defined as one of the sources of waste (Johnston, 1989), it can be concluded that the concept of ?defective products? is the intersection point of the concept of ?waste? and the concept of ?quality costs?, which also represents one of the most important reasons for conducting a survey like the measurement of quality costs. Waste is also shown as an observable part of the cost iceberg in the literature (Defeo, 2001). The nature of the relation between quality cost components To analyse the effect of the change in one quality cost component on another, it is necess- ary to investigate the relations between the four components. The increase in appraisal and prevention expenditures is assumed to bring a decline in failure costs. The increase in the appraisal costs may lead to a reduction of the failure costs because the appraisal activities are designed to investigate and to find the defective product before it is delivered to the consumer (Campanella & Corcoran, 1983). Greater expenditure on prevention would Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009 550 M. Omurgonulsen result in improved conformance and lower defects, in turn, are likely to produce overall reduction in the total costs of quality because of significant savings in rework, scrap and warranty (Garvin, 1984). Nevertheless, the exact relation between the components of quality costs is not easily determined, because it may change from one system to another depending on the nature of the business (Chen & Weng, 2002). There are three important models in the literature, in which the relations between the quality cost components are discussed. The first one, ?the traditional quality cost model?, was dominant in literature in the twentieth century. Figure 1 illustrates the model displaying the relation between conformance and quality-related costs. As conformance improves, non-conformance costs decrease and conformance costs increase. The total of the quality costs is the sum of conformance and non-conformance costs. The minimum point in the TQC curve is termed as the economic quality level (EQL), represented by Q (Foster, 1996), which coincides with a conformance of quality under 100%. According 1 to this model, as the appraisal activities are carried out by a fallible labour force (who are unable to maintain and exert muscular energy 100% of time, etc.), the cost of striving to attain perfect quality goes to infinity. Therefore, total quality costs also approach infinity (Juran & Gryna, 1988). This, in turn, would mean that the ultimate goal of quality manage- ment is never achieved and this level of quality, Q is always under the 100% level. 1, As the traditional quality cost model suggests that a decline in the non-conformance costs can only be attained by increasing conformance costs, the effects of quality learning and improvements on quality costs are totally ignored. However, the continuous improve- ment philosophy of quality cost behaviour has received theoretical support from work on quality-based learning. These models suggest that the traditional trade-off model may be a static representation of quality cost economics, but that in dynamic learning environments, conformance expenditures need not be increased to achieve ongoing reductions in failure costs (Ittner, 1996). A dynamic model suggests that with the identification and correc- tion of quality problems, a manufacturer is able to increase its rate of learning and thereby lower its quality assurance costs below their previous level (Fine, 1986; Mandal & Shah, 2002; Marcellus & Dada, 1991). As the efficiency and effectiveness of Figure 1. Traditional quality cost model (Juran & Gryna, 1988, 4.19). Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009 Total Quality Management 551 Figure 2. Quality-based learning model (Fine, 1986, p. 1310). quality control activities increase due to organisational learning, the conformance costs curve shifts down and to the right, thereby allowing reductions in non-conformance costs over time to be accompanied by reductions in conformance expenditures, as shown in Figure 2. As the traditional quality model has been modified into a quality- based learning model, it has been shown that the optimal quality level increases from Q to Q which directly corresponds to a higher level of quality. 1 2, With the introduction of developing technologies, ?the new quality cost model? came on to the agenda in the late twentieth century. At present, there seems to be a consensus that perfect outgoing quality can be achieved at a finite cost because of the rapidly developing technologies in automation, robotics, etc. (Simga-Mugan & Erel, 2000). With robotics and automation, human error during production is reduced. With the reduction of human error of appraisal by automated inspection and testing, the total quality costs do not approach infinity any more, as can be followed from Figure 3 (Juran & Gryna, 1988). This model also reflects the fact that optimum quality cost would mean zero defects (Schneiderman, 1986). As the company focuses on improved quality, the costs of conformance will be less owing to the innovations in technologies, processes and work methods that will result from the quality improvement effort. Therefore, the costs of conformance in Figure 3 are not rising as rapidly as they are in Figure 2 (Russell & Taylor, 1995). As the new model of quality costs has emerged, it has been shown that the shape of the total quality costs curve has also changed, in which the minimum point of the curve coincides with 100% quality (zero defects) and perfect quality can be attained with finite costs. The measurement of quality costs in the food manufacturing industry In today?s world, the measurement of quality costs is crucial to analyse the performance of firms especially in a world of scarce natural resources and severe competition. Given its direct dependence on the earth?s resources, the food and beverage industry is among the first sectors to face these issues (Poynton, 2007). Therefore, when the general uses of quality costs are considered as to promote quality as a business parameter, to give rise to performance measures, to plan and control future quality costs and to act as motivation Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009 552 M. Omurgonulsen Figure 3. New model of quality cost (Juran & Gryna, 1988, 4.19). (Plunkett & Dale, 1987), the importance of this measurement in the food manufacturing industry can better be assessed. As the measurement of quality costs shows the quality improvement process through waste reduction (Schrader, 1986), the measurement of quality costs represents an important amount of food waste that has potentially been elimi- nated. The existence of waste signifies that the jobs are not being done well the first time they are done and the necessity of rework and repair, which all would contribute to increase the costs of quality. In recent years, growing interest about hunger, resource conservation, and the environ- mental and economic costs associated with food waste have raised public awareness of food loss. This, in turn, has accelerated public and private efforts to make better use of available food supplies by recovering safe and nutritious food that would otherwise be wasted (Kantor et al., 1997). Food losses also occur when raw agricultural commodities are made into final food products, some of these which, like removing edible skins 2 from fresh produce, are a normal and necessary part of food processing (Kantor et al., 1997), while some are not (rework, scrap, returned products). The objective of the food industry should be to produce its products in a sustainable way. Spoiling nature?s resources means an inefficient way of transformation of raw materials into final products, resulting in large amounts of waste. The amount of industrial waste is 330 million tones and 400 million tones per year in Europe and the US respectively. Roughly, 20% of this amount can be attributed to the food, drink and tobacco industries (Somsen et al., 2004). With respect to Turkey, the situation is not very different. It has been estimated that as a result of the inefficient use of the resources, the total loss in agriculture is $61 billion and the total loss in the food industry is $16 billion in 2003 in Turkey (61 milyar dolar zarar, 2004). As the Turkish Gross National Product (GNP) for the year 2003 is $240 billion (Capital Infocard, 2004), it can be easily calculated that the total waste of agriculture is almost 25% of GNP and the total loss of the food industry is 6.6% of GNP for the Turkish economy. These figures draw attention to the significant level of waste in the food industry not only all over the world, but also in Turkey. There is a lack of research in the quality costs literature, as far as the food manufacturing industry is considered. Dale and Wan?s study represents one of the few which attempts to Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009 Total Quality Management 553 adjust the concept of quality costs into the elimination of waste efforts by setting up a quality costing system in a flavouring-manufacturing firm (Dale & Wan, 2002). The situation is not very different in Turkey. One of the few studies in costs of quality measure- ment has been undertaken in the biggest beer-producing firm in Turkey (Harmandar et al., 1996). In another study, the approximate amount of waste in one of the leading food and vegetable processing firms in Turkey, called Merko, was measured in terms of internal failure costs (Omurgonulsen et al., 2005), where significant reductions in internal failure costs have been found as a result of the introduction of the quality management system of HACCP (Hazard Analysis and Critical Control Points). Quality costs have also been analysed from the viewpoint of the traditional quality cost and quality-based learning models for firms operating in the Turkish food manufacturing industry in some other studies (Omurgonulsen, 2007; Omurgonulsen et al., 2006). Hypotheses development In this study, the effect of increased conformance expenditures on non-conformance costs is being tested. Therefore, the first hypothesis can be written as follows: H1: Conformance (prevention and appraisal) expenditures must be increasing over time to achieve reductions in non-conformance (internal and external failure) costs. Therefore, there is an inverse relation between conformance and non-conformance costs. The testing of H1 is actually the testing of the basic premise of the traditional quality cost model, which suggests that the decline in non-conformance costs can only be attained by increasing conformance costs. To test H1, a logarithmic model was formulated to express the coefficients in terms of elasticity, where the coefficient of b shows how much percentage of change takes place in non-conformance costs, when conformance costs are increased by 1%. ln (Non-conformance costs) ¼ aþ b ln (Conformance costs) (1) it it Non-conformance costs are, then, decomposed into internal and external failure costs and conformance costs, as prevention and appraisal costs respectively to build the other hypotheses. To fulfil this purpose, first the effect of conformance costs on the internal failure costs, then, the effect of conformance costs on the external failure costs are tested. Therefore, hypotheses H2 and H3 can be written as follows: H2: The increased expenditures on conformance activities cause internal failure costs to decline. Therefore, there is an inverse relation between conformance and internal failure costs. H3: The increased expenditures on conformance activities cause external failure costs to decline. Therefore, there is an inverse relation between conformance and external failure costs. The following models are formulated to test hypotheses H2 and H3. ln (Internal failure costs) ¼ aþ b ln (Conformance costs) (2) it it ln (External failure costs) ¼ aþ b ln (Conformance costs) (3) it it Then, the conformance costs are sub-categorised as prevention and appraisal costs to find out whether prevention or appraisal activities are more effective to sustain a decline in non-conformance costs. Internal failure costs are expected to decline as a result of the investment on prevention and appraisal activities. Once prevention and appraisal activities Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009 554 M. Omurgonulsen are carried out, the internal failure costs such as scrap, rework and retest are expected to be lower. Therefore, the following hypothesis is formulated: H4: Internal failure costs decline over time as a result of the investment made on conformance activities. Therefore, the components of conformance costs, prevention and appraisal costs have an inverse relation with internal failure costs. By the same token, the expenditures in prevention and appraisal activities are expected to reduce external failure costs. Once the quality system is properly installed and all the tests and inspections are carefully made within a firm, it is expected that losses resulting from defects that cannot be detected within the factory would be lower. The last hypothesis can be written as follows: H5: External failure costs decline over time as a result of the investment made on confor- mance activities. Therefore, the components of conformance costs, prevention and appraisal costs have an inverse relation with external failure costs. The formulated models to test hypotheses H4 and H5 are as follows. ln (Internal failure costs) ¼ aþ b ln (Prevention costs) it 1 it þ b ln (Appraisal costs) (4) 2 it ln (External failure costs) ¼ aþ b ln (Prevention costs) it 1 it þ b ln (Appraisal costs) (5) 2 it Methodology Unlike previous studies made either with cross-section or time series regression (Ittner, 1996; Krishnamoorthi, 1989), panel regression method, which takes the firm-specific and temporal effects into consideration, has been used to analyse the relation between con- formance and non-conformance costs in leading Turkish food manufacturing firms in this study. As panel regression is useful in the analysis of cost and refers to any dataset of repeated observations of the same individuals (Arellano, 2003), which are firms in this study, it fulfils the purpose of investigating the effect of conformance costs on non- conformance costs for the sample firms. What is specific about panel data is the possibility of following the same individuals over time, which facilitates the analysis of dynamic responses and the control of unobserved heterogeneity, which is not surprising when dealing with different units (Arellano, 2003). By combining time series of cross-section observations, panel data give more informative data and are better suited to study the dynamic of change that simply cannot be observed in pure cross-section or pure time series data (Gujarati, 2003). The research sample, the way the data are collected and the results are to be discussed in this section. The limitations of the study, managerial implications and directions for future research conclude the paper. Research sample: the Turkish food manufacturing industry The Turkish food industry contributes 5% of the GNP and it had a 20% share in total pro- duction of manufacturing sector by 2002. The food sector employs more than 100,000 registered workers and technical staff in more than 28,000 enterprises, which are mostly Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009 Total Quality Management 555 small and medium enterprises (SMEs) (T.R. Prime Ministry State Planning Organization, 2004). From these facts, it can be concluded that the food industry has an important role in the Turkish economy. Some of the strengths of the food industry are: no difficulty in finding raw materials; variety and quantity of agricultural production; relatively cheap labour force; increasing volume of trade and the prospect of EU accession; whereas the weaknesses of the industry are characterised by insufficient integration and cooperation between agriculture and industry, quality and safety problems in agriculture; technology and capacity utilisation problems of most food producing SMEs. Data collection The quality costs measurement question form, especially designed to monitor the quality costs of the food manufacturing industry, was sent to the biggest 30 firms that dominate 60?70% of the market, by either email or fax. It is also worth mentioning that some of these firms (which are located throughout Turkey) have been visited personally and more than once. The purpose and potential benefits of the study were explained to the top management and then, with their permission, interviews were undertaken with the quality managers. Of these 30 firms, seven firms returned the quality costs measurement 3 form corresponding to a response rate of 23%. The firms are all leader firms in terms of either market share or net sales in their sub-sectors of margarine, sugar and confection- ary, macaroni, oil, food and vegetable processing, alcohol-free and alcoholic beverages, respectively. These firms are also among the first 500 biggest industrial corporations in terms of the net sales in the years 2000?2005 according to the study carried out by the Istanbul Chamber of Industry annually (Istanbul Chamber of Industry, 2005), which proves their market dominancy in their sub-sectors. As some part of the quality cost data was not kept in the accounting records, they were extracted by the interviews with the quality control managers of these firms. Panel data were gathered between the years 2000 and 2005 for each firm in the sample. The panel dataset includes the quality cost data of each firm (n) for six years (t). Therefore, the sample set consists of 42 (67) observations, which can also be found in Appendix 1. Results and discussion Panel regression has been run and the results are discussed in this section. Estimation results regarding hypothesis H1 In Table 1, fixed coefficients and fixed effects regression results regarding H1 have been summarised. This table also reveals the advantages of the fixed effects method over the fixed coefficients method. According to the fixed coefficients method, the Beta coefficient has been found to be 1.36 and statistically significant at 1%. However, this method ignores 2 the firm-specific and temporal effects. The value of R of 0.33 means that about 33% of the variation in non-conformance costs is explained by conformance costs. Therefore, this result shows that without taking these factors into consideration, the explanatory power of the variation in non-conformance costs by conformance costs is not high and the estimation should be redone by the fixed effects method. In the fixed effects method, a dummy variable is added to the model for each firm and year and the model is estimated by least squares dummy variable model (see Yaffes, 2003). Firm-specific effects can matter because of the special features of each Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009 556 M. Omurgonulsen Table 1. Fixed coefficients and fixed effects panel regression of conformance costs on non-conformance costs for seven firms over six years. Method Fixed coefficients method Fixed effects  Constant term (a) ?4.37 24.12 (3.93) 3.68   ln (Conformance costs) 1.36 ?0.83 coefficient (b) (0.30) 0.28 2 R 0.33 0.94 Fixed effects test 2  Cross-section x ? 100.88 2  Period x ? 12.30 2  Period x ? 101.91 77 nt 42 42   Note: The standard errors have been shown in parentheses. The symbols and show the level of significance at 1% and 5% respectively. company, such as managerial style or management philosophy (Gujarati, 2003). Accord- ing to the estimation results of the fixed effects method, the Beta coefficient is found to be ?0.83 and statistically significant at 1% level. This means that, ceteris paribus, for the years between 2000 and 2005, for the seven firms, when the conformance expenditures are increased by 1%, non-conformance costs decline by 0.83%. The Beta coefficient which is close to unit elasticity with a negative sign shows that when conformance expen- ditures are increased by 1%, non-conformance costs decline almost by 1%. Therefore, H1, the basic premise of the traditional quality cost model emphasising the trade-off between conformance and non-conformance costs has been confirmed. This result also supports some of the empirical research findings in the literature (Burgess, 1996; Chauvel & Andre, 1985; Krishnamoorthi, 1989; Omachonu et al., 2004). Therefore, the model can be written as: ln (Non-conformance costs) ¼ 24:12 0:83 ln (Conformance costs) (6) it it The last column of Table 1 shows the redundant fixed effects test in which the val- idity of the two-way fixed effects has been tested. In other words, it has been tested whether firm-specific and temporal effects are helpful in explaining the relation between conformance and non-conformance costs. It can be seen that the two-way effect is also significant at 1% level. In fact, the redundant fixed effects test also gives information about cross-section and period fixed effects tests, which are also separately valid, shown by statistics of 100.88 and 12.30 at 1% and 5% levels of significance respectively. The validity of cross-section fixed effects reveals that the firm-specific characteristics are helpful in explaining the relations between conformance and non- conformance costs. This result can also be confirmed in the different sub-sectors where each firm operates. Each firm in the sample belongs to another sub-sector of the food manufacturing industry; therefore, each has different managerial styles or phil- osophy. In fact, the panel regression method shows the benefit of taking the heterogen- eity of the firms into consideration. The validity of the time effect test shows that every year has a certain inner dynamics, which also helps to explain the relation between Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009 Total Quality Management 557 Table 2. Fixed effects panel regression of conformance costs on internal and external failure costs. ln (Internal failure costs) ln (External failure costs)   Constant term (a) 17.63 20.13 (3.54) (3.31)  ln (Conformance costs) ?0.39 ?0.64 coefficient (b) (0.27) (0.25) 2 R 0.95 0.98 Fixed effects test 2   Cross-section x 109.09 131.63 2  Period x 7.08 6.83 2   Cross-section/Period x 110.55 132.22 nt 42 36   Note: The standard errors have been shown in parentheses. The symbols and show the level of significance at 1% and 5% respectively. conformance and non-conformance costs. As a result, the changes that are due to the temporal effects all affect the sample firms in the same way. Estimation results regarding hypotheses H2 and H3 Table 2 shows the fixed effects panel regression results used for testing H2 (left column) and H3 (right column) after subdividing non-conformance costs into internal and external failure costs. As a result of the fixed effects panel regression of conformance costs on internal failure costs, it has been found that the Beta coefficient is ?0.39, but not statistically significant. Therefore, H2 has not been confirmed. However, a negative relation is found between con- formance and external failure costs with a statistically significant Beta coefficient of ?0.64, thus confirming H3. When these two results are analysed together, the negative relation between conformance and non-conformance costs found in H1 can be attributed to external failure costs rather than internal failure costs. As a result, the confirmation of 2 H3 also supports H1. The high R (0.98) shows that the variation in the dependent variable is explained by independent variables and the two-way fixed effects test has been found to be valid. Estimation results regarding hypotheses H4 and H5 Table 3 shows the fixed effects panel regression results used for testing H4 (left column) and H5 (right column). Fixed effects regression has been run to see the effect of prevention and appraisal costs separately first on internal failure costs, then on external failure costs. As shown in Table 3, none of the coefficients (except 1.24) have been found to be statistically significant. 2 Therefore, H4 and H5 have not been confirmed. In this case, the high R together with statistically insignificant coefficients can be a sign of multicollinearity problem. In fact, the correlation coefficient of ?0.72 found between prevention and appraisal costs is thought to be high enough to be a symptom of multicollinearity problem. This strong negative relation also follows the fact that once the quality system is properly installed, Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009 558 M. Omurgonulsen Table 3. Fixed effects panel regression of prevention and appraisal costs on internal/external failure costs. ln (Internal failure costs) ln (External failure costs)  Constant term (a) 12.64 ?0.54 (5.61) (2.86) ln (Prevention costs) (b ) ?0.20 ?0.12 1 (0.24) (0.12)  ln (Appraisal costs) (b ) 0.20 1.24 2 (0.32) (0.16) 2 R 0.95 0.99 Fixed effects test 2   Cross-section x 117.57 166.79 2  Period x 4.50 19.50 2   Cross-section/Period x 118.96 167.25 nt 42 36  Note: The standard errors have been shown in parentheses. The symbol shows the level of significance at 1%. then there will be less need for tests and inspections. The multicollinearity problem, to a great extent, explains why H4 and H5 have not been confirmed. Conclusion and discussion This study aimed to measure the quality performance of the leading firms of the Turkish food manufacturing industry in terms of quality costs. To fulfil this purpose, the quality costs measurement form has been designed especially for the food manufacturing industry, taking into consideration the changes and developments with respect to quality cost elements in the quality costs literature. The firms in the sample are the leader firms of their sub-sectors in terms of both market share and net sales. One of the potential benefits of this study for these firms is that in these firms, the quality costing system, which is useful to monitor quality costs, has been installed. Therefore, all these firms now have the chance of monitoring and controlling quality costs, which were previously the hidden part of the cost iceberg. Most of the quality managers of the firms visited have also acknowledged that they would begin to install the quality costing system as it has been suggested in the literature. Such acknowledgement implies that this study helped to create awareness in the Turkish food manufacturing industry in terms of the vitality and importance of the measurement of quality costs. Unlike previous studies made either with cross-section or time series regression, this study contributes to literature both because the panel regression method has been used in examining the relation between conformance and non-conformance costs and because this is the first time such type of study has been conducted in the Turkish food manufacturing industry. The results of the panel regression show H1 and H3 to be confirmed, which also accord with the basic premise of the traditional quality cost model suggesting a trade-off between conformance and non-conformance costs. H3 also supports H1 indicating that the negative relation between conformance and non-conformance costs can be attributed to external failure costs rather than internal failure costs. The reasons for this trade-off can be Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009 Total Quality Management 559 given as follows. First, the years examined (2000?2005) all coincide with the years in which the returns of the quality installation programme were taken in all the sample firms. It is also worth mentioning that the traditional quality cost model is more valid in the first years of installation of the quality programme. With the help of quality-based learning and the increased effectiveness and efficiency of the quality programme, confor- mance costs should decline over time without a corresponding increase in conformance costs. In a future research, the period examined can be extended to find out whether a tra- ditional quality cost or quality-based learning model is to be confirmed. The other hypotheses (H4 and H5) have not been confirmed. This means that when the conformance costs were subdivided to examine the effects of prevention and appraisal costs separately first on internal and then on external failure costs, the expected benefit of this action on non-conformance cost elements was not seen. The problem of multicol- linearity, manifesting itself with a strong negative correlation between prevention and appraisal costs, has been found to be an important reason in explaining this situation. This study has certain limitations and difficulties. It has found that the big leading firmsof the Turkish foodmanufacturing industry are not familiar with the concept of quality costs. In firms where the concept is known, the thinking has not been transformed into action. This is, also, unfortunately a symptom of poor connection between industry and universities in Turkey. The Turkish accounting system is not designed to record quality costs, which also represents one of the greatest obstacles in conducting such a study in Turkey. Within time, if firms begin measuring quality costs, there may be a need for a revision in the Turkish accounting system, which will assist in monitoring and recording of quality costs. It should also be kept in mind that all the steps to be taken towards the measurement of quality costs at either firm or industry level will, in the end, contribute to waste elimin- ation, which in turn helps firms to reduce costs and remain competitive. This fact is considered to be an important managerial implication. This study has also some other implications for future research. The future research can concentrate on other industries and countries to make cross-cultural comparisons. Acknowledgements This paper has been adapted from a PhD dissertation of the author entitled ?A research on the measurement of quality costs in the Turkish food manufacturing industry? (2007) at Hacettepe University, Department of Business School, Ankara, Turkey. The initial version of this paper was presented at the 12th International Conference on Quality and Productivity Research, Haifa, Israel, 10?11 July 2007. The author would like to thank Prof. Dr. Ulku Sisik, Prof. Dr. Aydin Oztan, Prof. Dr. Sitki Gozlu and Associate Prof. Tarkan Cavusoglu for their noteworthy comments. This study was partially granted by the Turkish Productivity Center. Notes 1. This cost element represents one of the developments in the quality costs literature associated with the costs of obtaining certificates like ISO 9000 and ISO 14000 (Simga-Mugan & Erel, 2000). 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A primer for panel data analysis. Retrieved May 11, 2003, from http://www.nyu/ its/pubs/connect/fall03/yaffee/primer.html Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009 562 M. Omurgonulsen Appendix 1. The conformance, non-conformance, prevention, appraisal, internal failure and external failure costs of the seven firms for the period 2000?2005 (expressed in New Turkish Lira). Non- External Conformance conformance Prevention Appraisal Internal failure failure costs Years costs (NTL) costs (NTL) costs (NTL) costs (NTL) costs (NTL) (NTL) A 2000 706,000 4,307,600 702,000 4000 1,352,600 2,955,000 2001 1,063,300 3,837,000 1,058,000 5300 1,032,000 2,805,000 2002 1,185,400 3,988,300 1,179,500 5900 1383300,00 2,605,000 2003 1,355,100 3,578,400 1,349,000 6100 1123400,00 2,455,000 2004 1,334,774 3,524,724 1,328,765 6009 1106549,00 2,418,175 2005 1,318,756 3,482,427 1,312,820 5936 1093270,00 2,389,157 B 2000 627,257 1,722,500 108,757 518,500 1,655,000 67,500 2001 623,573 2,905,500 125,073 498,500 2,840,500 65,000 2002 590,763 1,198,000 72,263 518,500 1,1360,00 62,000 2003 580,704 2,208,500 70,204 510,500 2,148,500 60,000 2004 588,987 1,945,500 86,487 502,500 1,895,500 50,000 2005 570,210 16,132,000 79,710 490,500 16,084,500 47,500 C 2000 458,133 894,657 318,613 139,519 532,769 361,888 2001 629,373 1,213,128 355,647 273,726 848,980 364,147 2002 710,834 1,348,867 373,497 337,337 996,352 352,515 2003 711,774 1,333,742 374,343 337,431 989,640 344,101 2004 694,170 1,265,972 370,881 323,288 952,582 313,390 2005 670,426 1,206,468 365,679 304,746 909,616 296,851 D 2000 168,600 244,000 103,600 65,000 232,000 12,000 2001 214,500 293,000 132,500 82,000 282,000 11,000 2002 241,500 267,500 154,500 87,000 259,500 8000 2003 287,000 232,000 175,000 112,000 224,500 7500 2004 244,500 177,500 160,500 84,000 171,500 6000 2005 232,275 168,625 152,475 79,800 162,925 5700 E 2000 291,454 454,541 282,454 9000 15,300 454,388 2001 437,703 711,008 424,703 13,000 12,424 698,584 2002 598,793 1,001,038 581,793 17,000 13,400 987,638 2003 165,144 1,650,711 135,144 30,000 15,920 1,634,791 2004 132,628 2,716,304 92,628 40,000 21,729 2,694,575 2005 243,057 3,498,551 192,057 51,000 36,715 3,461,836 F 2000 116,254 92,520 67,684 48,570 88,133 4386 2001 228,409 99,775 132,982 95,427 91,156 8619 2002 280,680 103,157 163,415 117,265 92,565 10,591 2003 278,299 103,003 162,029 116,270 92,501 10,501 2004 265,155 102,152 154,376 110,779 92,147 10,005 2005 249,916 101,167 145,504 104,412 91,736 9430 G 2000 347,000 152,000 150,000 197,000 152,000 0 2001 333,500 124,200 106,500 227,000 124,200 0 2002 443,800 111,000 155,800 288,000 111,000 0 2003 424,000 91,000 153,000 271,000 91,000 0 2004 462,600 108,000 132,600 330,000 108,000 0 2005 581,400 87,500 138,400 443,000 87,500 0 Downloaded By: [T BTAK EKUAL] At: 10:59 4 June 2009
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