Market evaluations of dimensions of design quality

Int. J. Production Economics 129 (2011) 292–301

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Market evaluations of dimensions of design quality Philippos I. Karipidis n Alexander Technological Educational Institute of Thessaloniki, Dept. of Agricultural Development and Agribusiness Management, 57400 Thessaloniki, P.O. Box 141, Greece

a r t i c l e i n f o

a b s t r a c t

Article history: Received 2 March 2010 Accepted 22 October 2010 Available online 27 October 2010

After a literature review on the economics of quality, we combine the value creation logic with the hedonic price function to analyze dimensions of design quality in enterprises. Viewing the quality-based organization as a collection of processes generating quality attributes and characteristics that constitute a solution for customers, we estimate market value as a measure of process economic performance based on objectively measured real economic data. The model can help to identify the relationship between design quality and market evaluations and to manage the quality of product and service at supply chain level. & 2010 Elsevier B.V. All rights reserved.

Keywords: Quality process Economic performance Design quality Solutions for customer Supply chain Value approach Price

1. Introduction Quality-based organizations choose to invest in improvements raising customer satisfaction with the expectation that they will yield increases in the enterprise’s profitability or revenue (Rust et al., 2002). Therefore, financial performance metrics for quality processes and quality projects are needed (De Mast, 2006; Schroeder et al., 2008). Although cost elements of quality and quality/cost tradeoffs have had much attention from scientists (Dale and Plunkett, 1999; Chiadamrong, 2003; Yang, 2008), to our knowledge, there are no studies indicating that the existing economic methods and their applications to explain and support quality decisions at the firm level are adequate. This has recently been confirmed by some authors. For instance, Freiesleben (2008) highlights that existing economic models cannot provide managers with a measure of how the quality of a production unit affects their company’s profitability. Due to enterprises operating in an environment that is more complex than and different from what it was in the past, the need for more strategic thinking and proactive behavior, and the more aggressive and complex nature of these enterprises’ overall strategies (Rainey, 2008), managers cannot content themselves with the existing economic methodologies for quality management. Setijono and Dahlgaard (2008) ascertain this view and point out that the existing methodologies have been criticized as reactive rather than proactive. In accordance with this, some time earlier, Evans (2004) highlights the need for better approaches for analyzing economic performance results in addition to the need for

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incorporating competitive comparisons in an organization’s performance review processes. Sousa and Voss (2002), looking at this necessity from a different angle, indicate managerial areas that need more theoretical development. For instance, they propose for the quality management field to establish links to more theoretically developed fields and to engage in more theory-testing research through replication studies and testing existing theories in new settings. In qualitymanagement approaches such as total quality management and Six Sigma, customer input is critical at the organization and project levels. At the organization level, it is critical in establishing which processes and products (or/and services) are in need of strategic improvement and at the project level in defining those quality attributes and characteristics that are critical-to-quality factors (Schroeder et al., 2008). Because a significant change in the fundamental concepts in the new version (2010) of the EFQM Excellence Model is the shift from the ‘‘customer focus’’ on ‘‘adding value for customers’’, an important field for further research emerges. The value proposition provides a comprehensive view of what the enterprise delivers to its customers (it creates value for customers) and constituents, and value maximization is a powerful guiding philosophy for enterprise decision-making (Besanko et al., 1996). Because improvements in the quality of products and service that enterprises offer can add value for customers, managers can rank these improvements by measuring the valuation of these improvements by the market (market value); therefore, it helps them to choose the most efficient improvements and explore quality opportunities. The aim of the present paper is (1) to review the existing literature concerning the economics of quality to establish a link to the value-creation approach and (2) to test the appropriateness of the value-creation approach in formulating a

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quality strategy by choosing the set of processes and activities that contribute to the achievement of enterprise-quality targets. More specifically, the estimation of the value that each quality-related process or activity creates enables enterprise management to know its economic performance and to rank the processes (and activities) according to their contribution to the value that an enterprise creates. The main contribution of this article is to adopt the valuecreation approach, to test the fitness of an economic model (hedonic price model), and to estimate the market value of the quality processes and activities. We thus establish links between quality management and a theoretically more developed field and test an existing economic theory in a new setting. In the rest of the paper, we present a literature review on economic concepts, models and measures of quality, distinguishing them into two categories: ‘‘quality cost’’ definitions and models and frameworks built around ‘‘benefits for customers’’. We then ascertain the failure or inefficiency of the existing models to estimate the economic performance of quality processes and the impact of quality plans and actions on enterprise revenue or profits, and then we adapt the value-creation approach and propose the conceptual framework. Next, we empirically investigate the hedonic price model in a certain market, such as the food market. Then the estimation of the model followed by the results and discussion are presented, and, finally, the conclusions and propositions for future research are provided.

2. The economic quality models—a literature review Because the grand corporate strategy focuses on creating value in the present and the future, we adopt the value framework developed by Besanko et al. (1996). According to this, as goods move along the vertical chain, value is created by production and marketing functions such as manufacturing, procurement, storing, packaging, labeling, transporting, information providing, and selling. Fig. 1 indicates a simple supply chain including three enterprises as players: a raw material provider, a manufacturing– wholesaling firm, and a retailing firm. Viewing these enterprises as value-creating organizations, we examine the case of the retailing firm, which provides value for the ultimate customers giving them the possibility to choose a product of a certain quality package that meets or exceeds their needs or expectations. Customers derive benefits from this package and pay a price for it. This quality package, also named the ‘‘solution’’ (Rainey, 2008), can be composed of the quality attributes and characteristics of the finished product and service that accompany it, for example, in the case of a bottle of wine, the wine color and alcohol content, the package size and the bottle design, accompanied by the service determining the time at which it becomes available to the customers in a certain place. Value for customers is thus augmented by decreasing the prices they pay, by increasing the benefits offered to customers, or by doing both. This can be attained by two main categories of primary considerations and effects: investments and transformations through value-adding

Raw materials ...............................................................Finished products Production

manufacturing & marketing

Retailing

Customer’s Value Sacrificed value

B

C Value created

VC

Fig. 1. Value creation along the vertical chain per product unit.

C U S T O M E R S

293

processes/activities (Besanko et al., 1996; Rainey, 2008). For example, developing a total quality management (or Six Sigma) project can create powerful opportunities to enhance value creation for customers and stakeholders and to sustain the success of an organization through investments in training and process transitions. We assume that the value the final customer (consumer) derives by the product/service is reflected by the perceived benefits, B1, and that the cost, which is the value sacrificed to be converted a raw material into finished product and to be marketed until the ultimate customers, is represented by C. The value created (VC) per product and service unit by a supplier is equal to the difference between the value the customers derive from the product they choose for a certain use and the value that is sacrificed to produce it and to make it available to customers in a certain place and time: VC ¼ BC:

ð1Þ

Therefore, the quality advantage that the enterprise builds can be based on quality-related cost reductions enabling the lowering of price customers pay for a certain quality package and increases in the benefits for customers or both. To adapt this framework, we could imagine an enterprise as a player in the vertical chain. Accepting the interpretation that the enterprise provides solutions to meet customers’ needs, wants and expectations, it can be a producing or marketing firm that attempts to maximize the total value it creates. Viewing it as a quality-based organization that creates value through the quality-related improvements, the value it creates depends on the perceived benefits the solution provides to customers and the quality-related costs of production and marketing. Therefore, the economic concepts and models concerning the quality costs and the perceived benefits of a product/service quality constitute the frameworks and methods being appropriate to study value creation and thus its impact on a firm’s revenue and profit. Defining the quality of an enterprise as internal and external and assuming that internal quality is composed of design and conformance quality (Fynes and Voss, 2001); we focus mostly on design quality, which is becoming increasingly important for market success. 2.1. The value sacrificed for quality According to Freiesleben (2008), the discussion on the economic concepts of quality began in 1986 study by Porteus (1986), who proposes a model to capture the relationship between quality and production economics by examining the impact of defect rates on optimal lot sizes and one-shot preventive investments. Ever since, a large number of researchers have presented definitions of quality cost components, and some others have proposed models estimating quality costs. For example, Dahlgaard et al. (1992, 1998) suggest a classification of quality costs into internal/external and visible/ invisible costs, and Sandoval-Chavez and Beruvides (1998) extend the Prevention–Appraisal–Failures (PAF) quality cost model, adding opportunity costs. Chiadamrong (2003) presents an empirical model of the economics of quality as a function of two main components: traditional prevention-appraisal-failure expenses and hidden-opportunity quality-loss costs. This process-cost approach enables tracking costs normally associated with production in addition to those traditionally associated with the quality. Some other quality cost methods have also been proposed for special purposes, such as the time-based cost element method, the department-based quality cost analysis, the team-based quality cost analysis, and a process cost model, which is described in Dale 1 These should be thought of as the perceived gross benefit of the product and service, which depends on the product and service’s attributes and characteristics.

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and Plunkett (1999). Yang (2008) develops a new conceptual system of quality costing. He refines the traditional categories of quality costs (‘‘Prevention–Appraisal–Failure’’/PAF) and hidden costs through the addition of two new categories: ‘extra resultant cost’ and ‘estimated hidden cost’. Using this new categorization, he provides a detailed classification of the items of quality costs along the product life cycle. Failure Mode and Effects Analysis (FMEA) is used within a company’s risk management program. Its objective is to prevent unacceptable failures from reaching the customer and to assist management in generating a more efficient allocation of resources. With respect to the FMEA, Gilchrist (1993) proposes a cost-oriented modification. He stresses the seriousness of faults to the customer in terms of two cost situations: if the customer detects the fault on the delivery of the product and if the customer does not. Von Ahsen (2008) proposes a mode of integrating FMEA to estimate the cost of faults that are not detected before the product is delivered to the customer. This cost-oriented FMEA allows for a weighting of potential improvement activities according to the associated costs. The above-presented quality cost models and the approximations give us useful measurements and metrics and can contribute to estimating and analyzing the value that is sacrificed in the valuecreation approach. Because these models cannot contribute to the estimation of the benefits customers derive from product and service quality, they cannot enable the estimation of firm revenue and profit.

2.2. Value provided to customers The need for economic frameworks that connect internal quality dimensions with the customer’s buying choices or the market has attracted the interest of many researchers. Some of them implement the quality loss function – the economic consequences of deviating from the quality target point – conceptualized by Taguchi. This function is a helpful tool in quality engineering during the stage of new product development, when tolerances are set and quality targets are established, but it is not sufficient for the enterprise decisions aiming at maximizing economic performance and profits. Therefore, Taguchi and Clausing (1990), appreciating this insufficiency, highlights that they do not eliminate any other approximation of a quality loss function depending on the corporate possibility of tracing cost data. Therefore, a number of authors in an attempt to address this gap approximate this function in certain cases of goods. At the same time, Tang (1990) studies the economic performance of the deviation of a product from the quality target. He views profitability as a result of the deviation from the quality target point and investigates the situation in which the items produced by a production process are sorted into two different grades sold at two price levels. He develops two separate models using a performance variable and determines the optimal grading specifications that maximize the expected firm profit. The product price is incorporated in these models as an index for helping the estimation of the profits for the two grades. This model helps to estimate the impact of product robustness on product price and, subsequently, enterprise profits, but it does not stretch out the impact of the different packages of quality attributes and characteristics and different quality levels on price and profits. Sometime later, Ganeshan et al. (2001) gave a new approximation of the quality loss function studying the interaction between the economics of production and process quality. Their main contribution comes from the fact that the optimal quality solution includes the effect of Taguchi’s estimated losses. Specifically, they investigated investment in a process to decrease its variability. Their model determines the optimal levels of inventory and the

production lot size that minimizes the sum of inventory and quality-related costs. Kethley et al. (2003) adopted the quality loss function in the case of real estate to estimate separate measures for house characteristics. They estimate a loss function for each characteristic and then weight the functions by the relative importance of the customers to estimate a single price allowing comparisons between houses. Although the above implementation helps more than the simple loss function’s approximation, they do not enable the enterprise to estimate the customers’ benefits in monetary terms that is revenue or profit. Later, Fleiesleben (2005) highlights the lack of a comprehensive economic explanation of the financial benefits of different qualityrelated improvements. In his article, ‘‘The economic effects of quality improvement’’, he suggests the complementation of the empirical base of cost of quality studies with a general cost logic. He combines the cost argument and price argument in an attempt to represent the situation in which a business produces a product of better quality than another business and explains the reason for why a rational consumer chooses one product as being more robust than another. Although this suggestion extends the existing models, it does not provide sufficient help for the analysis of the real market situation, where most suppliers offer products of different qualities in different quality packages and quality levels and customers’ willingness to pay price premiums is different for each package of quality characteristics. In a recent article, Freiesleben (2008) returns to his view that the previous economic concepts of quality, such as the widely cited costof-quality model, present an incomplete perspective of the economic effects of quality. He proposes a new type of quality loss function called the ‘‘economic quality loss function’’ by developing the market share function of a producer, assuming a linear relation between customer utility and quality. This function helps to estimate the market share of a product as a result of benefits that its quality produces for customers. The main weakness of this model is that it does not take into account the prices of different packages of quality attributes and characteristics, in the complex (real) market situation. Therefore, the same author (Freiesleben, 2010) proposes a conceptual model and gives a framework for a rather holistic assessment of quality, defining design quality as the degree to which products in a certain market segment meet customer needs in that segment. He finds that deviations from both optimal feature composition and optimal production technology likely result in losses similar to those commonly attributed to poor production quality. The main contribution of this proposition is to estimate the effects of undershooting and overshooting the optimal feature composition on matching customer needs and price. The proposed framework can contribute to the identification of the direction of the impact of a quality dimension on price, but it needs to be combined with an economic model to account for the quality impact. The relationship between design quality and customer satisfaction and business performance is also addressed in a few empirical studies in the fields of quality management and marketing. For example, Rust et al. (1995) devise an approach that quantify the market share implication, the net present value of the profit and return on quality of quality expenditure, and Rust et al. (2002) examine the effectiveness of revenue expansion and cost reduction of quality efforts. Fynes and Voss (2001) and Fynes and De Burca (2005) develop a path model incorporating quality practice, design quality, conformance quality, external quality-in-use, product cost, time to market, customer satisfaction, and business performance. They confirm the influential role of design quality on other measures of quality performance reducing cost, improving quality in the marketplace and in terms of competitiveness. Setijono and Dahlgaard (2008) investigate the perceived value of quality improvements as an indirect measure of the return on quality improvements. It indicates whether business quality

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efforts give higher, consistent or lower returns. More specifically, they suggest a methodology to measure the impact of quality costs on customers’ perceptions regarding the ‘‘value of the product’’. Their proposition is based on the changes in the prevention– appraisal and failure costs, the customers’ perceptions regarding the quality of the company’s product or service, and the consumers’ cognitive judgment as measured by single- or multi-attribute scales. A serious defect of the above methods is that idiosyncratic and relative natures make evaluations subjective, ambiguous, and difficult to define (Khalifa, 2004). As a result, consumer’s judgment is a subjective construction expressing customers’ expected behavior and not the actual behavior, and the results cannot reflect the customer’s actual buying preference. In addition, it cannot help to estimate a firm’s revenue and profit in monetary terms. These defects also apply for those studies based on other kinds of respondents’ judgments in terms of, for example, enterprise marketing and management. The hedonic price approach, introduced by Rosen (1974), is recognized as one of the most appropriate tools to estimate the market value of product or service quality. This method is based on the (hedonic) hypothesis that goods are valued in the market for their utility-bearing attributes and characteristics. It facilitates the analysis of the price structure of a commodity in relation to its specific attributes and characteristics through the estimation of product attributes and characteristics’ shadow prices. Hedonic prices are defined as the implicit prices of attributes or characteristics and are revealed to economic agents from observed prices of products and services and the specific amounts of attributes and characteristics associated with them. In long-run equilibrium, the hedonic price function represents the maximum price at which attributes and characteristics can be purchased and the minimum price at which they can be supplied. This equilibrium helps to highlight how sellers determine the value of the products they offer and how consumers value the products they buy. We can thus estimate the market value of quality attributes and characteristics, regressing them to the observed prices in the market. This enables enterprise management to estimate the expected change in revenue as a result of a change in different quality attributes and characteristics; this is the main advantage of the theory. There are a large number of hedonic price studies in different goods and markets in the last two decades, such as food, beverages, farmland, land, energy, house, automobiles, newspapers, environment, and production inputs. All of these investigations aim at estimating the market value (or implicit prices) of quality attributes or characteristics for certain goods or at estimating quality-adjusted price changes in some cases. Because previous studies examine the hedonic hypothesis in the fields of the input and output markets (backward and forward corporate linkages), they are helpful for marketing decisions, such as new product development and pricing. In our view, there has been no attempt to adopt this model to study internal quality questions concerning the design quality, especially process quality and performance, and the evaluation of quality plans and actions. The main contribution of this study is to test the appropriateness of the hedonic price model in combination with the value-creation logic in design quality choices identifying key processes, which participate in market-value creation. This method can be implemented in the entire market or in a certain market segment, and it analyzes enterprise choices to achieve a competitive advantage, building it on a broader quality basis by adopting the solution concept than the product only. We thus establish a link between quality management theory and the economic theory of market value, adapting the value creation logic and hedonic price theory in a new setting.

295

3. The hedonic price framework The development of a hedonic price model is based on the assumption that products and services consist of sets of attributes and bundles of characteristics. This model itself amounts to a description of competitive equilibrium on a plane consisting of several quality dimensions on which buyers and sellers are located. The class of goods under consideration is described by n objectively measured attributes and characteristics. Therefore, any location on the plane is represented by a vector of coordinates Z ¼(Z1,Z2,y,Zn), with Zi representing the amount of the ith attribute or characteristic contained in the considered good. There exist a wide variety of alternative packages of attributes and characteristics, and transactions are equivalent to tied sales when they are thought of as bundles of attributes or characteristics. In particular, a price P(Z) ¼P(Z1,Z2,y,Zn) is defined at each point on the plane and guides both the locational choices of both consumers and producers/marketers regarding packages of attributes and characteristics bought and sold. According to Rosen (1974), the hedonic supply function can be expressed as Pi ðZÞ ¼ Gi ðZ1 ,Z2 ,. . .,Zn ,YÞ,

ð2Þ

where Pi is the price of product i in the market and Z1,Z2,y,Zn the product’s attributes and characteristics. Y is an exogenous supplyshift variable. In cases where no differences in cost among firms exist, Y can be dropped out of Eq. (2). Otherwise, it is possible to consider factors affecting the cost. In our study, we incorporate Y representing quality-related expenses for supplying a certain quality package—the solution (Rosen 1974; Besanko et al., 1996).

4. Conceptual framework—the value creating organization Hedonic price theory assumes the firm to be a collection of atomistic production establishments, each of them specializing in one product design (certain package of attributes and characteristics). For optimal design, the marginal revenue from additional attributes and characteristics equals the marginal cost of production per unit sold. Furthermore, quantities of attributes and characteristics are supplied up to the point where the unit revenue equals the marginal production cost, evaluated at the optimal bundle of attributes and characteristics. Our departure from Rosen’s suggestion is that we view the enterprise as a collection of quality-bearing/value-creating organizations, and we proceed to think that each quality organization consists of a collection of m quality-related processes (Fig. 2). These processes create value, transforming inputs into outputs at both the firm level and the supply chain level. For example, the marketing process supplies a product of certain form and quality labeled properly in a certain place and at the time when customers demand it. Because each process can be divided into activities and subactivities, the output of a process is composed of one or more attributes/characteristics of product/service quality, which are the outputs of its activities/sub-activities (Fig. 2). For example, the output of product-labeling activity, which is an activity of the marketing process, is a product classified in quality category I and is labeled by signal I; we thus say that it generates the presence of the quality signal I attribute. If the final customer values this product labeled by the ‘‘category I’’ signal positively, we say that the labeling activity/sub-activity creates value for him/her. We thus relate the processes/activities with the attributes/characteristics of the products and services and identify the relationship between design quality and market evaluations. Adopting the solution concept, we view a quality-related organization to be extended at the supply chain level and to

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Activity 1 (labeling) PROCESS 1 (marketing)

S-activity 1 (category I) S-activity 2 (origin)

Activity 2 (time selection)

PROCESS 2 (procurement)

Activity 1 (supplier selection)

VALUE OUTPUT (solution) Attributes & Characteristics

Benefits Sacrifice

Quality Costs

C U S T O M E R S

PROCESS 3 (retailer capabilities)

PROCESS m

Fig. 2. Value for customers created by the quality bearing processes in supply chain.

become an inter-firm quality-bearing (production and marketing) organization. We now examine the simple situation where this quality organization is supplying a package of attributes and characteristics for which it is best suited. We also assume that there exists a second quality organization supplying the same quality package (solution) but at different quality-related cost conditions. Factors that can differentiate cost conditions include input prices, human capabilities, knowledge, technology, and quality-specific R&D expenditure. For example, the labeling activity requires a combination of specific resources (human, knowledge, information, machines, and materials) in the production and marketing operations, and it describes the product/service quality accurately. These resources can reduce expenses such as quality control, time loss, and search efforts for buyers and sellers, lowering the transaction costs across the vertical chain. Therefore, if the total quality-related cost is reduced at the supply chain level, the ultimate marketer (retailer) can sell the labeled product at a lower price, and we say that labeling activity creates value by reducing the value sacrificed for a certain package of attributes and characteristics. The main contribution of this study is that we use a hedonic model, viewing a quality organization as a collection of processes and activities in the supply chain and the output of this organization as a package of attributes or characteristics offered in the market. In addition, we assume that processes/activities differentiating the quality cost conditions are also value creating, as they lead to the reduction of the value sacrificed for a certain package of attributes and characteristics offered and to the price lowering in long-run market equilibrium. We can thus examine both types of processes: those that increase the value derived by the customer (benefit) from the product and service and those that reduce the value sacrificed to offer a certain package of quality attributes and characteristics to the customers. Because the results of such a study account for market evaluations in the typical market (whole or segment) situation and not customer evaluations only, they allow

enterprises to identify quality processes and activities that can help to outperform their competitors and thus achieve a competitive advantage based on design quality. It also gives enterprises an economic base for benchmarking by identifying the value enterprise can creates, that the customers need, want or expect and thus achieve a competitive advantage based on conformance quality in addition. We choose to specify the value-creation framework by estimating the hedonic price function in a case enabling us to incorporate product and service attributes and characteristics at the supply chain level; such is the case of a seasonal food. Taking a food marketing enterprise as a player in the supply chain, we assume, for simplicity, that its quality-related organization includes two core processes (marketing and procurement) that can create value by increasing the benefits for customers or by lowering the qualityrelated costs sacrificed for a certain solution. The marketing process is a process at the interface between the business organization and the external environment (market), in which it trades products (foreword linkage). This process can include a set of activities such as the choice of selling time and product labeling. The later can be divided into two sub-activities, producing the product quality category signal and the product origin signal. The procurement is also a core process at the interface between the business organization and its external environment (backward linkage) in which it trades and operates. It includes activities such as the evaluation of the supplier of raw material, which leads to the selection of a supplier. The food marketing enterprise seeks to maximize the value it creates for customers. This value creation can be capable by redesigning existing processes and activities and introducing new processes or activities or eliminating old ones. Therefore, enterprise must identify the value that the processes or activities create. If there is market value for a quality process or activity in the above-mentioned notion, there is an incentive for enterprise to examine it to be included in the set of internal improvements.

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A higher market value of an attribute or characteristic, which is the output of a process, implies that a higher value is created by this process, and we can assert that a greater incentive for the enterprise to increase the output of this process exists if we compare it to the related quality costs.

5. Empirical investigation of the market value framework We choose to empirically investigate the presented framework, in the case of food commerce, including products that are vulnerable and bulky. Because the cost of transaction is higher in these products, it enables us to implement the model in a setting with a wide range of processes creating value by both providing benefits for customers and lowering quality costs for a certain package of attributes and characteristics. We assume a typical retailing firm selling food products to the ultimate customers (consumers) because at this point of the supply chain, the value created reaches its maximum level (maximum number of quality attributes and characteristics). Therefore, the results can be more useful for all players along the vertical chain. 5.1. Model specification Following Stanley and Tschirhart (1991), consumers gain utility from the attributes and characteristics of the solution available to them. Therefore, utility is provided by the product labeling activity using quality category and product origin signal. It contributes to an accurate product quality description and, as we explain below, it lowers transaction costs in the supply chain. Utility is also provided when a product is made to be consistently available. An example of this is the retailer to make a seasonally produced product available at a time out of the main production season when the consumer needs it. Attributes and characteristics, being positively or negatively evaluated in the market, are factors that impact the price and constitute the quality of the product (quality category) and the quality of services (selling time). Therefore, it is possible to estimate the market value of the outputs of the processes and activities, which are the quality attributes and characteristics. Some definitions are given below for the impact of quality processes/activities under consideration on product price and subsequently on market value. 5.1.1. Marketing process As we have highlighted above, the marketing process can be a collection of three activities/sub-activities: product labeling by quality category, labeling by product origin, and the selection of the time of selling (Fig. 2). Labeling by quality category presupposes grading, which is the sorting of dissimilar products into uniform quality categories according to quality standards. It makes possible the sale of products by sample or by description and generates more accurate market information. The use and communication of uniform quality grades (quality categories) to customers lowers search and transaction costs incurred by both buyers and sellers and fosters a more efficient price-discovery situation, contributing to both operational and pricing efficiency (Kohls and Uhl, 2002; Fearne et al., 2003). The information provided to customers by the product label is expected to impact the cost of a certain quality package and, according to Rosen (1974), to lead the market equilibrium to a lower price level in long run. We thus expect that the labeling activity creates value by lowering the cost of the supplying a solution, and as a result, we expect the labeled product with the category I signal to have a lower price (qP/qZ1 o0). If the food-marketing enterprise collects raw material (primary product) from the same region, it can attain more consistent product quality as an output of the same production conditions. Therefore, the

297

labeling activity by the product origin signal and the communication of it reduces transaction costs and is thus expected to result in lower prices (qP/qZ2 o0) in the long run. As we stated above, the time that a product of a certain quality package becomes available to customers by the marketer is a service quality characteristic. Food suppliers attempt to provide customers products of a quality that meets or exceeds their needs or expectations at the time they need them. Some products are seasonal in their production because of factors such as climate. When a food product of a certain quality is produced in the main production season, it needs certain inputs, but as the season progresses apart from the central point of the main production season, the inputs and thus the costs of attaining the same quality of product increase. Higher quality-related production costs, in combination with additional services provided by the retailer to customers to be the product available out of the typical season, lead the market equilibrium to a higher price level and consequently to a higher product price. We thus expect the deviation of selling time from the main production season to positively impact the price of a certain quality package (qP/qZ3 40). 5.1.2. Procurement process (suppliers’ selection/vertical integration) The procurement process involves complex and crucial decision-making. It can include the evaluation and selection of suppliers and probably the elimination of one or more intermediate suppliers. The latter leads to the vertical integration of production or marketing processes, and it can produce savings in areas such the product quality maintaining and communicating at the supply chain level. These savings are expected to be higher in perishable products because of the high storage and distribution expenses concerning the preservation of product quality. That is, a firm with two functions, such as wholesaling and retailing, can reduce costs to maintain an identical set of quality attributes and characteristics. Additionally, selecting suppliers can result in receiving more similar products and reduce expenses, such as quality-control actions. Therefore, when a retailer purchases products directly from raw material providers (here farmers), eliminating the intermediates or wholesalers, it can reduce the supply costs of a certain quality package. As a result, we expect the selection of suppliers (activity), which is the leading step in vertical integration, to create value by lowering the costs of a certain quality product package. Therefore, we expect the solution of a certain quality provided to customers to have a lower price (qP/qZ4 o0). 5.1.3. The form of retailer Changes in shopping patterns and preferred retail formats in combination with the dominance of some major retailers in the marketplace have resulted in the appearance of new retail formats. In the simplest situation, we can identify three venue types: major shopping venues, secondary shopping venues or convenience stores, and specialist shops. Here a major retail supplier (super market) can attain higher cost savings in providing solutions to customers and be more efficient through, for example, achieving economies of specialization and labor division. As a result, we expect major retailers to negatively impact product prices for a certain quality package (qP/qY1 o0). After the above definitions and specializations, we build the hedonic model, including five independent variables. Assuming linear relations between the dependent and independent variables, we take (3) PðZÞ ¼ a þ b1 Z1 þ b2 Z2 þb3 Z3 þ b4 Z4 þ b5 Y1 þ u1 ,

ð3Þ

where a is the constant term and u1 is the disturbance term, that captures unobservable and missing attributes and characteristics, measurement errors, and unknown factors.

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Table 1 Processes/activities, outputs, expected signs and measurements. Process—activity

Attributes—characteristics

Expected sign

Character

Measurement

Labeling

Category I signal Z1 Origin signal Z2 Out of season Z3 Raw material provider Z4 S. Market Y1

  +  

Dichotomous Dichotomous Continual Continual Dichotomous

0–1 0–1 0–6 weeks 0–100% 0–1

Time selection Supplier selection Retailer form

Table 2 Results of the econometric estimation for the three product cases. PROCESS—activities

C Category I signal Z1 Origin signal Z2 Out of season Z3 Raw material provider Z4 S. Market Y1 R-squared Adjusted R-squared Durbin–Watson stat F-statistic Prob(F-statistic)

Model 1—Peach

Model 2—Nectarines

Model 3—Tomato

Coefficient

t-Statistic

Prob.

Coefficient

t-Statistic

Prob.

Coefficient

t-Statistic

Prob.

2.191418  0.178139 0.192003 0.086825  0.003190  0.152702

11.79867  2.141555 1.060892 3.257889  2.072449  1.686858

0.0000 0.0342* 0.2908 0.0014* 0.0403* 0.0941* 0.258550 0.229127 1.796529 8.787448 0.000000

2.438781  0.198225 0.211273 0.020911 0.000214  0.329110

14.55903  2.322324 1.410415 0.591878  0.143474  3.420912

0.0000 0.0218* 0.1609 0.5550 0.8861 0.0008* 0.171760 0.138364 1.457649 5.143027 0.000254

1.592391  0.187198  0.340319 0.054096  0.000939  0.265246

8.131214  1.516913  3.454439 1.479484  0.672981  2.722620

0.0000 0.1309 0.0007* 0.1406 0.5018 0.0071* 0.099758 0.076314 1.673148 4.255208 0.001082

Table 1 presents the processes/activities with their outputs (quality attributes and characteristics), the variables representing them, the expected signs of each variable and its measurement. The independent variable that represents the product’s labeling by the quality category (Z1) is a dichotomous one and takes the value of one if the product is labeled by a category I signal and zero if product is not labeled. The variable representing the product labeling by origin signal (Z2) is also dichotomous, taking the value of one if the product is purchased and labeled by a certain region and zero if the product’s origin is unknown. The time of selling selection variable (Z3) is measured by the weeks before or after the central day of the within-season period. The variable relevant to procurement (Z4) represents the share of procurement utilized by raw material providers (farmers) and takes values from 0.05 to 1.0. A dummy variable (Y1) is introduced in the model that equals one if the product is sold by a major retailer (super market) and equals zero in any other case.

5.2. Model estimation and discussion Data for the model estimation were obtained by a survey developed in the spring of 2008. A questionnaire was pre-tested, and a table was ultimately scheduled, which was filled in by visiting 210 representative retail shops in the metropolitan areas of Athens, which is the capital city, and Thessaloniki, which is the secondlargest city in Greece during the summer and fall of 2008. The data were gathered and recorded on the tables by observing all of the labels of fresh food product varieties on the retailers’ shelves. Finally, sets of usable observations were gathered for three perishable products with seasonal character (peaches, nectarines, and tomatoes). The estimation of the model (Eq. 3) was introduced, using the ordinary least squares method (OLS) for the 241 sets of peach observations, 238 sets of nectarine observations and 330 sets of tomato observations. We used EViews to estimate three equations for the above-mentioned products. The hypothesis for homoscedasticity in error terms was rejected, and a test for the correction of heteroskedasticity was applied. The results of the

model estimation (variable coefficients, t-statistics, and probability values) are presented in Table 2. The value of the F-statistic indicates that all of the independent variables significantly affect the dependent variable in the three models. At the 10% confidence level, the results indicate that four out of the five estimates in the first model are statistically significant and that two out of the five estimates in the second and third models are statistically significant. The results indicate that the product category negatively impacts the retail product price, as expected, in the two cases, and that the product’s origin negatively impacts price in one case. We thus conclude that the product labeling activity through the product-category signal and the product-origin signal lowers transaction (quality related) costs and leads to value creation by reducing the sacrifice of expenses of a certain quality package. The time out of the typical season that the product of a certain quality becomes available to customers by the retailing outlet positively impacts the retail price, as expected, in one case. This implies that the service quality activity of time selection crates value by increasing benefits for customers. The supplier evaluation and selection activity, leading to the direct purchases of a product by raw material providers (farmers), thus eliminating the intermediate wholesalers, negatively impacts the product price in one case. It implies that the activity of selecting suppliers creates value by lowering quality expenses for a certain package of product attributes and characteristics when the intermediate wholesalers are eliminated. Finally, we see that taking the form of a retailer (negatively) impacts the product price in all cases. This implies that when the retailer is a major one (e.g., a supermarket), the price of a certain quality package of the product is lower than in other cases, where the retail establishment is a greengrocer, a minimarket or a grocer.

5.3. Elasticities for quality attributes/characteristics A further exploration of the results presented above is possible for the relationship between design quality and market evalua-

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299

Table 3 Elasticities of quality processes—activities outputs. Peach

Category I signal Z1 Origin signal Z2 Out of season Z3 Raw material provider Z4 S. Market Y1

Nectarines

Tomato

Mean

Elasticity

Mean

Elasticity

Mean

Elasticity

0.2901 0.8889 3.8889 10.9783 0.3251

 0.0228* 0.0755 0.1493*  0.0155*  0.0220*

0.2581 0.8599 3.7178 11.5847 0.3112

 0.0512* 0.0811 0.0777  0.0011  0.0460*

0.3105 0.6306 3.2447 12.4694 0.3716

0.0467  0.1724* 0.1755 0.0094  0.0792*

tions by estimating the elasticities for quality attributes and characteristics. These elasticities represent shadow values of the outcomes of the quality-related processes and activities/subactivities and are not demand elasticities. These are counted as mean-weighted indices estimated by the mean value of the corresponding independent variable multiplied by the b coefficient and divided by the mean value of the dependent variable (ei ¼biZi/P). Table 3 reports the estimated elasticities for the three product cases with their corresponding processes and activities/sub-activities. Through these values, enterprise management can rank the quality processes and activities according to their contribution to the total value creation. For instance, the  0.0228 elasticity in the product category in the first model implies that a 100% increase of the output (peach) of the labeling activity by the category I signal (duplication of the category I—labeled product) leads to a 2.28% decrease in the average retail price paid by the customers. Because this percentage can represent the mean reduction of the value sacrificed at supply chain level in the case of labeling the product with the category I signal, keeping all other attributes and characteristics constant, we can estimate the economic performance of the labeling activity/ signaling sub-activity and thus the economic performance of the marketing process (Fig. 1). Assume that a marketing enterprise offers in the market a solution with a certain quality package and sells it at a meanweighted retail price P. The enterprise output includes a share of food (peach) labeled with the category I signal at q¼0.2901 (29.01%), and we suppose that the management aims to increase the labeled product of category I, keeping all other quality attributes and characteristics stable. If the labeled product of category I increases by 100%, that is, that the share of the labeled product in the total output becomes 2q¼ 0.5802, and the enterprise sells it at a mean-weighted price PI such that PI o(1 0.0228)P, it outperforms its typical (mean) competitor. This implies that if the enterprise applies a quality project focusing on the duplication of a labeled product it must also lower total expenses at the supply chain level and the price consumers pay for the same quality package by r2.28% to eliminate the risk of profit and revenue losses or to increase the revenues. Contrary to this, the 0.1493 elasticity in the time selection of peaches (broadening the time of product sales) implies that a 100% increase in the time that the product of a certain quality package becomes available to the customers is connected to a 14.93% increase in the price paid by the customers. More specifically, if the enterprise implements a design quality project to increase the amount of time it sells the product out of the main season, and it goes from a mean time t E3.89 weeks into 2t ¼7.78 weeks, it can attain an increase in the mean-weighted price by 14.93%. If the enterprise broadens the time as explained above and holds its total expenses to a level that enables it to sell the certain quality package at a price below P+ 0.1493P¼1.1493P, it can outperform its typical competitor. Keeping all other attributes and characteristics unchanged, the alternative choices an enterprise faces in its decisions concerning the time expansion as a service quality characteristic, are summarized as follows: (i) The time expansion

is equal to the price increase. In this case, the solution enterprise provides to customers is equally attractive than previous and it can keep sales and revenue unchanged. (ii) The time expansion percentage is higher than the price percentage increasing. In this case, the total solution that the enterprise provides to customers is more attractive than what was previously provided, resulting in an increase in sales and revenue. (iii) The percentage increase in the time expansion is lower than the percentage increase in the price. In this case, the solution that enterprise provides customers is strictly less attractive than it was previously, making it impossible to sustain its sales and revenue. In addition, if the enterprise accounts for its activity/characteristic-related costs, it can estimate the profit margins and profits for each choice concerning the time expansion. Therefore, it will be asserted that the enterprise management can rearrange the ‘‘solution’’ offered to consumers efficiently by changing the service quality characteristics it contains.

6. Concluding remarks and propositions for future research In this article, after a review of the existing literature on the economics of quality, we adapt an economic framework to study the relationship between the design quality and market evaluations. In our adaptation, we view the quality-based organization of an enterprise as creating value for customers. This organization is a collection of quality processes and activities/sub-activities; each of them gives a quality attribute or characteristic as an output. The package of quality attributes and characteristics offered by the quality-based organization constitute a solution for customers and is valued in the market as bearing utility. Combining the value-creation logic with the hedonic price model at the supply chain level, we estimate the market value of the (product and service) solution attributes and characteristics. It thus became possible to account the economic performance of corresponding processes and activities and to measure the contribution of any internal quality improvement on the firm’s revenue and profit. As a result, enterprise management can identify the key quality processes and activities under consideration to improve or change. Subsequently, enterprise management can integrate the external aspects of the business environment along with the internal resources, capabilities, and processes of the organization into an effective entity and can thus explore opportunities in terms of generating quality. The value that a quality-related organization creates depends on the benefits customers derive from the product/service attributes and characteristics and on quality-related costs, that is, the value sacrificed to produce and supply a certain quality package that constitutes a solution for customers. Decreasing the quality costs of the certain quality package enables enterprise to reduce, in the long run, the price that customers pay for it, leading the market equilibrium to a lower price level for this package. It thus becomes possible to estimate the market value for both kinds of quality processes and activities: those increasing benefits for customers by

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the quality and those lowering costs (and price) for a certain quality package. Obtaining data by product labels on the shelves of retailing establishments, we estimate the hedonic model choosing three products properly, such as the perishable and seasonal food characterized by high quality-related costs (transaction and preservation). The results confirm that the proposed framework has the capability to estimate the economic performance of qualityrelated processes and activities by measuring the market value of quality attributes and characteristics. These measures can be used (i) to detect whether certain processes/activities outperform the correspondent processes/activities of the competitors in the same market and build a competitive advantage based on design quality and (ii) as benchmarks with which enterprise management can identify processes or activities, creating value below that which the mean (typical) enterprise creates in the market, and plan to strengthen its competitive position, which is also based on conformance quality dimensions. Therefore, enterprise management can identify and choose the form and the level of the organizational and strategic quality-related changes to implement. The estimations of the three models can be used to compute the elasticities for each attribute and characteristic. These elasticities enable management to rank the quality processes and activities according to their contribution to the increase of benefits customers derive and on the reduction of quality cost for a certain package of attributes and characteristics. It is thus capable of ranking the quality-related processes/activities under consideration for improvement and change. If the enterprise combines the proposed framework with a process-oriented quality costing method, in cases where value is created by providing benefits for customers, it can account for the expected profit that each internal quality improvement or change provides. We thus conclude that the framework proposed above can yield multiple useful applications based on real economic data that are objectively measured. The findings of the empirical test verify the appropriateness of the adapted framework to contribute to the estimation of the economic performance on both kinds of quality processes: those creating value by increasing the benefits for customers and those that do so by reducing the value sacrificed for a certain quality package of attributes and characteristics (solution). Here a process/ activity that creates value by increasing benefits for customers is the selection of selling time activity for a seasonal product out of the typical season. There are three processes/activities that create value by reducing the value sacrificed for a certain quality package: labeling the product by the quality category signal, labeling it by the region of origin signal, and selecting the suppliers by preferring raw material providers (eliminating intermediate wholesalers). The selection of time to make the product available to customers when they demand it in a certain place is a service quality characteristic undertaken (added) by the retailer. Therefore, it is verified that the proposed framework can estimate the market value for a solution provided to customers composed of product and service attributes and characteristics. The results also confirm the assertion that a retailing establishment can create value by reducing the quality costs for a certain quality package by attaining economies of specialization and labor division. This finding can help providers and manufacturers–wholesalers of raw material in their decisions to consider the form of the ultimate supplier (retailer) they choose for their products. Because the framework helps enterprise management in the selection of the supplier and the seller in a vertical chain arrangement, it is also useful for enterprises in their attempts to manage inter-firm relations (crossenterprise decisions). Given the current complexity of building a quality-based advantage and the lack of existing methodologies to measure

the economic performance of processes and the impact of qualityrelated projects on firms’ revenues and profits, it is necessary to empirically test this method in different settings and forms. An example of this is to estimate a non-linear form of the hedonic price model, as, in some cases, the relationship between an attribute or characteristic and product price may be not linear. Because the market value of a process/activity arises from the regression of the correspondent attribute/characteristic with the observed price, it is not possible to estimate the economic performance of those processes/activities that do not face external customers in the market. Subsequently, enterprise management cannot include such a process or activity in those that are planned to be improved unless it can allocate benefits and expenses internally. In addition, a weakness in this method is an assumption that there is no horizontal dependence between internal processes and activities. Therefore, it is difficult to assess the market value of an attribute/ characteristic in a process or activity if this attribute is the common output of two processes/activities, forcing the management to allocate this value between them or to handle these processes as one.

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