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A method for identifying and assessing key customer group needs
Industrial Marketing Management 33 (2004) 643 – 655
A method for identifying and assessing key customer group needs Ernesto R. Wagnera,*, Eric N. Hansenb,1 a
b
6844 NE Vinings Way, Apartment 2232, Hillsboro, OR 97124, USA Department of Wood Science and Engineering, College of Forestry, Oregon State University, Corvallis, OR, USA Received 10 February 2003; received in revised form 29 September 2003; accepted 8 October 2003 Available online 5 December 2003
Abstract This paper presents a methodology for identifying and weighing the importance of product attributes used by a key customer group of a company. A central feature of the technique is the introduction of a new concept: competition factors (CF). These factors address the influence of substitute products in the specific product attributes that a customer group considers. A better knowledge of substitute products can surface previously hidden or latent customer needs. CF allow dealing with this problem, providing a powerful tool for market-oriented businesses that seek to understand customers’ expressed and latent needs. The wood products industry and architects are used to illustrate the technique. D 2003 Elsevier Inc. All rights reserved. Keywords: Product attributes; Lead users; Latent needs; Architects; Competition factors
1. Introduction During the first half of the 20th century, companies equated marketing with selling (Graham, 1993; Webster, 1988). This selling orientation meant selling anything the factory could produce (Webster, 1988). Then in the mid1950s, the marketing concept was formulated. Marketing became customer focused, as the scarcity of resources and products during WWII was replaced by an abundance of manufacturers fighting for the patronage of consumers (Graham, 1993; Webster, 1988; Webster, 1994a). The marketing concept remained at the core of business activity for more than a decade but lost steam during the 1970s as strategic planning became the dominant paradigm (Day & Wensley, 1983; Webster, 1988). A loss of competitiveness by U.S. companies during the 1980s caused a rediscovery of the marketing concept (Webster, 1988). This was because strategic planning was too focused on competitors while customers were barely considered (Webster, 1988). In the meantime, the marketing concept evolved into three aspects: customer orientation, coordinated marketing efforts of the
* Corresponding author. Tel.: +1-503-679-6844; fax: +1-503-6480446. E-mail addresses: [email protected] (E.R. Wagner), [email protected] (E.N. Hansen). 1 Tel.: +1-541-737-4240; fax: +1-541-737-3385. 0019-8501/$ – see front matter D 2003 Elsevier Inc. All rights reserved. doi:10.1016/j.indmarman.2003.10.003
entire firm, and focus on profit rather than on sales volume (McGee & Spiro, 1988). Modern authors rephrase the marketing concept in the following way: the purpose of an organization is twofold, (1) to discover wants and needs of its target customers, and (2) to satisfy those needs in a better way than competitors, focusing on profit rather than sales volume (Slater & Narver, 1998; Webster, 1994b). Even though many years have elapsed since the marketing concept was elicited, much more research is needed in basic issues, like the determination of the target customers of a business and understanding their wants and needs. However, recent debate sheds light on this issue. The discussion refers to the difference between customer-led and market-oriented companies (Slater & Narver, 1998, 1999). While the first are primarily concerned with satisfying customers’ expressed needs and focus on short-term issues, the second seek to understand customer expressed and latent needs and try to develop innovative solutions for producing superior customer value (Slater & Narver, 1999). One weakness of customer-led companies is the ‘‘tyranny of the served market,’’ as managers of those firms see the world only through their current customers’ eyes (Slater & Narver, 1998). Current customer insights into new product needs are restricted by their real world experience and thus are unlikely to generate novel product concepts (Von Hippel, 1986). On the other hand, market-oriented companies employ innovative techniques in order to discover latent needs of their customers. One of those techniques is to
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survey lead users (Slater & Narver, 1998). Lead users are customers whose present needs will later become those of mainstream consumers (Ungson & Trudel, 2001; Von Hippel, 1986). Lead customers can identify latent needs because they are familiar with conditions that lie in the future for most other customers (Von Hippel, 1986). Lead users are early adopters that are watched and emulated later by the majority (Hawkins, Best, & Coney, 1998; Rogers, 1995). The current hypercompetition environment further complicates the problem, as a growing number of product alternatives mean increasingly dynamic customer behavior (Grimm & Smith, 1997). Shifting customer behavior helps explain product substitution, an area that deserves more attention since most investigations have analyzed product substitution in retail settings, specifically inside a product category (Anupindi & Dada, 1998; Walters, 1991). Only a few studies have considered product substitution beyond these boundaries. Eastin, Shook, and Fleishman (2001) examined trends of material substitution in the U.S. residential construction industry. They attempted to explain material substitution by analyzing the change in preferences over time by customers with regard to several product (material) attributes. The authors argued that any product can be differentiated from similar competing products by considering how these products vary among just a few attributes highly valued by end users. Given the preceding discussion, this article outlines a method for identifying a key customer group and the subsequent evaluation of their product wants and needs. The technique considers the influence of substitute products on the importance of product attributes. A better knowledge of substitute products can surface customer needs previously
hidden or latent. In this regard, the present research provides a tool for market-oriented businesses, which seek to understand both customers’ expressed and latent needs (Slater & Narver, 1999). An application with the wood products industry and a key customer group, architects, is used to illustrate the technique, which was successfully used in a larger study that sought to improve the customer orientation of wood products companies, while maintaining a competition focus, specifically on substitute products. Also important, because of the globalization of the wood products industry, we consider two countries: the United States and Chile. Chile is an interesting country to analyze, given that Chilean wood products are gaining significant market share in selected U.S. wood products markets (Wagner & Hansen, in press).
2. Conceptual model First, the conceptual model of the full project is explained as well as how this paper fits into the bigger picture. Fig. 1 shows a matrix depicting customer needs and company competitive advantages. Company competitive advantages are the basic blocks of business strategy, the elements to ponder in order to determine which are more important for satisfying customer needs, the ultimate focus of this research. Customer needs and competitive advantages are related through a relationship matrix, which allows transforming weights of customer needs into weights of competitive advantages. The whole matrix is an adaptation of the main quality chart or ‘‘house of quality’’ used in quality function
Fig. 1. Conceptual model (underlined areas show focus of this article).
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deployment (QFD) (Bossert, 1991; Cohen, 1995; Day, 1994). In a traditional QFD application, customer needs are compared with design parameters of products. In this study, customer needs are compared with the competitive advantages of companies. It is important to emphasize that this study considers competitive advantages of wood products companies. On the other hand, the customer needs correspond to material design attributes that go beyond the wood material. These design attributes allow a comparison between wood and substitute products, therefore assessing which attributes constitute features that wood must better satisfy in order to gain market share from competing products.
3. Methods 3.1. Selecting the customer group: overview Selecting a customer group is a key decision in any marketing study. It is not always evident which group of people is the most adequate to investigate in order to answer the questions of interest. In this case, use of QFD requires that customer groups must be analyzed separately. It is not advisable to combine weights of attributes of two or more groups of customers in the same matrix. The main problem stems from the difficulty of knowing the overall importance of one group of customers with respect to the other. On the other hand, a representative from one group cannot fairly compare the importance of their needs to the needs of a representative of another group; the representatives can only speak for themselves (Cohen, 1995). Therefore, any QFD application should select one and only one customer group. The customer selection process was focused on the construction industry, as new residential and nonresidential construction represents almost one half of U.S. sawn softwood consumption (United Nations Economic Commission for Europe, 2001). Therefore, trends in material substitution in the construction industry are directly impacting the wood products industry (Eastin et al., 2001). Indeed, steel wall framing and poured concrete floors have increased market share between 1997 and 2000, whereas wood lost an average 2.5% market share in walls, floors, and roofs during the same period (Wood Promotion Update, 2001). The market share lost by the wood products industry amounts to approximately US$270 million in annual revenue. Thus, it is relevant to investigate those customer groups involved in the material specification for residential and nonresidential projects. These specifiers may include architects, construction firms/contractors, structural engineers, and final owners. Nowadays, most new homes and apartments are built prior to sale; therefore, the owner of a new home has little influence on material selection. Construction firms, architects, and structural engineers, however, interact in the material (product) selection process.
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The overall question that the selected customer group must answer is, ‘‘What can increase the appeal of the product so that it will be selected instead of competing products?’’ In this case study, contractors were discarded as a possible customer group for two reasons: First, although construction companies actually buy the wood products, the influence of specifiers like architects or structural engineers in the material specification process of medium and large construction projects is very significant. Twenty interviews with architects and civil engineers in the United States and Chile verified the importance of their role. Architects are especially influential in projects where differentiation is a main concern, like high-end condominiums, showrooms, corporate headquarters, etc. On the other hand, the importance of civil or structural engineers grows in industrial projects. Second, previous research shows that it is very difficult to obtain a representative sample of contractors, with poor response rates that range between 7% and 14% (Alderman, 2001; Eastin et al., 2001; Fell, Gaston, Hansen, & Hovgaard, 2001). Based on this information, the customer group should be either architects or civil engineers, and further analyses were necessary in order to choose between these two customer groups. 3.2. Selecting the customer group: conjoint and cluster analyses Conjoint and cluster analyses were conducted in order to learn about the material preferences of the two professional groups of interest. In that regard, a sample of 20 civil engineers and architects was selected (5 U.S. engineers, 9 U.S. architects, 2 Chilean engineers, and 4 Chilean architects). Professionals from both countries were faced with the same Conjoint analysis design, basically a set of cards depicting different materials (wood, steel, concrete, and masonry) with different attributes (environmental sustainability, cost, and familiarity of the workforce with the material), in order to assess cultural and professional differences. Use of conjoint analysis showed a difference between the sampled Chilean and U.S. architects (and engineers) regarding environmental issues. The U.S. architects were very aware of environmentally certified (green) wood products. They try to foster the use of environmentally friendly products, as was clearly pointed out during the personal interviews. With one exception, U.S. engineers were not aware of environmentally certified wood products. Also, neither Chilean architects nor engineers consider environmental issues as an attribute when selecting a material. Table 1 shows the utilities (regression coefficients with reversed signs) of the attribute ‘‘environmentally sustainable’’ for the 20 respondents (sustainability: ‘‘a state or process that can be maintained indefinitely’’) (IIDA, 1999, p. 2). It is remarkable how well this attribute separates professionals from the two countries. It is important to emphasize that respondents could not fabricate these utilities
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Table 1 Utilities (in decreasing order) of the attribute ‘‘environmental sustainability’’ for U.S. and Chilean architects and engineers U.S. U.S. U.S. U.S. U.S. U.S. U.S. U.S. U.S. U.S.
engineer engineer architect architect architect architect architect architect architect engineer
2.00 2.00 2.00 2.00 1.50 1.50 1.50 1.25 0.75 0.75
Chilean engineer Chilean architect U.S. engineer U.S. engineer U.S. architect U.S. architect Chilean engineer Chilean architect Chilean architect Chilean architect
0.75 0.50 0.25 0 0 0 0 0.25 0.50 0.50
(part worths) because they were implicit in their answers regarding material preferences. Cluster analysis grouped individuals according to demographic information as well as the likeness of their preferences; in other words, the procedure grouped respondents according to the similarity of the importance (utilities) they assigned to each attribute in the conjoint analysis application. The most interesting clustering resulted when using all variables and when labeling by profession and country. The dendogram in Fig. 2 shows how respondents are linked together according to the similarity of their preferences. The more to the right the vertical link between two respondents, the more dissimilar they are. The sampled U.S. professionals tended to fit in one cluster (Group 1 in Fig. 2) while Chilean professionals tended to fit in another cluster (Group 2 in Fig. 2), suggesting that cultural differences make the product (material) preferences of professionals in the two countries radically different. This result indicated that separate matrices like Fig. 1 would be necessary for each country. In order to test the objectivity of the clusters, a set of t tests was carried among the clustering variables (Harrigan, 1985) in order to assess differences among the clusters with respect to each of the variables. The t tests showed a
statistically significant difference in four of the seven clustering variables (two-sided P values < .05), somewhat supporting the objectivity of the clusters. A K-means clustering algorithm was also used, requiring two groups. This algorithm rendered all U.S. professionals but one in one of the clusters, providing additional evidence of a difference between the United States and Chile. It is important to comment that the difference between the two countries persisted, even when ‘‘environmentally sustainable’’ was not considered as a clustering variable. Finally, and most important for this research, clusters tended to have both architects and engineers of a certain country (either the United States or Chile). In other words, the data suggest that even if the importance of ‘‘environmentally sustainable’’ separates architects from engineers, it seems that the other attributes blur that difference and make professional groups of a single country quite similar when considering all the attributes. The small sample size makes any inference to the total populations only tentative. Still, the objective of the analyses was to compare, even in a limited fashion, the material preferences of architects and engineers. The results are consistent with those of Kozak and Cohen (1999), who found almost no significant differences between architects and engineers regarding construction material preferences. Architects, and not structural engineers, were selected as the customer group for this study for two reasons. First, environmentally friendly (green) buildings are a growing trend, as reflected by the numerous related conferences and even associations that have been created. Therefore, this study intended to measure the environmental preferences of a lead customer involved in the material selection decision for construction projects (Von Hippel, 1986). The results of the conjoint and cluster analyses unequivocally point at architects as the most environmentally concerned professional group. Indeed, architects are seen to be a lead customer group regarding environmental issues (IIDA,
Fig. 2. Architects and engineers dendogram using average linkage (between groups).
E.R. Wagner, E.N. Hansen / Industrial Marketing Management 33 (2004) 643–655 Table 2 Wood product groups as defined by architects
3.3. Identifying customer wants and needs
Product groups
Product properties that are important for each group
Specific products that fit into the groups
Structural products group
Strength and structural properties Aesthetic properties
Softwood lumber + softwood plywood + oriented strand board Hardwood decorative panels + moldings + finishing materials GlueLam, I-Beams, etc.
Appearance products group Engineered wood products group
Strength and aesthetic properties
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A second set of personal interviews was conducted with practicing architects (4 in Chile and 13 in the United States). The interviewees were carefully selected to ensure a good variety of respondents. In the United States, the size of both the company and the city where the architect worked was an important criterion used when selecting the respondents. It is important to note that the interviews were just intended to identify customer wants and needs; thus, a small number of interviews were able to accomplish this task. However, the measurement of the importance of each customer want and need required a representative sample of architects; thus, a nationwide mail questionnaire was used, as is described below. The architect interviews included two parts. The purpose of the first part was to identify a classification of wood products consistent with the way architects specify wood
1999; Von Hippel, 1986). Second, the wood products industry targets architects with environmental advertising and therefore were an appropriate group for this research (Wagner & Hansen, in press).
Table 3 Attributes weights and categorization for U.S. wood products Mean
S.D.
HSD method1
CF
New means due to CF
Range method1
Final groups1
U.S. structural products Material available Uniform quality Dimensionally stable Adaptability2 Durability Knowledgeable work force Low cost Environmentally sustainable Fire concern
5.83 5.63 5.53 5.54 5.17 5.14 4.97 4.96 (4.80 – 5.17) 4.23
0.89 1.25 1.29 1.16 1.41 1.40 1.34 1.49 1.60
a a b b b b b b c
1.5 1.8 1.8 1.5 1.5 1.5 1.5 1.5 1.2
8.75 10.14 9.96 8.30 7.75 7.72 7.45 7.2 – 7.76 5.07
a a a b b b b b c
a a a b b b b b c
U.S. appearance products Appearance, warmth, tactile Honest material Off gassing3 Environmentally sustainable Durability Low cost
5.83 5.44 4.87 4.87 (4.69 – 5.08) 4.84 4.50
0.98 1.40 1.60 1.56 1.60 1.38
a a b b b b
1.5 1.5 1.2 1.5 1.5 1.5
8.74 8.17 5.85 7.04 – 7.62 7.26 6.75
a a b b4 b b
a a b b4 b b
U.S. engineered wood products Uniform quality Dimensionally stable Strong material Adaptability Environmentally sustainable Feasibility of curves5 Low cost Off gassing Appearance, warmth, tactile
6.05 6.03 5.90 5.39 5.05 (4.84 – 5.31) 4.76 4.76 4.43 4.16
0.87 0.94 0.99 1.17 1.47 1.54 1.29 1.68 1.74
a a a a b b b c c
1.8 1.8 1.2 1.5 1.5 1.5 1.5 1.2 1.2
10.89 10.86 7.07 8.09 7.26 – 7.97 7.13 7.13 5.32 4.99
a a b b b b b c c
a a b b b b b c c
1 This table illustrates two classification methods for the attributes on the left column. The HSD method and the Range method classify the means in a maximum of three groups: a, b, and c. Attributes in one group (say ‘‘a’’) are not significantly different from each other, but any two attributes of two different groups (say ‘‘a’’ and ‘‘b’’) are different. The range method does consider the competition factors; thus, it was the categorization method preferred by this study (final groups are the groups defined by the range method). 2 Adaptability refers to the simplicity with which wood elements can be trimmed to the correct length. 3 Off gassing refers to the concern about harmful vapors coming out of a material when in use. 4 The variability of the importance may make this attribute to belong to either the ‘‘a’’ or the ‘‘b’’ category. 5 Feasibility of curves refers to either the possibility of installing the wood material over a curved surface or to build curved wood elements, like curved laminated beams.
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materials. Thus, a preliminary classification was constructed based on personal knowledge and a literature review. The interviews confirmed the adequacy of the preliminary product groups: a structural group where the main requirements are strength and structural properties; an appearance group where aesthetics is the key requirement; and an engineered wood products group where both strength properties and appearance issues are relevant. Architects unanimously supported this categorization as one that fits the way they select construction materials. Table 2 defines the groups in more detail. The second part of the interview was an open question asking architects about the good and bad characteristics of wood products. They were also asked about what can increase the appeal of wood so that it would be preferred over competing materials, like steel, concrete, or plastics. Respondents answered the same question for each of the three product groups. The different number of interviews in the United States and Chile (13 and 4) required the use of a different criterion for identifying the final set of attributes utilized in each country. In the Chilean case, the small number of interviews meant that we kept all attributes
named by the interviewees, whereas in the Unites States only the attributes named by at least four persons were kept. Architects used a very similar language for expressing the design concepts they consider, making attribute categorization and identification easy. The actual attributes determined through the interviews are shown in the first column of Tables 3 and 4. The described methodology is equally applicable for single products or for product groups. In the first case, Tables 3 and 4 would be only a list of attributes, without the subsections defined by the product groups. Still, the techniques for determining the customer needs and the weights of those described in the next section are exactly the same. 3.4. Determining weights of customer needs A carefully constructed mail questionnaire was developed based on information from interviews and the extant literature in order to assess the importance of the attributes identified through the interviews. The United States and Chilean cases were analyzed separately.
Table 4 Attributes weights and categorization for Chilean wood products1 Mean
S.D.
HSD2 method
CF
New means due to CF
Range2 method
Final2 groups
Chilean structural products Structural properties Durability and maintenance Uniform quality Appearance Low cost Fast construction Fire concern Lack of constructive solutions
5.91 5.79 5.75 5.60 5.25 5.15 4.79 4.02
1.18 1.20 1.31 1.27 1.28 1.42 1.49 1.64
a a a a a a a b
1.2 1.2 1.2 1.5 1.2 1.2 1.2 1.2
7.09 6.95 6.90 8.40 6.30 6.18 5.75 4.82
a a a a a a b b
a a a a a a b b
Chilean appearance products Appearance, warmth, tactile Honest material Durability and maintenance Feasibility of curves Material easy to refurbish Low cost
6.58 6.19 5.87 5.32 5.23 4.42
0.57 0.90 0.90 1.46 1.32 1.26
a b b b b c
1.5 1.5 1.5 1.5 1.2 1.8
9.87 9.29 8.81 7.98 6.28 7.96
a a a b c b
a a a b c b
Chilean engineered wood products Uniform quality Durability and maintenance Appearance Feasibility of curves Fire concern Glue quality Low cost Lack of competitors Lack of constructive solutions
6.10 6.06 6.00 5.88 5.77 5.60 5.04 4.88 4.74
0.81 0.98 1.00 1.16 1.11 1.41 1.33 1.34 1.61
a b b b b b b b c
1.44 1.5 1.5 1.5 1.2 1.2 1.44 1.5 1.2
8.78 9.09 9.00 8.82 6.92 6.72 7.26 7.32 5.69
a a a a b c b b c
a a a a b c b b c
1
In this case, just one person provided the competition factors. This table illustrates two classification methods for the attributes on the left column. The HSD and range methods classify the means in a maximum of three groups: a, b, and c. Attributes in one group (say ‘‘a’’) are not significantly different from each other, but any two attributes of two different groups (say ‘‘a’’ and ‘‘b’’) are different. The range method does consider the competition factors; thus, it was the categorization method preferred by this study (final groups are the groups defined by the range method). 2
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3.4.1. U.S. mail questionnaire In the United States, a nationally representative measure of the opinion of the owner or chief architect of architect offices was pursued. These individuals would be the most knowledgeable about design and material selection. The mailing process was an adaptation of the tailored design method (Dillman, 2000). Questionnaires (1200) were sent, expecting a response rate of about 30% while still meeting the target of approximately 380 returned questionnaires, for a sampling error of 5% (Dillman, 2000). Three hundred and seventy-five validly answered questionnaires were received, for a 34% response rate, discounting nondeliverables. This response rate compares well with other studies that involved architects (Damery & Fisette, 2001; Kozak & Cohen, 1999). The next lines describe only how the nonresponse error was controlled, although the two other types of survey error were also monitored, namely, coverage and measurement (Dillman, 2000). Regarding nonresponse error, a common method is to assume that late respondents (second mailing) are more similar to nonrespondents than early respondents (first mailing) (Armstrong & Overton, 1977). Early respondents were compared to late respondents on a total of 30 attributes, and only one statistically significant difference was found (two-sided P value < .05 from t tests). One significant P value out of 30 can happen just by chance, so there is no evidence of nonresponse error. 3.4.2. Chilean questionnaire Cultural reasons make it very difficult to obtain survey responses in Chile. Mail questionnaires inevitably end up in the trash. Therefore, the approach was to select a convenience sample of the largest architect offices (sample size of 85), most of which are located in the Santiago metro area. This fact reflects the importance of this city in the whole nation, as it contains 40% of its population and about 40% of its gross national product (Instituto Nacional de Estadisticas (INE), 2003). Importantly, the Chilean survey was conducted in Spanish and it incorporated the design attributes identified through the Chilean interviews. The survey methodology used, feasible because of the small sample size, was to first send the questionnaire by mail and then follow-up by phone. On average, each architect office was called 15 times to obtain the 53 answers (a 62% response rate). 3.5. Competition factors (CF) Certain characteristic(s) of a construction material (say, dimensional stability) induces customers to select it as the product to be used (e.g., steel) instead of competing products (Eastin et al., 2001). Clearly, some products inherently meet specific quality characteristics better than others. Surveys are generally ineffective for identifying those differences among products because respondents answer questionnaires with too narrow a notion of competing products or substitutes. Knowledge of substitute products
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helps surface latent customer needs. Introduction of CF is a way to deal with this problem, providing a powerful tool for market-oriented businesses (Slater & Narver, 1999). To understand CF, is essential to introduce Kano’s quality typology (Cohen, 1995), which divides quality characteristics into three different categories: 1. Expected quality: These are characteristics of the product that the customer expects to be present. Customers normally do not ask for them in market research; but if this quality is absent, it causes dissatisfaction (therefore called dissatisfiers) (Bossert, 1991, Cohen, 1995). 2. Desired quality: These characteristics, also called satisfiers, are something that customers want in their products and usually ask for them in surveys. The more of a satisfier, the happier customers will be (Cohen, 1995). 3. Exciting quality: These characteristics, called delighters by Cohen (1995), are product attributes that are pleasant surprises that greatly satisfy customers when they first encounter them (like happened several years ago with cup holders in cars). By definition, customers cannot expect exciting quality, so if this kind of characteristic is missing, customers will not be dissatisfied (Akao, 1990). This typology closely resembles the concepts of expected and augmented product (Levitt, 1980, Slater & Narver, 1999). The expected product corresponds to what the customer considers the minimum acceptable benefits that the product must comprise, while the augmented product encompasses benefits that satisfy latent needs. In other words, an augmented product satisfies needs that have not yet been addressed by current products. CF introduce the product substitution influence into the problem by taking into account the existence of customer needs that correspond to either expected or exciting qualities (expected or augmented product). The competition factor of each attribute is formed by the multiplication of the improvement ratio and the sales point, constituting an adaptation of the method applied by Cohen (1995) (see Fig. 3), as explained below. Improvement ratio: If steel, concrete, or a plastic product meets an architect requirement, another material, like wood, is expected to fulfill the requirement at least equally well (expected quality). Undoubtedly, such an attribute is more important to satisfy than a requirement where the competition of wood does not do well at all, which can constitute a delighter (exciting quality), as has been discussed previously. The improvement ratio enhances the importance of attributes where the product of interest (wood) is in a disadvantageous position regarding substitute products and thus is ‘‘product specific’’ (Fig. 3). A good example of a requirement that wood does not meet well is dimensional stability. Wood swells or contracts when relative humidity changes, while a piece of steel maintains its size; thus, architects may (and in fact they do) request an important
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Fig. 3. CF for wood (product of interest) considering substitute products (steel, concrete, and plastics).
improvement for this feature in the wood material, thus it exhibits a high improvement ratio. Sales point: The sales point enhances the importance of attributes that encourage sales on their own, regardless of the type of product that is considered, and thus is ‘‘attribute specific.’’ The sales point may show issues where wood is in an advantageous position regarding substitute products (Fig. 3). A good example of such an issue is the ‘‘warmth’’ of a material, as wood reportedly creates environments where people like to work. On the contrary, many people do not like environments with predominant steel or concrete (Ridoutt, Ball, & Killerby, 2002a, 2002b). The CF were determined using expert opinion. Three architects in the Unites States provided values for the improvement ratio and sales point according to the rule depicted in Fig. 3. The Delphi technique was used to gather expert opinion (Clayton, 1997). Reasonable convergence was defined by answers that could not contain extremes, i.e., the combination of levels 1.0, 1.0, and 1.2 was acceptable, but not 1.0, 1.0, and 1.5. In the first round of the U.S. case, perfect agreement (for example, 1.0, 1.0, and 1.0) was reached in 39 of the 48 decisions (24 attributes, 2 decisions per attribute). Convergence was reached in the second round. In the Chilean case, only one architect could be reached to provide values for the CF. The values of that single person are being used. The final CF are reported in the central column of Tables 3 and 4.
4. Analysis Tables 3 and 4 report the customer needs for the United States and Chile, respectively. The respondents were asked to assign a value for each attribute in each product group according to the level of importance that the feature has in the material specification process. The scale used corresponds to a 1 to 7 Likert-type scale, from 1 = less important to 7 = more important. Tables 3 and 4 display the attribute names and their mean and standard deviation in the three left columns. The remaining columns depict two categorization systems. The CF are reported in the middle of the charts. The categorization of attributes in importance groups was based on statistical significance. In that respect, attributes were categorized in a maximum of three groups: ‘‘a’’ for important attributes, ‘‘b’’ for attributes of medium impor-
tance, and ‘‘c’’ for attributes of low importance. The notion is that attributes inside a group (say, ‘‘a’’ attributes) are not significantly different among each other, but the difference becomes significant if attributes from two importance groups are considered (if comparing, say, attributes from groups ‘‘a’’ and ‘‘b’’). Two categorization systems were developed: the first (honest significant difference method or HSD) is a strictly statistical technique, whereas the second method (range method) introduces the CF into the problem. The classification of attributes in importance groups incorporating the CF is a key feature in the intent to determine which attributes are really important for satisfying customer needs while considering the influence of substitute products. 4.1. HSD categorization method The allocation of attributes to groups according to their level of importance can be approached in several ways. Each of the attributes will be considered as an independent sample, and therefore the analysis will correspond to multiple comparisons of means (Ramsey & Schafer, 1997). The large number of all pairwise comparisons compounds statistical uncertainty. The method selected for this problem is the Tukey HSD, which considers a family-wise confidence level (Ramsey & Schafer, 1997). Two means, yi and yj, are declared not equal if jyi yjj>HSD; HSD = multiplier S.E., multiplier is the q (a, number of groups, degrees of freedom) statistic that can be obtained from a studentized range distribution (Kuehl, 2000). The methodology orders the means from smallest to largest. The biggest range (means 1 and n) is analyzed and the rule for equality of means is tested. If the difference between the means is larger than HSD, then means 1 and (n 1) are analyzed and also means 2 and n. If the difference is still larger than HSD, the range then diminishes to 2 and (n 1) and so on. Significance was set at 1% due to the large sample sizes (a=.01). In the case of U.S. structural products, the 1% significance determined an HSD of .5. The group of means that was found not significantly different was the set with a maximum of 5.5 (adaptability, dimensionally stable) and a minimum of 5 (environmentally sustainable, low cost): the attributes in that set obtained a ‘‘b’’ importance. Means above and below that set are considered to be in other groups: ‘‘a’’ and ‘‘c,’’ respectively. Eventually, only two groups are defined or even one, depending on the dispersion
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of the means of the attributes. U.S. appearance products and Chilean structural products are cases where less than three groups were defined. 4.2. CF and range method The CF introduce the effect of substitute products on the means, as well as the problem of different types of qualities, some of them more important to meet than others. The CF were multiplied with the old means to produce what is called ‘‘new means due to CF’’ (see Tables 3 and 4). These new means were categorized using a range method, which does not take into account the standard deviations. So, for U.S. structural products, the difference between the maximum and the minimum new means (range) was 5.07. The number of segments defined by HSD is used so the range is divided by three in order to define three segments: 5.07/ 3 = 1.69, which determines the segments ‘‘a’’: 8.47 –10.16, ‘‘b’’: 6.77 –8.46, and ‘‘c’’: 5.07– 6.76. The same procedure was followed with all product groups. Thus, at the end, we had two categorization methods. The range method was chosen between the two because it takes into account the CF. It is important to emphasize that the HSD technique is still providing the number of segments for each product group even when using the range method. The HSD and range methods produce quite similar segments in the U.S. case, providing evidence of internal consistency (Bagozzi, 1994, chap. 1). That is not the case with the Chilean product groups where the methods produce quite different results. The categorization of the range method was still kept in the latter case.
5. Results The design attributes and specification criteria used by architects are reported in the following paragraphs. First, results of the U.S. study are discussed, followed by a cross-cultural comparison between the Unites States and Chile.
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nowadays more concerned about other aspects of wood materials, essentially technical issues, than about price of the material or sustainability. This outcome shows that although qualitative research is useful for learning and providing input for further research, the quantitative results may actually differ from interviewer perceptions acquired during the qualitative part of the study (Winer, 1999). It was expected that the attribute environmentally sustainable would have a different importance in different areas of the United States, as the attitude of architects towards the environment may not be the same across the nation. In this regard, the importance of the attribute environmentally sustainable of the structural product group was analyzed in four regions of the United States. There is suggestive evidence of a statistically significant difference (one-way ANOVA analysis: P value of .065). The West region (Hawaii, Washington, Oregon, and California) was the highest with an average of 5.3 (on a scale of 1 to 7), and the averages for other regions were 5.0, 5.0, and 4.6. If the West is taken out of the analysis, the other three regions were not significantly different from one another (one-way ANOVA analysis: P value of .25). ‘‘Dimensionally stable’’ is a U.S.-exclusive attribute that received high scores in both the structural and engineered wood products categories. Dimensional stability is something that wood does not meet well, as compared with a competing material like steel. Thus, it was expected that dimensionally stable would be an attribute that would receive a high improvement ratio by architects. Consistently, it received an improvement ratio of 1.5 that caused the only change in the categorization of U.S. structural products, if comparing the HSD and the range method: dimensionally stable rises to the ‘‘a’’ category when using the range method. Consideration of substitute products is one of the distinctive features of the methodology presented in this article. The CF showed that dimensionally stable is more important than what the raw measure of its importance shows. 5.2. Cross-cultural comparison of architect needs and preferences
5.1. U.S. results Environmentally sustainable and low cost are two attributes that appear in all three product segments. It was surprising that these two attributes received low scores, especially in the case of environmentally sustainable because this attribute was regarded as very important during the personal interviews. ‘‘Environmentally sustainable’’ ranks in the bottom three in both the structural and the appearance group but achieves a better position in the engineered wood products group. This makes sense as these products were introduced as environmentally friendly. The lower relative importance of environmentally sustainable and low cost indicates that perhaps U.S. architects are
The following are several interesting similarities and dissimilarities between Chile and the Unites States. The U.S. interviews clearly identified an environmentally related attribute in the three product groups. On the other hand, Chilean architects did not mention an environmentally related attribute in any of their product groups. This is consistent with the results of the conjoint analysis where Chilean architects generally did not show positive part worths for the attribute environmentally sustainable. Uniform quality is an attribute that is in the top three regardless of the country considered. During the U.S. interviews, architects complained about a general decrease in the quality of wood products, a message consistent with the
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findings of Hansen and Bush (1996) and Weinfurter and Hansen (1999). Fire concern is much lower than the literature suggests (Kozak & Cohen, 1999). In the case of the United States, it was hypothesized that fire concern would have a lower importance in the Northwest because wood is the traditional Northwest material. This attribute was tested for differences among four U.S. regions and no statistically significant differences were found ( P value=.10 from a one-way ANOVA). The most interesting result concerns the appearance group. Despite the language difference, architects from both countries worded two attributes in the same way and those attributes received the two highest scores in the product group, regardless of country. The attributes are as follows: appearance, warmth and tactile sensation of the material, and honest material. Architects of both countries expressed in the interviews that the grain and texture of wood are unique; thus, appearance does not explain the concept adequately. Instead, appearance, warmth, and tactile sensation give a holistic approach to the concept. On the other hand, honest material simply means that architects like that the material is what it seems to be.
6. Limitations This study has limitations. First of all, one half of the interviewed U.S. engineers and one third of the interviewed U.S. architects studied in Oregon universities. The interviews just provided the attributes, not the weights of the attributes, but the local tastes may have influenced the answers used in the conjoint and cluster application. Also important, the U.S. results come from a random sample drawn from a population of 115,000 architects. These results are much more generalizable than Chilean results drawn from a convenience sample. The Chilean component of this work provides great insights regarding the difficulty of performing marketing studies in other countries regardless of language differences. Chilean architects (and people in general) are well known for not cooperating with any survey or interview effort. This difficulty was apparent in this project, and personal contact and considerable patience were invaluable for obtaining answers. Cross-gender comparisons of preferences in the United States were impossible because 93.9% of the respondents were male (352 out of 375). Still, the survey was successful in reaching the owner of each architect office. Only 40 out of the 375 respondents (10.6%) were nonowners. Data analysis revealed an important source of error regarding the order in which the attributes inside each product group were presented to respondents. Dillman (2000) suggests that people analyze all the categories before answering a question in a questionnaire but also notes that some research indicates otherwise. Before conducting the
study, both environmentally sustainable and low cost were expected to be highly rated. Thus, half of the questionnaires sent out had environmentally sustainable and low cost in the first and second position, while the other half had them in the last and second-to-last position. Although low cost did not show a statistically significant difference, the mean importance of environmentally sustainable was significantly different in each of the three product groups. Indeed, this last attribute received a higher weight when placed at the end than when placed at the beginning of the set of attributes regardless of the product group (two-sided P values of .02, .02, and .004 from t tests) (the weights of environmentally sustainable when placed at the beginning and when placed at the end are shown between parentheses next to the mean of the attribute in Table 3). This variability means environmentally sustainable may fit in either the ‘‘b’’ or ‘‘a’’ category of the appearance group. The other groups did not show changes in the attribute memberships. This result suggests that most respondents did not read all the attributes before assigning the weights. Environmentally sustainable receives a higher rating when placed at the end because respondents have already evaluated the other attributes. When in the first position, the respondent does not have a frame of reference for estimating the importance of environmentally sustainable. The other attributes are of a technical nature so we do not expect a similar problem. Environmentally sustainable is a social context attribute. Thus, its importance would increase after considering technical issues. Low cost, a practical attribute, supports this proposition because it was rated similarly regardless of its position in the questionnaire.
7. Contributions The main contribution of this research effort is the development of a methodology for selecting a customer group of a company, and subsequently categorizing its customer wants and needs. Consideration of the influence of substitute products on the importance of product attributes constitutes another contribution, as market-oriented businesses need innovative techniques for learning about both expressed and latent needs of their customers. The multidisciplinary nature of the research, which unites concepts of marketing, total quality management, and strategy, is also notable.
8. Managerial implications The methodology presented in this article is applicable to any industry and any customer group. In that regard, there are two main areas that should be of interest for managers. First, a common problem in real business settings is the need to deal with different customer groups, while time or money constraints may mean focusing marketing research
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efforts on only one. This study provides a comprehensive approach for selecting a key customer group, which considers both practical issues like the inability to obtain reasonable response rates from certain customer groups and more theoretical matters like testing the objectivity of clusters of customers. Second, a better understanding of substitution dynamics would benefit any company. As an illustration, retail executives can apply the CF concept to the opening of a new supermarket in an area of a city attended by an existing store. The new supermarket may offer new and superior service, like accepting debit cards, while the older establishment only accepts cash and checks. While this
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offering is initially an exciting quality, as consumers become accustomed to the service, it may evolve into an expected quality. Thus, even if the existing supermarket is otherwise very convenient, the lack of some key features (debit card) might cause important dissatisfaction among its traditional customers who may change their buying habits. It is important to note, however, that substitute products may really complement the offer and not drive the obsolescence of the former product. That is the case of the fax machine. This machine proved much more convenient and affordable than telex, causing the immediate obsolescence of the latter. Interestingly, although electronic mailing is
Fig. 4. Key customer group selection and study: a step list for industrial customers.
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even more convenient than fax in some regards, the ability to send forms filled by hand or to draw pictures or write annotations over documents that are subsequently sent corresponds to previously hidden needs that the fax machine satisfies better than e-mail, and that enables the fax to still have a place in offices around the world. Fig. 4 presents a summarized step list for managers willing to apply the methodology introduced by this study to their particular business situation. The procedure can be applied to either industrial (professional) customers or to final consumers. Although the step list is equally applicable to either one, the selection of the right customer is arguably more difficult in the case of industrial customers, as product selection decisions may be influenced by several different individuals (professional customers). The article provides an excellent example in this regard. Finally, it is important to emphasize that many previously unrelated industries have become direct competitors. Examples abound in the communications business, where computer-to-computer phone calls are competing directly with normal long distance calls. Therefore, the examination of attributes of any product should consider the influence of substitutes, as this analysis may allow maintaining the patronage of increasingly elusive customers. References Akao, Y. (1990). Quality function deployment: Integrating customer requirements into product design (p. 367). Cambridge, MA: Productivity Press. Alderman, D. R. (2001, April 12). An investigation into attitudes towards recycling CCA treated lumber. PhD thesis. Wood Science and Forest Products, Virginia Polytechnic Institute. Anupindi, R., & Dada, M. (1998). Estimation of consumer demand with stock-out based substitution: An application to vending. Marketing Science, 17(4), 406 – 423. Armstrong, J. S., & Overton, T. S. (1977, August). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14, 396 – 402. Bagozzi, R. P. (1994). Measurement in marketing research: Basic principles of questionnaire design. In R. Bagozzi (Ed.), Principle of marketing research ( pp. 1 – 49). Oxford, UK: Blackwell, Chapter 1. Bossert, J. L. (1991). Quality function deployment a practitioner’s approach (p. 127). New York: Marcel Dekker. Clayton, M. J. (1997, December). Delphi: A technique to harness expert opinion for critical decision-making tasks in education. Educational Psychology, 17(4), 373 – 386. Cohen, L. (1995, May). Quality function deployment: How to make QFD work for you (p. 348). Reading, MA, USA: Addison-Wesley Publishing (First printing). Damery, D. T., & Fisette, P. (2001). Decision making in the purchase of siding: A survey of architects, contractors and homeowners in the U.S. Northeast. Forest Products Journal, 51(7/8), 29 – 36. Day, G. S. (1994, October). The capabilities of market-driven organizations. Journal of Marketing, 58, 37 – 52. Day, G. S., & Wensley, R. (1983, Fall). Marketing theory with a strategic orientation. Journal of Marketing, 47, 79 – 89. Dillman, D. A. (2000). Mail and internet surveys: The tailored design method (2nd ed.) (p. 464). New York: Wiley. Eastin, I. L., Shook, S. R., & Fleishman, S. J. (2001). Material substitution in the US residential construction industry, 1994 versus 1998. Forest Products Journal, 51(9), 30 – 37. Fell, D., Gaston, C., Hansen, E., & Hovgaard, A. (2001, March). Attributes
demanded in single-family floor systems. . Vancouver, BC, Canada: Forintek Canada (Project No. 2504). Forest Products Annual Market Review 2000 – 2001 (2001). ECE/TIM/ BULL/54/3 United Nations Economic Commission for Europe (UNECE). Food and Agriculture Organization of the United Nations. Graham, P. (1993, May). Marketing’s domain: A critical review of the development of the marketing concept. Marketing Bulletin, 4, 1 – 10. Grimm, C. M., & Smith, K. G. (1997). Strategy as action: Industry rivalry and coordination. Cincinnati, OH: Southwestern College. Hansen, E. N., & Bush, R. J. (1996). Consumer perceptions of softwood lumber quality. Forest Products Journal, 46(10), 29 – 34. Harrigan, K. R. (1985). An application of clustering for strategic group analysis. Strategic Management Journal, 6, 55 – 73. Hawkins, D.I., Best, R.J., & Coney, K.A. (1998). Consumer behavior: Building marketing strategy (7th ed.) p. 760. New York, NY, USA: McGraw-Hill. Instituto Nacional de Estadisticas (INE), (2003, September 1). (similar to the Bureau of Census in the USA) Available at: http://www. ine.cl/. Last accessed September 01, 2003. Kozak, R. A., & Cohen, D. H. (1999, April). Architects and structural engineers: An examination of wood design and use in non residential construction. Forest Products Journal, 49(4), 37 – 46. Kuehl, R. O. (2000). Design of experiments: Statistical principles of research design and analysis (2nd ed.) (p. 666). Belmont, CA, USA: Duxbury Press. Levitt, T. (1980). Marketing success through differentiation of anything. Harvard Business Review, 58(1), 83 – 91. McGee, L. W., & Spiro, R. L. (1988, May/June). The marketing concept in perspective. Business Horizons, 31(3), 40 – 45. Ramsey, F.L., & Schafer, D.W. (1997). The statistical sleuth: A course in methods of data analysis p. 742. Belmont, CA, USA: Duxbury Press. Ridoutt, B. G., Ball, R. D., & Killerby, S. K. (2002a, September). Wood in the interior office environment: Effects on interpersonal perception. Forest Products Journal, 52(9), 23 – 30. Ridoutt, B. G., Ball, R. D., & Killerby, S. K. (2002b, October). First impressions of organizations and the qualities connoted by wood in interior design. Forest Products Journal, 52(10), 30 – 36. Rogers, E. M. (1995). Diffusion of innovations (4th ed.) (p. 519). New York: Free Press. Slater, S. F., & Narver, J. C. (1998). Customer-led and market-oriented: Let’s not confuse the two. Strategic Management Journal, 19, 1001 – 1006. Slater, S. F., & Narver, J. C. (1999). Market-oriented is more than being customer-led. Strategic Management Journal, 20, 1165 – 1168. The project: Assessing the future of green design (1999). Sponsored by the International Interior Design Association (IIDA). Available at: www. iida.org. Accessed February, 2001. Ungson, G. R., & Trudel, J. D. (2001). High prosperity management: Templates for the information age. Internal paper Lundquist College of Business, University of Oregon. Von Hippel, E. (1986, July). Lead users: A source of novel product concepts. Management Science, 32(7), 791 – 805. Wagner, E. R., & Hansen, E. N. (2002). Methodology for evaluating green advertising of forest products in the United States: A content analysis. Forest Products Journal, 52(4), 17 – 23. Wagner, E.R., & Hansen, E.N. (2004). Environmental attributes of forest products: Context and relevance for US architects. Forest Products Journal, (in press). Walters, R. G. (1991, April). Assessing the impact of retail promotion on product substitution and complementary purchase and interstore sales displacement. Journal of Marketing, 55(2), 17 – 28. Webster Jr., F. E. (1988, May – June). The rediscovery of the marketing concept. Business Horizons, 31(3), 29 – 39. Webster Jr., F. E. (1994a). Defining the new marketing concept. Marketing Management, 2(4), 23 – 31. Webster Jr., F. E. (1994b). Executing the new marketing concept. Marketing Management, 3(1), 9 – 16.
E.R. Wagner, E.N. Hansen / Industrial Marketing Management 33 (2004) 643–655 Weinfurter, S., & Hansen, E. N. (1999). Softwood lumber quality requirements: Examining the supplier/buyer perception gap. Wood and Fiber Science, 31(1), 83 – 94. Winer, R. S. (1999). Marketing management (p. 551). Upper Saddle River, NJ: Prentice-Hall. Wood Promotion Update, R. S. (2001, June 11). Available at: http:// www.wpnupdate.com/Nov/ (Accessed October 19 2002).
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Ernesto Wagner (PhD Oregon State University) has also a professional degree in Civil Engineering (1994) and an MS in Construction Management (1995) from the Catholic University of Santiago, Chile. Eric Hansen (PhD Virginia Tech) is Associate Professor and Extension Specialist, Department of Wood Science and Engineering, Oregon State University, Corvallis.
A method for identifying and assessing key customer group needs Ernesto R. Wagnera,*, Eric N. Hansenb,1 a
b
6844 NE Vinings Way, Apartment 2232, Hillsboro, OR 97124, USA Department of Wood Science and Engineering, College of Forestry, Oregon State University, Corvallis, OR, USA Received 10 February 2003; received in revised form 29 September 2003; accepted 8 October 2003 Available online 5 December 2003
Abstract This paper presents a methodology for identifying and weighing the importance of product attributes used by a key customer group of a company. A central feature of the technique is the introduction of a new concept: competition factors (CF). These factors address the influence of substitute products in the specific product attributes that a customer group considers. A better knowledge of substitute products can surface previously hidden or latent customer needs. CF allow dealing with this problem, providing a powerful tool for market-oriented businesses that seek to understand customers’ expressed and latent needs. The wood products industry and architects are used to illustrate the technique. D 2003 Elsevier Inc. All rights reserved. Keywords: Product attributes; Lead users; Latent needs; Architects; Competition factors
1. Introduction During the first half of the 20th century, companies equated marketing with selling (Graham, 1993; Webster, 1988). This selling orientation meant selling anything the factory could produce (Webster, 1988). Then in the mid1950s, the marketing concept was formulated. Marketing became customer focused, as the scarcity of resources and products during WWII was replaced by an abundance of manufacturers fighting for the patronage of consumers (Graham, 1993; Webster, 1988; Webster, 1994a). The marketing concept remained at the core of business activity for more than a decade but lost steam during the 1970s as strategic planning became the dominant paradigm (Day & Wensley, 1983; Webster, 1988). A loss of competitiveness by U.S. companies during the 1980s caused a rediscovery of the marketing concept (Webster, 1988). This was because strategic planning was too focused on competitors while customers were barely considered (Webster, 1988). In the meantime, the marketing concept evolved into three aspects: customer orientation, coordinated marketing efforts of the
* Corresponding author. Tel.: +1-503-679-6844; fax: +1-503-6480446. E-mail addresses: [email protected] (E.R. Wagner), [email protected] (E.N. Hansen). 1 Tel.: +1-541-737-4240; fax: +1-541-737-3385. 0019-8501/$ – see front matter D 2003 Elsevier Inc. All rights reserved. doi:10.1016/j.indmarman.2003.10.003
entire firm, and focus on profit rather than on sales volume (McGee & Spiro, 1988). Modern authors rephrase the marketing concept in the following way: the purpose of an organization is twofold, (1) to discover wants and needs of its target customers, and (2) to satisfy those needs in a better way than competitors, focusing on profit rather than sales volume (Slater & Narver, 1998; Webster, 1994b). Even though many years have elapsed since the marketing concept was elicited, much more research is needed in basic issues, like the determination of the target customers of a business and understanding their wants and needs. However, recent debate sheds light on this issue. The discussion refers to the difference between customer-led and market-oriented companies (Slater & Narver, 1998, 1999). While the first are primarily concerned with satisfying customers’ expressed needs and focus on short-term issues, the second seek to understand customer expressed and latent needs and try to develop innovative solutions for producing superior customer value (Slater & Narver, 1999). One weakness of customer-led companies is the ‘‘tyranny of the served market,’’ as managers of those firms see the world only through their current customers’ eyes (Slater & Narver, 1998). Current customer insights into new product needs are restricted by their real world experience and thus are unlikely to generate novel product concepts (Von Hippel, 1986). On the other hand, market-oriented companies employ innovative techniques in order to discover latent needs of their customers. One of those techniques is to
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survey lead users (Slater & Narver, 1998). Lead users are customers whose present needs will later become those of mainstream consumers (Ungson & Trudel, 2001; Von Hippel, 1986). Lead customers can identify latent needs because they are familiar with conditions that lie in the future for most other customers (Von Hippel, 1986). Lead users are early adopters that are watched and emulated later by the majority (Hawkins, Best, & Coney, 1998; Rogers, 1995). The current hypercompetition environment further complicates the problem, as a growing number of product alternatives mean increasingly dynamic customer behavior (Grimm & Smith, 1997). Shifting customer behavior helps explain product substitution, an area that deserves more attention since most investigations have analyzed product substitution in retail settings, specifically inside a product category (Anupindi & Dada, 1998; Walters, 1991). Only a few studies have considered product substitution beyond these boundaries. Eastin, Shook, and Fleishman (2001) examined trends of material substitution in the U.S. residential construction industry. They attempted to explain material substitution by analyzing the change in preferences over time by customers with regard to several product (material) attributes. The authors argued that any product can be differentiated from similar competing products by considering how these products vary among just a few attributes highly valued by end users. Given the preceding discussion, this article outlines a method for identifying a key customer group and the subsequent evaluation of their product wants and needs. The technique considers the influence of substitute products on the importance of product attributes. A better knowledge of substitute products can surface customer needs previously
hidden or latent. In this regard, the present research provides a tool for market-oriented businesses, which seek to understand both customers’ expressed and latent needs (Slater & Narver, 1999). An application with the wood products industry and a key customer group, architects, is used to illustrate the technique, which was successfully used in a larger study that sought to improve the customer orientation of wood products companies, while maintaining a competition focus, specifically on substitute products. Also important, because of the globalization of the wood products industry, we consider two countries: the United States and Chile. Chile is an interesting country to analyze, given that Chilean wood products are gaining significant market share in selected U.S. wood products markets (Wagner & Hansen, in press).
2. Conceptual model First, the conceptual model of the full project is explained as well as how this paper fits into the bigger picture. Fig. 1 shows a matrix depicting customer needs and company competitive advantages. Company competitive advantages are the basic blocks of business strategy, the elements to ponder in order to determine which are more important for satisfying customer needs, the ultimate focus of this research. Customer needs and competitive advantages are related through a relationship matrix, which allows transforming weights of customer needs into weights of competitive advantages. The whole matrix is an adaptation of the main quality chart or ‘‘house of quality’’ used in quality function
Fig. 1. Conceptual model (underlined areas show focus of this article).
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deployment (QFD) (Bossert, 1991; Cohen, 1995; Day, 1994). In a traditional QFD application, customer needs are compared with design parameters of products. In this study, customer needs are compared with the competitive advantages of companies. It is important to emphasize that this study considers competitive advantages of wood products companies. On the other hand, the customer needs correspond to material design attributes that go beyond the wood material. These design attributes allow a comparison between wood and substitute products, therefore assessing which attributes constitute features that wood must better satisfy in order to gain market share from competing products.
3. Methods 3.1. Selecting the customer group: overview Selecting a customer group is a key decision in any marketing study. It is not always evident which group of people is the most adequate to investigate in order to answer the questions of interest. In this case, use of QFD requires that customer groups must be analyzed separately. It is not advisable to combine weights of attributes of two or more groups of customers in the same matrix. The main problem stems from the difficulty of knowing the overall importance of one group of customers with respect to the other. On the other hand, a representative from one group cannot fairly compare the importance of their needs to the needs of a representative of another group; the representatives can only speak for themselves (Cohen, 1995). Therefore, any QFD application should select one and only one customer group. The customer selection process was focused on the construction industry, as new residential and nonresidential construction represents almost one half of U.S. sawn softwood consumption (United Nations Economic Commission for Europe, 2001). Therefore, trends in material substitution in the construction industry are directly impacting the wood products industry (Eastin et al., 2001). Indeed, steel wall framing and poured concrete floors have increased market share between 1997 and 2000, whereas wood lost an average 2.5% market share in walls, floors, and roofs during the same period (Wood Promotion Update, 2001). The market share lost by the wood products industry amounts to approximately US$270 million in annual revenue. Thus, it is relevant to investigate those customer groups involved in the material specification for residential and nonresidential projects. These specifiers may include architects, construction firms/contractors, structural engineers, and final owners. Nowadays, most new homes and apartments are built prior to sale; therefore, the owner of a new home has little influence on material selection. Construction firms, architects, and structural engineers, however, interact in the material (product) selection process.
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The overall question that the selected customer group must answer is, ‘‘What can increase the appeal of the product so that it will be selected instead of competing products?’’ In this case study, contractors were discarded as a possible customer group for two reasons: First, although construction companies actually buy the wood products, the influence of specifiers like architects or structural engineers in the material specification process of medium and large construction projects is very significant. Twenty interviews with architects and civil engineers in the United States and Chile verified the importance of their role. Architects are especially influential in projects where differentiation is a main concern, like high-end condominiums, showrooms, corporate headquarters, etc. On the other hand, the importance of civil or structural engineers grows in industrial projects. Second, previous research shows that it is very difficult to obtain a representative sample of contractors, with poor response rates that range between 7% and 14% (Alderman, 2001; Eastin et al., 2001; Fell, Gaston, Hansen, & Hovgaard, 2001). Based on this information, the customer group should be either architects or civil engineers, and further analyses were necessary in order to choose between these two customer groups. 3.2. Selecting the customer group: conjoint and cluster analyses Conjoint and cluster analyses were conducted in order to learn about the material preferences of the two professional groups of interest. In that regard, a sample of 20 civil engineers and architects was selected (5 U.S. engineers, 9 U.S. architects, 2 Chilean engineers, and 4 Chilean architects). Professionals from both countries were faced with the same Conjoint analysis design, basically a set of cards depicting different materials (wood, steel, concrete, and masonry) with different attributes (environmental sustainability, cost, and familiarity of the workforce with the material), in order to assess cultural and professional differences. Use of conjoint analysis showed a difference between the sampled Chilean and U.S. architects (and engineers) regarding environmental issues. The U.S. architects were very aware of environmentally certified (green) wood products. They try to foster the use of environmentally friendly products, as was clearly pointed out during the personal interviews. With one exception, U.S. engineers were not aware of environmentally certified wood products. Also, neither Chilean architects nor engineers consider environmental issues as an attribute when selecting a material. Table 1 shows the utilities (regression coefficients with reversed signs) of the attribute ‘‘environmentally sustainable’’ for the 20 respondents (sustainability: ‘‘a state or process that can be maintained indefinitely’’) (IIDA, 1999, p. 2). It is remarkable how well this attribute separates professionals from the two countries. It is important to emphasize that respondents could not fabricate these utilities
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Table 1 Utilities (in decreasing order) of the attribute ‘‘environmental sustainability’’ for U.S. and Chilean architects and engineers U.S. U.S. U.S. U.S. U.S. U.S. U.S. U.S. U.S. U.S.
engineer engineer architect architect architect architect architect architect architect engineer
2.00 2.00 2.00 2.00 1.50 1.50 1.50 1.25 0.75 0.75
Chilean engineer Chilean architect U.S. engineer U.S. engineer U.S. architect U.S. architect Chilean engineer Chilean architect Chilean architect Chilean architect
0.75 0.50 0.25 0 0 0 0 0.25 0.50 0.50
(part worths) because they were implicit in their answers regarding material preferences. Cluster analysis grouped individuals according to demographic information as well as the likeness of their preferences; in other words, the procedure grouped respondents according to the similarity of the importance (utilities) they assigned to each attribute in the conjoint analysis application. The most interesting clustering resulted when using all variables and when labeling by profession and country. The dendogram in Fig. 2 shows how respondents are linked together according to the similarity of their preferences. The more to the right the vertical link between two respondents, the more dissimilar they are. The sampled U.S. professionals tended to fit in one cluster (Group 1 in Fig. 2) while Chilean professionals tended to fit in another cluster (Group 2 in Fig. 2), suggesting that cultural differences make the product (material) preferences of professionals in the two countries radically different. This result indicated that separate matrices like Fig. 1 would be necessary for each country. In order to test the objectivity of the clusters, a set of t tests was carried among the clustering variables (Harrigan, 1985) in order to assess differences among the clusters with respect to each of the variables. The t tests showed a
statistically significant difference in four of the seven clustering variables (two-sided P values < .05), somewhat supporting the objectivity of the clusters. A K-means clustering algorithm was also used, requiring two groups. This algorithm rendered all U.S. professionals but one in one of the clusters, providing additional evidence of a difference between the United States and Chile. It is important to comment that the difference between the two countries persisted, even when ‘‘environmentally sustainable’’ was not considered as a clustering variable. Finally, and most important for this research, clusters tended to have both architects and engineers of a certain country (either the United States or Chile). In other words, the data suggest that even if the importance of ‘‘environmentally sustainable’’ separates architects from engineers, it seems that the other attributes blur that difference and make professional groups of a single country quite similar when considering all the attributes. The small sample size makes any inference to the total populations only tentative. Still, the objective of the analyses was to compare, even in a limited fashion, the material preferences of architects and engineers. The results are consistent with those of Kozak and Cohen (1999), who found almost no significant differences between architects and engineers regarding construction material preferences. Architects, and not structural engineers, were selected as the customer group for this study for two reasons. First, environmentally friendly (green) buildings are a growing trend, as reflected by the numerous related conferences and even associations that have been created. Therefore, this study intended to measure the environmental preferences of a lead customer involved in the material selection decision for construction projects (Von Hippel, 1986). The results of the conjoint and cluster analyses unequivocally point at architects as the most environmentally concerned professional group. Indeed, architects are seen to be a lead customer group regarding environmental issues (IIDA,
Fig. 2. Architects and engineers dendogram using average linkage (between groups).
E.R. Wagner, E.N. Hansen / Industrial Marketing Management 33 (2004) 643–655 Table 2 Wood product groups as defined by architects
3.3. Identifying customer wants and needs
Product groups
Product properties that are important for each group
Specific products that fit into the groups
Structural products group
Strength and structural properties Aesthetic properties
Softwood lumber + softwood plywood + oriented strand board Hardwood decorative panels + moldings + finishing materials GlueLam, I-Beams, etc.
Appearance products group Engineered wood products group
Strength and aesthetic properties
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A second set of personal interviews was conducted with practicing architects (4 in Chile and 13 in the United States). The interviewees were carefully selected to ensure a good variety of respondents. In the United States, the size of both the company and the city where the architect worked was an important criterion used when selecting the respondents. It is important to note that the interviews were just intended to identify customer wants and needs; thus, a small number of interviews were able to accomplish this task. However, the measurement of the importance of each customer want and need required a representative sample of architects; thus, a nationwide mail questionnaire was used, as is described below. The architect interviews included two parts. The purpose of the first part was to identify a classification of wood products consistent with the way architects specify wood
1999; Von Hippel, 1986). Second, the wood products industry targets architects with environmental advertising and therefore were an appropriate group for this research (Wagner & Hansen, in press).
Table 3 Attributes weights and categorization for U.S. wood products Mean
S.D.
HSD method1
CF
New means due to CF
Range method1
Final groups1
U.S. structural products Material available Uniform quality Dimensionally stable Adaptability2 Durability Knowledgeable work force Low cost Environmentally sustainable Fire concern
5.83 5.63 5.53 5.54 5.17 5.14 4.97 4.96 (4.80 – 5.17) 4.23
0.89 1.25 1.29 1.16 1.41 1.40 1.34 1.49 1.60
a a b b b b b b c
1.5 1.8 1.8 1.5 1.5 1.5 1.5 1.5 1.2
8.75 10.14 9.96 8.30 7.75 7.72 7.45 7.2 – 7.76 5.07
a a a b b b b b c
a a a b b b b b c
U.S. appearance products Appearance, warmth, tactile Honest material Off gassing3 Environmentally sustainable Durability Low cost
5.83 5.44 4.87 4.87 (4.69 – 5.08) 4.84 4.50
0.98 1.40 1.60 1.56 1.60 1.38
a a b b b b
1.5 1.5 1.2 1.5 1.5 1.5
8.74 8.17 5.85 7.04 – 7.62 7.26 6.75
a a b b4 b b
a a b b4 b b
U.S. engineered wood products Uniform quality Dimensionally stable Strong material Adaptability Environmentally sustainable Feasibility of curves5 Low cost Off gassing Appearance, warmth, tactile
6.05 6.03 5.90 5.39 5.05 (4.84 – 5.31) 4.76 4.76 4.43 4.16
0.87 0.94 0.99 1.17 1.47 1.54 1.29 1.68 1.74
a a a a b b b c c
1.8 1.8 1.2 1.5 1.5 1.5 1.5 1.2 1.2
10.89 10.86 7.07 8.09 7.26 – 7.97 7.13 7.13 5.32 4.99
a a b b b b b c c
a a b b b b b c c
1 This table illustrates two classification methods for the attributes on the left column. The HSD method and the Range method classify the means in a maximum of three groups: a, b, and c. Attributes in one group (say ‘‘a’’) are not significantly different from each other, but any two attributes of two different groups (say ‘‘a’’ and ‘‘b’’) are different. The range method does consider the competition factors; thus, it was the categorization method preferred by this study (final groups are the groups defined by the range method). 2 Adaptability refers to the simplicity with which wood elements can be trimmed to the correct length. 3 Off gassing refers to the concern about harmful vapors coming out of a material when in use. 4 The variability of the importance may make this attribute to belong to either the ‘‘a’’ or the ‘‘b’’ category. 5 Feasibility of curves refers to either the possibility of installing the wood material over a curved surface or to build curved wood elements, like curved laminated beams.
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materials. Thus, a preliminary classification was constructed based on personal knowledge and a literature review. The interviews confirmed the adequacy of the preliminary product groups: a structural group where the main requirements are strength and structural properties; an appearance group where aesthetics is the key requirement; and an engineered wood products group where both strength properties and appearance issues are relevant. Architects unanimously supported this categorization as one that fits the way they select construction materials. Table 2 defines the groups in more detail. The second part of the interview was an open question asking architects about the good and bad characteristics of wood products. They were also asked about what can increase the appeal of wood so that it would be preferred over competing materials, like steel, concrete, or plastics. Respondents answered the same question for each of the three product groups. The different number of interviews in the United States and Chile (13 and 4) required the use of a different criterion for identifying the final set of attributes utilized in each country. In the Chilean case, the small number of interviews meant that we kept all attributes
named by the interviewees, whereas in the Unites States only the attributes named by at least four persons were kept. Architects used a very similar language for expressing the design concepts they consider, making attribute categorization and identification easy. The actual attributes determined through the interviews are shown in the first column of Tables 3 and 4. The described methodology is equally applicable for single products or for product groups. In the first case, Tables 3 and 4 would be only a list of attributes, without the subsections defined by the product groups. Still, the techniques for determining the customer needs and the weights of those described in the next section are exactly the same. 3.4. Determining weights of customer needs A carefully constructed mail questionnaire was developed based on information from interviews and the extant literature in order to assess the importance of the attributes identified through the interviews. The United States and Chilean cases were analyzed separately.
Table 4 Attributes weights and categorization for Chilean wood products1 Mean
S.D.
HSD2 method
CF
New means due to CF
Range2 method
Final2 groups
Chilean structural products Structural properties Durability and maintenance Uniform quality Appearance Low cost Fast construction Fire concern Lack of constructive solutions
5.91 5.79 5.75 5.60 5.25 5.15 4.79 4.02
1.18 1.20 1.31 1.27 1.28 1.42 1.49 1.64
a a a a a a a b
1.2 1.2 1.2 1.5 1.2 1.2 1.2 1.2
7.09 6.95 6.90 8.40 6.30 6.18 5.75 4.82
a a a a a a b b
a a a a a a b b
Chilean appearance products Appearance, warmth, tactile Honest material Durability and maintenance Feasibility of curves Material easy to refurbish Low cost
6.58 6.19 5.87 5.32 5.23 4.42
0.57 0.90 0.90 1.46 1.32 1.26
a b b b b c
1.5 1.5 1.5 1.5 1.2 1.8
9.87 9.29 8.81 7.98 6.28 7.96
a a a b c b
a a a b c b
Chilean engineered wood products Uniform quality Durability and maintenance Appearance Feasibility of curves Fire concern Glue quality Low cost Lack of competitors Lack of constructive solutions
6.10 6.06 6.00 5.88 5.77 5.60 5.04 4.88 4.74
0.81 0.98 1.00 1.16 1.11 1.41 1.33 1.34 1.61
a b b b b b b b c
1.44 1.5 1.5 1.5 1.2 1.2 1.44 1.5 1.2
8.78 9.09 9.00 8.82 6.92 6.72 7.26 7.32 5.69
a a a a b c b b c
a a a a b c b b c
1
In this case, just one person provided the competition factors. This table illustrates two classification methods for the attributes on the left column. The HSD and range methods classify the means in a maximum of three groups: a, b, and c. Attributes in one group (say ‘‘a’’) are not significantly different from each other, but any two attributes of two different groups (say ‘‘a’’ and ‘‘b’’) are different. The range method does consider the competition factors; thus, it was the categorization method preferred by this study (final groups are the groups defined by the range method). 2
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3.4.1. U.S. mail questionnaire In the United States, a nationally representative measure of the opinion of the owner or chief architect of architect offices was pursued. These individuals would be the most knowledgeable about design and material selection. The mailing process was an adaptation of the tailored design method (Dillman, 2000). Questionnaires (1200) were sent, expecting a response rate of about 30% while still meeting the target of approximately 380 returned questionnaires, for a sampling error of 5% (Dillman, 2000). Three hundred and seventy-five validly answered questionnaires were received, for a 34% response rate, discounting nondeliverables. This response rate compares well with other studies that involved architects (Damery & Fisette, 2001; Kozak & Cohen, 1999). The next lines describe only how the nonresponse error was controlled, although the two other types of survey error were also monitored, namely, coverage and measurement (Dillman, 2000). Regarding nonresponse error, a common method is to assume that late respondents (second mailing) are more similar to nonrespondents than early respondents (first mailing) (Armstrong & Overton, 1977). Early respondents were compared to late respondents on a total of 30 attributes, and only one statistically significant difference was found (two-sided P value < .05 from t tests). One significant P value out of 30 can happen just by chance, so there is no evidence of nonresponse error. 3.4.2. Chilean questionnaire Cultural reasons make it very difficult to obtain survey responses in Chile. Mail questionnaires inevitably end up in the trash. Therefore, the approach was to select a convenience sample of the largest architect offices (sample size of 85), most of which are located in the Santiago metro area. This fact reflects the importance of this city in the whole nation, as it contains 40% of its population and about 40% of its gross national product (Instituto Nacional de Estadisticas (INE), 2003). Importantly, the Chilean survey was conducted in Spanish and it incorporated the design attributes identified through the Chilean interviews. The survey methodology used, feasible because of the small sample size, was to first send the questionnaire by mail and then follow-up by phone. On average, each architect office was called 15 times to obtain the 53 answers (a 62% response rate). 3.5. Competition factors (CF) Certain characteristic(s) of a construction material (say, dimensional stability) induces customers to select it as the product to be used (e.g., steel) instead of competing products (Eastin et al., 2001). Clearly, some products inherently meet specific quality characteristics better than others. Surveys are generally ineffective for identifying those differences among products because respondents answer questionnaires with too narrow a notion of competing products or substitutes. Knowledge of substitute products
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helps surface latent customer needs. Introduction of CF is a way to deal with this problem, providing a powerful tool for market-oriented businesses (Slater & Narver, 1999). To understand CF, is essential to introduce Kano’s quality typology (Cohen, 1995), which divides quality characteristics into three different categories: 1. Expected quality: These are characteristics of the product that the customer expects to be present. Customers normally do not ask for them in market research; but if this quality is absent, it causes dissatisfaction (therefore called dissatisfiers) (Bossert, 1991, Cohen, 1995). 2. Desired quality: These characteristics, also called satisfiers, are something that customers want in their products and usually ask for them in surveys. The more of a satisfier, the happier customers will be (Cohen, 1995). 3. Exciting quality: These characteristics, called delighters by Cohen (1995), are product attributes that are pleasant surprises that greatly satisfy customers when they first encounter them (like happened several years ago with cup holders in cars). By definition, customers cannot expect exciting quality, so if this kind of characteristic is missing, customers will not be dissatisfied (Akao, 1990). This typology closely resembles the concepts of expected and augmented product (Levitt, 1980, Slater & Narver, 1999). The expected product corresponds to what the customer considers the minimum acceptable benefits that the product must comprise, while the augmented product encompasses benefits that satisfy latent needs. In other words, an augmented product satisfies needs that have not yet been addressed by current products. CF introduce the product substitution influence into the problem by taking into account the existence of customer needs that correspond to either expected or exciting qualities (expected or augmented product). The competition factor of each attribute is formed by the multiplication of the improvement ratio and the sales point, constituting an adaptation of the method applied by Cohen (1995) (see Fig. 3), as explained below. Improvement ratio: If steel, concrete, or a plastic product meets an architect requirement, another material, like wood, is expected to fulfill the requirement at least equally well (expected quality). Undoubtedly, such an attribute is more important to satisfy than a requirement where the competition of wood does not do well at all, which can constitute a delighter (exciting quality), as has been discussed previously. The improvement ratio enhances the importance of attributes where the product of interest (wood) is in a disadvantageous position regarding substitute products and thus is ‘‘product specific’’ (Fig. 3). A good example of a requirement that wood does not meet well is dimensional stability. Wood swells or contracts when relative humidity changes, while a piece of steel maintains its size; thus, architects may (and in fact they do) request an important
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Fig. 3. CF for wood (product of interest) considering substitute products (steel, concrete, and plastics).
improvement for this feature in the wood material, thus it exhibits a high improvement ratio. Sales point: The sales point enhances the importance of attributes that encourage sales on their own, regardless of the type of product that is considered, and thus is ‘‘attribute specific.’’ The sales point may show issues where wood is in an advantageous position regarding substitute products (Fig. 3). A good example of such an issue is the ‘‘warmth’’ of a material, as wood reportedly creates environments where people like to work. On the contrary, many people do not like environments with predominant steel or concrete (Ridoutt, Ball, & Killerby, 2002a, 2002b). The CF were determined using expert opinion. Three architects in the Unites States provided values for the improvement ratio and sales point according to the rule depicted in Fig. 3. The Delphi technique was used to gather expert opinion (Clayton, 1997). Reasonable convergence was defined by answers that could not contain extremes, i.e., the combination of levels 1.0, 1.0, and 1.2 was acceptable, but not 1.0, 1.0, and 1.5. In the first round of the U.S. case, perfect agreement (for example, 1.0, 1.0, and 1.0) was reached in 39 of the 48 decisions (24 attributes, 2 decisions per attribute). Convergence was reached in the second round. In the Chilean case, only one architect could be reached to provide values for the CF. The values of that single person are being used. The final CF are reported in the central column of Tables 3 and 4.
4. Analysis Tables 3 and 4 report the customer needs for the United States and Chile, respectively. The respondents were asked to assign a value for each attribute in each product group according to the level of importance that the feature has in the material specification process. The scale used corresponds to a 1 to 7 Likert-type scale, from 1 = less important to 7 = more important. Tables 3 and 4 display the attribute names and their mean and standard deviation in the three left columns. The remaining columns depict two categorization systems. The CF are reported in the middle of the charts. The categorization of attributes in importance groups was based on statistical significance. In that respect, attributes were categorized in a maximum of three groups: ‘‘a’’ for important attributes, ‘‘b’’ for attributes of medium impor-
tance, and ‘‘c’’ for attributes of low importance. The notion is that attributes inside a group (say, ‘‘a’’ attributes) are not significantly different among each other, but the difference becomes significant if attributes from two importance groups are considered (if comparing, say, attributes from groups ‘‘a’’ and ‘‘b’’). Two categorization systems were developed: the first (honest significant difference method or HSD) is a strictly statistical technique, whereas the second method (range method) introduces the CF into the problem. The classification of attributes in importance groups incorporating the CF is a key feature in the intent to determine which attributes are really important for satisfying customer needs while considering the influence of substitute products. 4.1. HSD categorization method The allocation of attributes to groups according to their level of importance can be approached in several ways. Each of the attributes will be considered as an independent sample, and therefore the analysis will correspond to multiple comparisons of means (Ramsey & Schafer, 1997). The large number of all pairwise comparisons compounds statistical uncertainty. The method selected for this problem is the Tukey HSD, which considers a family-wise confidence level (Ramsey & Schafer, 1997). Two means, yi and yj, are declared not equal if jyi yjj>HSD; HSD = multiplier S.E., multiplier is the q (a, number of groups, degrees of freedom) statistic that can be obtained from a studentized range distribution (Kuehl, 2000). The methodology orders the means from smallest to largest. The biggest range (means 1 and n) is analyzed and the rule for equality of means is tested. If the difference between the means is larger than HSD, then means 1 and (n 1) are analyzed and also means 2 and n. If the difference is still larger than HSD, the range then diminishes to 2 and (n 1) and so on. Significance was set at 1% due to the large sample sizes (a=.01). In the case of U.S. structural products, the 1% significance determined an HSD of .5. The group of means that was found not significantly different was the set with a maximum of 5.5 (adaptability, dimensionally stable) and a minimum of 5 (environmentally sustainable, low cost): the attributes in that set obtained a ‘‘b’’ importance. Means above and below that set are considered to be in other groups: ‘‘a’’ and ‘‘c,’’ respectively. Eventually, only two groups are defined or even one, depending on the dispersion
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of the means of the attributes. U.S. appearance products and Chilean structural products are cases where less than three groups were defined. 4.2. CF and range method The CF introduce the effect of substitute products on the means, as well as the problem of different types of qualities, some of them more important to meet than others. The CF were multiplied with the old means to produce what is called ‘‘new means due to CF’’ (see Tables 3 and 4). These new means were categorized using a range method, which does not take into account the standard deviations. So, for U.S. structural products, the difference between the maximum and the minimum new means (range) was 5.07. The number of segments defined by HSD is used so the range is divided by three in order to define three segments: 5.07/ 3 = 1.69, which determines the segments ‘‘a’’: 8.47 –10.16, ‘‘b’’: 6.77 –8.46, and ‘‘c’’: 5.07– 6.76. The same procedure was followed with all product groups. Thus, at the end, we had two categorization methods. The range method was chosen between the two because it takes into account the CF. It is important to emphasize that the HSD technique is still providing the number of segments for each product group even when using the range method. The HSD and range methods produce quite similar segments in the U.S. case, providing evidence of internal consistency (Bagozzi, 1994, chap. 1). That is not the case with the Chilean product groups where the methods produce quite different results. The categorization of the range method was still kept in the latter case.
5. Results The design attributes and specification criteria used by architects are reported in the following paragraphs. First, results of the U.S. study are discussed, followed by a cross-cultural comparison between the Unites States and Chile.
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nowadays more concerned about other aspects of wood materials, essentially technical issues, than about price of the material or sustainability. This outcome shows that although qualitative research is useful for learning and providing input for further research, the quantitative results may actually differ from interviewer perceptions acquired during the qualitative part of the study (Winer, 1999). It was expected that the attribute environmentally sustainable would have a different importance in different areas of the United States, as the attitude of architects towards the environment may not be the same across the nation. In this regard, the importance of the attribute environmentally sustainable of the structural product group was analyzed in four regions of the United States. There is suggestive evidence of a statistically significant difference (one-way ANOVA analysis: P value of .065). The West region (Hawaii, Washington, Oregon, and California) was the highest with an average of 5.3 (on a scale of 1 to 7), and the averages for other regions were 5.0, 5.0, and 4.6. If the West is taken out of the analysis, the other three regions were not significantly different from one another (one-way ANOVA analysis: P value of .25). ‘‘Dimensionally stable’’ is a U.S.-exclusive attribute that received high scores in both the structural and engineered wood products categories. Dimensional stability is something that wood does not meet well, as compared with a competing material like steel. Thus, it was expected that dimensionally stable would be an attribute that would receive a high improvement ratio by architects. Consistently, it received an improvement ratio of 1.5 that caused the only change in the categorization of U.S. structural products, if comparing the HSD and the range method: dimensionally stable rises to the ‘‘a’’ category when using the range method. Consideration of substitute products is one of the distinctive features of the methodology presented in this article. The CF showed that dimensionally stable is more important than what the raw measure of its importance shows. 5.2. Cross-cultural comparison of architect needs and preferences
5.1. U.S. results Environmentally sustainable and low cost are two attributes that appear in all three product segments. It was surprising that these two attributes received low scores, especially in the case of environmentally sustainable because this attribute was regarded as very important during the personal interviews. ‘‘Environmentally sustainable’’ ranks in the bottom three in both the structural and the appearance group but achieves a better position in the engineered wood products group. This makes sense as these products were introduced as environmentally friendly. The lower relative importance of environmentally sustainable and low cost indicates that perhaps U.S. architects are
The following are several interesting similarities and dissimilarities between Chile and the Unites States. The U.S. interviews clearly identified an environmentally related attribute in the three product groups. On the other hand, Chilean architects did not mention an environmentally related attribute in any of their product groups. This is consistent with the results of the conjoint analysis where Chilean architects generally did not show positive part worths for the attribute environmentally sustainable. Uniform quality is an attribute that is in the top three regardless of the country considered. During the U.S. interviews, architects complained about a general decrease in the quality of wood products, a message consistent with the
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findings of Hansen and Bush (1996) and Weinfurter and Hansen (1999). Fire concern is much lower than the literature suggests (Kozak & Cohen, 1999). In the case of the United States, it was hypothesized that fire concern would have a lower importance in the Northwest because wood is the traditional Northwest material. This attribute was tested for differences among four U.S. regions and no statistically significant differences were found ( P value=.10 from a one-way ANOVA). The most interesting result concerns the appearance group. Despite the language difference, architects from both countries worded two attributes in the same way and those attributes received the two highest scores in the product group, regardless of country. The attributes are as follows: appearance, warmth and tactile sensation of the material, and honest material. Architects of both countries expressed in the interviews that the grain and texture of wood are unique; thus, appearance does not explain the concept adequately. Instead, appearance, warmth, and tactile sensation give a holistic approach to the concept. On the other hand, honest material simply means that architects like that the material is what it seems to be.
6. Limitations This study has limitations. First of all, one half of the interviewed U.S. engineers and one third of the interviewed U.S. architects studied in Oregon universities. The interviews just provided the attributes, not the weights of the attributes, but the local tastes may have influenced the answers used in the conjoint and cluster application. Also important, the U.S. results come from a random sample drawn from a population of 115,000 architects. These results are much more generalizable than Chilean results drawn from a convenience sample. The Chilean component of this work provides great insights regarding the difficulty of performing marketing studies in other countries regardless of language differences. Chilean architects (and people in general) are well known for not cooperating with any survey or interview effort. This difficulty was apparent in this project, and personal contact and considerable patience were invaluable for obtaining answers. Cross-gender comparisons of preferences in the United States were impossible because 93.9% of the respondents were male (352 out of 375). Still, the survey was successful in reaching the owner of each architect office. Only 40 out of the 375 respondents (10.6%) were nonowners. Data analysis revealed an important source of error regarding the order in which the attributes inside each product group were presented to respondents. Dillman (2000) suggests that people analyze all the categories before answering a question in a questionnaire but also notes that some research indicates otherwise. Before conducting the
study, both environmentally sustainable and low cost were expected to be highly rated. Thus, half of the questionnaires sent out had environmentally sustainable and low cost in the first and second position, while the other half had them in the last and second-to-last position. Although low cost did not show a statistically significant difference, the mean importance of environmentally sustainable was significantly different in each of the three product groups. Indeed, this last attribute received a higher weight when placed at the end than when placed at the beginning of the set of attributes regardless of the product group (two-sided P values of .02, .02, and .004 from t tests) (the weights of environmentally sustainable when placed at the beginning and when placed at the end are shown between parentheses next to the mean of the attribute in Table 3). This variability means environmentally sustainable may fit in either the ‘‘b’’ or ‘‘a’’ category of the appearance group. The other groups did not show changes in the attribute memberships. This result suggests that most respondents did not read all the attributes before assigning the weights. Environmentally sustainable receives a higher rating when placed at the end because respondents have already evaluated the other attributes. When in the first position, the respondent does not have a frame of reference for estimating the importance of environmentally sustainable. The other attributes are of a technical nature so we do not expect a similar problem. Environmentally sustainable is a social context attribute. Thus, its importance would increase after considering technical issues. Low cost, a practical attribute, supports this proposition because it was rated similarly regardless of its position in the questionnaire.
7. Contributions The main contribution of this research effort is the development of a methodology for selecting a customer group of a company, and subsequently categorizing its customer wants and needs. Consideration of the influence of substitute products on the importance of product attributes constitutes another contribution, as market-oriented businesses need innovative techniques for learning about both expressed and latent needs of their customers. The multidisciplinary nature of the research, which unites concepts of marketing, total quality management, and strategy, is also notable.
8. Managerial implications The methodology presented in this article is applicable to any industry and any customer group. In that regard, there are two main areas that should be of interest for managers. First, a common problem in real business settings is the need to deal with different customer groups, while time or money constraints may mean focusing marketing research
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efforts on only one. This study provides a comprehensive approach for selecting a key customer group, which considers both practical issues like the inability to obtain reasonable response rates from certain customer groups and more theoretical matters like testing the objectivity of clusters of customers. Second, a better understanding of substitution dynamics would benefit any company. As an illustration, retail executives can apply the CF concept to the opening of a new supermarket in an area of a city attended by an existing store. The new supermarket may offer new and superior service, like accepting debit cards, while the older establishment only accepts cash and checks. While this
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offering is initially an exciting quality, as consumers become accustomed to the service, it may evolve into an expected quality. Thus, even if the existing supermarket is otherwise very convenient, the lack of some key features (debit card) might cause important dissatisfaction among its traditional customers who may change their buying habits. It is important to note, however, that substitute products may really complement the offer and not drive the obsolescence of the former product. That is the case of the fax machine. This machine proved much more convenient and affordable than telex, causing the immediate obsolescence of the latter. Interestingly, although electronic mailing is
Fig. 4. Key customer group selection and study: a step list for industrial customers.
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even more convenient than fax in some regards, the ability to send forms filled by hand or to draw pictures or write annotations over documents that are subsequently sent corresponds to previously hidden needs that the fax machine satisfies better than e-mail, and that enables the fax to still have a place in offices around the world. Fig. 4 presents a summarized step list for managers willing to apply the methodology introduced by this study to their particular business situation. The procedure can be applied to either industrial (professional) customers or to final consumers. Although the step list is equally applicable to either one, the selection of the right customer is arguably more difficult in the case of industrial customers, as product selection decisions may be influenced by several different individuals (professional customers). The article provides an excellent example in this regard. Finally, it is important to emphasize that many previously unrelated industries have become direct competitors. Examples abound in the communications business, where computer-to-computer phone calls are competing directly with normal long distance calls. Therefore, the examination of attributes of any product should consider the influence of substitutes, as this analysis may allow maintaining the patronage of increasingly elusive customers. References Akao, Y. (1990). Quality function deployment: Integrating customer requirements into product design (p. 367). Cambridge, MA: Productivity Press. Alderman, D. R. (2001, April 12). An investigation into attitudes towards recycling CCA treated lumber. PhD thesis. Wood Science and Forest Products, Virginia Polytechnic Institute. Anupindi, R., & Dada, M. (1998). Estimation of consumer demand with stock-out based substitution: An application to vending. Marketing Science, 17(4), 406 – 423. Armstrong, J. S., & Overton, T. S. (1977, August). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14, 396 – 402. Bagozzi, R. P. (1994). Measurement in marketing research: Basic principles of questionnaire design. In R. Bagozzi (Ed.), Principle of marketing research ( pp. 1 – 49). Oxford, UK: Blackwell, Chapter 1. Bossert, J. L. (1991). Quality function deployment a practitioner’s approach (p. 127). New York: Marcel Dekker. Clayton, M. J. (1997, December). Delphi: A technique to harness expert opinion for critical decision-making tasks in education. Educational Psychology, 17(4), 373 – 386. Cohen, L. (1995, May). Quality function deployment: How to make QFD work for you (p. 348). Reading, MA, USA: Addison-Wesley Publishing (First printing). Damery, D. T., & Fisette, P. (2001). Decision making in the purchase of siding: A survey of architects, contractors and homeowners in the U.S. Northeast. Forest Products Journal, 51(7/8), 29 – 36. Day, G. S. (1994, October). The capabilities of market-driven organizations. Journal of Marketing, 58, 37 – 52. Day, G. S., & Wensley, R. (1983, Fall). Marketing theory with a strategic orientation. Journal of Marketing, 47, 79 – 89. Dillman, D. A. (2000). Mail and internet surveys: The tailored design method (2nd ed.) (p. 464). New York: Wiley. Eastin, I. L., Shook, S. R., & Fleishman, S. J. (2001). Material substitution in the US residential construction industry, 1994 versus 1998. Forest Products Journal, 51(9), 30 – 37. Fell, D., Gaston, C., Hansen, E., & Hovgaard, A. (2001, March). Attributes
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Ernesto Wagner (PhD Oregon State University) has also a professional degree in Civil Engineering (1994) and an MS in Construction Management (1995) from the Catholic University of Santiago, Chile. Eric Hansen (PhD Virginia Tech) is Associate Professor and Extension Specialist, Department of Wood Science and Engineering, Oregon State University, Corvallis.