The structure of design orientation and its relationship with market orientation

Rocco, Sanja; Selinšek, Aleksandra Article The structure of design orientation and its relationship with market orientation Naše gospodarstvo / Our Economy Provided in Cooperation with: Faculty of Economics and Business, University of Maribor Suggested Citation: Rocco, Sanja; Selinšek, Aleksandra (2019) : The structure of design orientation and its relationship with market orientation, Naše gospodarstvo / Our Economy, ISSN 2385-8052, Sciendo, Warsaw, Vol. 65, Iss. 3, pp. 50-62, https://doi.org/10.2478/ngoe-2019-0013 This Version is available at: https://hdl.handle.net/10419/290448 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ 50 The Structure of Design Orientation and its Relationship with Market Orientation Sanja Rocco Zagreb School of Business, Croatia [email protected] Aleksandra Selinšek University of Maribor, Faculty of Economics and Business, Slovenia [email protected] Abstract Although market orientation has been investigated in numerous studies, its complex relationship with design orientation lacks research attention, especially in countries with transitional economies. Therefore, existing models of market orientation (MO) and design orientation (DO) have been investigated. The research has been executed in several stages, combining qualitative and quantitative methods. In the first, qualitative stage, a series of face-to-face in-depth interviews were conducted. In the second, quantitative stage, an Internet survey was conducted among managers and CEOs from Croatian companies in different industries. Partial Least Square and Structural Equation Modelling analyses were conducted to examine the relationships between variables of MO and DO. Results confirm the positive relationship between design orientation and market orientation. Further, results also confirm sub-hypotheses that customer orientation and strategic marketing are positively related to all dimensions of design orientation. The model could have implications for marketers, designers and managers in practice. Both concepts, MO and DO, are very complex and multidimensional, so it was not possible to investigate all the aspects of the constructs. Another limitation of the study was the sample size, as a result of a low response rate as well as a relatively high drop-out rate. The research contributes to theory highlighting the role of design as an important element of market orientation. Keywords: design orientation, market orientation, managers, relationship, transitional economies Introduction Concepts in marketing have been continuously developing throughout its history. Today, marketing engages an organization’s resources, skills, products, services, and thinking to understand and meet consumers’ conscious and latent needs (Bogozzi, 2011). Customers are looking for added value, while in most industries technical and functional qualities are taken for granted. With regard to responding to customer needs, some recent marketing literature mentions three crucial concepts: market orientation, customer orientation, and design orientation (Coley, Mentzer, & Cooper, 2010; Gummesson, 1991; Moll, Montana, NAŠE GOSPODARSTVO OUR ECONOMY pp. 50–62 ORIGINAL SCIENTIFIC PAPER Citation: Rocco, S., & Selinšek, A. (2019). The Structure of Design Orientation and its Relationship with Market Orientation. Naše gospodarstvo/Our Economy, 65(3), 50–62. DOI: 10.2478/ ngoe-2019-0013 DOI: 10.2478/ngoe-2019-0013 UDK: 339.138:7.012:005.311 JEL: M310 RECEIVED: JUNE 2019 REVISED: JULY 2019 ACCEPTED: AUGUST 2019 Vol. 65 No. 3 2019 51 Sanja Rocco, Aleksandra Selinšek: The Structure of Design Orientation and its Relationship with Market Orientation Guzman, & Praallada, 2007; Venkatesh, Digerfeld-Mansson, Brunel, & Chen, 2012). Comparison of the design-orientation literature (Chitturi, Raghunattan, & Mahajan, 2008; Moll et al., 2007; Srinivasan et al., 2006; Verizer et al., 2005) and market-orientation literature (Gummesson, 1991; Kohli, Jaworski, & Kumar, 1990, 1993) indicates that customer-centered product design strategies are critical to superior market performance and success. Many authors discuss the fact that market orientation has a positive impact on a company’s economic result in the market (Bodlaj, 2010; Kahn, 2001; Kohli et al., 1993; Jaworski et al., 1993; Narver & Slater, 1990; Snoj, Milfelner, & Gabrijan, 2007). Slater and Narver (2000) suggest that market orientation is one component in the architecture of a learning organization that leads to superior learning capability. They believe that this replication provides strong support for the existence of a positive relationship between market orientation and performance and that future research should focus on the processes for developing and reinforcing a market-oriented culture, as well as for implementing it through organizational structure, systems, capabilities, and strategies. According to Bodlaj (2010), existing empirical research adopting both forms of MO (responsive and proactive) and examining the impact on new-product performance (Atuahene-Gima, 2005; Narver et al., 2004, Tsai et al., 2008) or business performance (Voola & O’Cass, 2010) is still very limited and has mostly been conducted in non-European countries. Only a few studies have examined the entire chain of relationships between both market orientation types, innovation and business performance (e.g., Milfelner, 2009). On the other hand, quite a similar situation can be seen in the case of design orientation. This is a concept that has been a subject of various studies in recent years, but mostly in developed countries. Additionally, various studies have shown evidence that there is a positive relationship between investing in design and improved business results (e.g. Black & Baker, 1987; Borja de Mozota, 2003b; Bruce, Potter, & Roy, 1995; Design Council, 2004-2014; Gemser & Leenders, 2001; Hertenstein, Platt, & Veryzer 2005; Kootstra 2009; Sisodia, 1992; Slater & Narver, 2000; Ulrich & Pearson, 1998; ). Investigating the impact of design orientation in Croatian companies as well as the complex relation between design orientation and market orientation is the main purpose of this study. The paper begins with the theoretical background of the researched topic and continues with the development of the conceptual model and hypothesis. Next, the research methodology and results of the research are described. Finally, conclusions, implications and limitations of the study are presented. Theoretical Background on Design and Market Orientation Because of its complexity, companies and researchers take different approaches towards design and its meaning. Design can be observed as the process of designing products or as the result of this process – the final, tangible or intangible product that has been designed. Depending on the context, design implies an objective, the intention of designing, particularly in the analytical and creative phases, as well as a process, a drawing, a sketch or a model in the execution phase, to give form to an idea. Recent years have seen a development in the use of design, from shaping and aesthetics to strategic design policies in business innovation processes, as well as in a number of societal development processes. Design, its methods and a design-oriented way of thinking have been emphasized by many researchers as resources for increasing a company’s innovation capability (Beverland & Farrell, 2007; Ulrich & Eppinger, 2000; Veryzer and Borja de Mozota, 2005). Also, most design management research results indicate that design improves the performance of innovation, whether or not it is technological (Borja de Mozota, 2003b; Von Stamm, 2008). Although the role of design within organizations can be difficult to define, it is clear that giving design a seat at the table adds significant value that helps differentiate and elevate companies beyond the norm and helps to deliver tangible business results (Rae, 2013, p. 37). The importance of design as a key discipline for bringing new ideas to the market has also been recognised in commitment 19 of the Innovation Union, an initiative in the Europe 2020 Growth Strategy, as a result of different studies undertaken in the UK, Denmark, Finland and other developed countries. This consensus has resulted in the European Commission’s Action Plan for Design-Driven Innovation (EC, 2013). According to Venkatesh et al. (2012), design orientation (DO) involves a strategic way of employing a company-wide vision that integrates design into the creation of customer value. It has also been identified as a factor integrating decisions at different levels of an organization and involving customers as a key element (Bloch, Brunel, & Arnold, 2003; Moll et al., 2007). Design orientation can also be described as a managerial strategic approach based on choosing design as a source of competitive advantage (Borja de Mozota, 2003a). Design-oriented companies are those that incorporate their design process into their business strategy (Moll et al., 2007). However, 52 NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 65 No. 3 / September 2019 design orientation and design implementation are also related to the environment in which a company operates, including social, political and economic circumstances; design tradition; education; and national design policy. From this perspective, it is clear that design should also be managed. Therefore, design management is directly concerned with the place of design within an organization, the identification of specific design disciplines that are relevant for key management issues, and the training of senior managers to use design effectively (Gorb, 1990). It can also be interpreted as the implementation of design within a corporation by communicating the relevance of design to long-term corporate goals and coordinating design resources at all levels of corporate activities to achieve the corporation’s objectives. This includes contributing to corporate strategic goals by developing a design policy alongside corporate identity and strategy, managing design resources and building a design network of information and ideas (Blaich & Blaich, 1993). Design management, according to Best (2006), is about managing design in every organization and can be implemented in three stages. Design strategy, as the first stage of design management, identifies opportunities and creates conditions in which design projects can be proposed. Managing the design process, as the second stage, focuses on developing design projects and agendas, thus making strategy visible through design. It develops a culture of collaboration, investigates the acquired skills and engages creative teams. Managing design implementation, as the third stage, is focused on delivery of design projects and outcomes in practice. It includes decision-making in the process of designing, as well as working relationships and responsibilities. According to Buchannan (2015, p. 16), there are clear benefits that come from investment in design in various countries. The problem is that some of these studies have focused more on the traditional areas of industrial design and related tactical practices rather than on the overall benefit of making design a central feature of management that ranges from goods and services to operations to vision and strategy – that is, the uses of design in “design-centric” organizations. Market orientation (MO) can be defined simply as the implementation of the marketing concept – that is, generating market information within the entire organization regarding the current and future needs of customers and clients (Kohli, Jaworski, & Kumar, 1990). The majority of studies from the 1990s suggest that MO is related to superior performance, sales growth and new product success (Atuahene-Gima, 1995; Desphande & Farley, 1998; Han, Yun, Kim, & Cho, 1998; Jaworski et al., 1993; Slater & Narver, 1994). MO can also be explained as the extent to which a firm engages in the generation, dissemination, and response to market intelligence pertaining to current and future customer needs, competitor strategies and actions, channel requirements and abilities, and the broader business environment (Morgan et al., 2009). MO and marketing capabilities are complementary to one another in ways that generate economic rents, and each may be viewed as an individual source of competitive advantage. The interaction between MO and marketing capabilities possesses the characteristic of ‘asset interconnectedness’ (Teece et al., 1997). For Grinstein (2008), market orientation is positively related to a number of strategic orientations. To be successfully implemented, all alternative orientations should be guided by the necessary underlying system of beliefs. Studies about the influence of design on some parts of marketing like customer satisfaction, product development, and innovation or business performance also exist, but there is a lack of research about the relationship and possible role of design in strategic marketing, as well as of the possibilities and potential of the common platform for closer collaboration. To be successful in the same way as marketing, design has to be integrated into all functional parts of an organization. Understanding design potentials and design implementation efficiency, when integrated at all levels of an organization, would allow marketers and managers to achieve better results. The new proposed conceptual model extends current thinking by integrating market and design orientation towards strategic competitive advantage. The Conceptual Model and Hypothesis Development After studying the existing literature, a new initial model of the relationship between design and market orientation has been proposed. The basis of the new design-market orientation conceptual model was the existing market orientation model in relation to new product (and service) success (Narver et al., 2004), combined with the managerial model of design (Moll et al., 2007), where market orientation and design orientation are put into a relationship. It is the result of an empirical qualitative study undertaken in three Spanish industries concerning design orientation, market orientation, and design management. However, the model does not show the precise correlation between different variables of design and market orientation. Design orientation describes a strategic managerial approach based on choosing to use design as a source of competitive advantage (Best, 2006; Borja de Mozota, 2003b, 2009; 53 Brown, 2008; Buchanan, 2015, Design Council, 2015, 2018; DMI, 2015; European Commission, 2013; Gorb, 1990; Kootstra, 2009; Moll et al., 2007; Rae, 2013; Rau, 2017; Venkatesh et al., 2012; Von Stamm, 2008), which means that both concepts are oriented towards a higher value in the eyes of their customers on one hand and both represent a higher value for the company in today’s competitive environment on the other hand. Based on this definition, we can conclude that design orientation has a positive relationship with market orientation. Therefore, we propose the main hypothesis: H1: Design orientation of a company is positively related to its market orientation. Moreover, in accordance with the above discussion, we further develop two sub-hypotheses: H1a: Customer orientation is positively related to all dimensions of design orientation. H1b: Strategic marketing is positively related to all dimensions of design orientation. Research Methodology The research was conducted combining qualitative and quantitative methods. The measurement instrument for empirical model verification was developed in several phases. After analyzing the literature, relevant items for the questionnaire were used from previous reliable research for two constructs: market orientation and design orientation (see Table 1). The first, qualitative stage of the research was focused on the design orientation of market-oriented companies. Two groups of respondents were interviewed (five managers and five designers) in a series of qualitative, face-to-face interviews, in order to design the questionnaire for quantitative research. The interviews lasted 45-60 minutes each. The sample of selected professionals was chosen, based on the assessment of the researcher, as typical representatives of the future respondents in the quantitative research. In the second stage, the quantitative research was conducted using an Internet survey of managers and CEOs from Croatian companies in different industries, with at least three employees in each company. The testing phase with nine experts from the fields of marketing and design preceded the execution of the quantitative research, in order to determine the quality of the questionnaire. The experts answered the questionnaire but were also given the opportunity to comment on the questionnaire’s clarity and length as well as any possible difficulties. Most of their comments were taken into account in preparing the final questionnaire, which consisted of 21 questions in six blocks: market orientation, design orientation, managerial approach, interfunctional coordination inside the company, business results and design environment. Most of the questions were answered on a five-point Likert scale. An additional nine questions about general data were Table 1. The basis for developing the questionnaire Market orientation Title Variables Lafferty B. A. and Hult G. T. M. (2001) A synthesis of contemporary market orientation perspectives Four variables of MO as basic approach: emphasis on clients, importance of information, inter-functional coordination and receptivity to change Narver J.C., Slater F.S. and Mac Lachlan D. L. (2004) Responsive and Proactive Market Orientation and New-Product Success Variables for proactive market orientation Marketing Department, Faculty of Economics and Business, University of Maribor with Marketing Institute (2008) Marketing in the 21st Century Variables of MO: marketing management, customer orientation. Design orientation Venkatesh A., Digerfeld-Mansson T., Brunel F. F. and Chen S. (2012) Design Orientation: a grounded theory analysis of design thinking and action Key questions as basic subthemes of design orientation. Centre for Design Innovation Ireland (2007) Design Difference – Research Methodology with Questionnaire. Design Innovation Research Variables of innovation by design, questions about design environment and design policy. Design Management Institute (2013) DMI Design Value Scorecard survey Variables/levels of design implementation: Tactical, organisational value, strategic value of design Borja de Mozota B. (1998/2003a) A model for design management excellence in European SMEs Variables of design – perception of design by managers Sanja Rocco, Aleksandra Selinšek: The Structure of Design Orientation and its Relationship with Market Orientation 54 NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 65 No. 3 / September 2019 included at the end, for a total of 30 questions altogether. The pretesting exploratory factor analysis (EFA) was conducted on the sample of N = 95 consisting of 75.8% small and medium-sized enterprises and 24.2% large-sized enterprises. The SPSS statistical program was used for the analysis of the data. All the scales were verified for construct validity in the pretesting EFA analysis, which indicates the extent to which the items on a scale measure the abstract or theoretical construct (Chandler, 1991). The EFA was conducted using IBM SPSS Amos 22 software. The results also confirmed a positive relationship between DO and MO. Finally, we applied the PLS SEM Partial Least Square / Structural Equation Modelling to present these relations between constructs in more detail, taking into account the factors of DO and MO. The PLS was conducted in Smart PLS 3 software. Final Results and Hypothesis Testing Sample A list with 2,184 e-mail addresses of CEOs, general managers or marketing managers was compiled based on data provided from several reliable sources: the Croatian Chamber of Commerce; the Croatian Ministry of Entrepreneurship and Crafts (MINPRO); the Croatian Agency for SMEs, Innovation and Investments (HAMAG-BICRO); and the list of Croatian companies with the GREEN MARK Sign of Excellence 2016. Managers received an email explaining the general purpose of the study and a link to the Internet survey. The survey was created in Lime Survey software at the www.engeres.com domain. The electronic questionnaire was designed so that the respondents could not see all the questions at once and therefore could not alter their answers in light of additional information. The survey was conducted from April to July 2017. A total of 397 undelivered e-mails were omitted from the list, and a follow-up email was sent to non-respondents in September. From the total number of sent emails, 233 clicks on the sent link were generated (click-through rate 13.04%). However, a significant number of respondents did not finish the questionnaire. A total number of usable questionnaires from 143 managers were received, yielding a 61 percent completion response rate. A total of 112 respondents were qualified for the research (i.e., CEOs or managers of companies with more than 3 employees), or 78% of the total number. The study sample consisted of 40% product companies, 33% service companies and 27% combined industry sectors. The final sample of 112 CEOs/managers came from companies of different sizes: 27 with 3-10 10 employees (24%), 38 with 11-50 employees (34%), 17 with 51-100 employees (15%), 7 with 101-200 employees (6%), and 23 with more than 201 employees (21%). According to the European Commission recommendation of 6 May 2003 concerning the definition of micro (<10 employees), small (11-50 employees) and medium-sized (51-250 employees) enterprises (OJ L 124, 2003, p. 36), the sample consisted of approximately 80 % micro, small and medium-sized enterprises and approximately 20% large-sized enterprises, which is an acceptable ratio for the Croatian economy. The general data show that the respondents were 42% female and 58% male. While 60.7% of managers were in various positions, ranging from executives to marketing and communcations, sales or design managers, many of the respondents were also owners or CEOs (39%), which is logical considering the large percentage of SMEs. With regard to age, most respondents were in the group between 40 and 49 years old (42.9%), followed by 30-39 and 50-59 (both 22.3%). Most of the respondents had a graduate degree (47.3%), followed by master degree (15.2%) and bachelor's degree (13.4%). Testing the Hypothesis To verify the main hypothesis (H1) regarding the relationship between market orientation and design orientation, we first used EFA on the final sample in order to identify the number of extracted factors of both constructs and to define the dimensions of each construct. After that, correlation analysis was conducted to determine whether intercorrelations exist between the factors of MO and DO. Five significant factors for all the questions of market orientation and design orientation were extracted with EFA analysis, which account for 63.5% of variance. The first two factors each explain about 20% of the variance (21.9% and 19.6%, respectively), while the other three factors each explain less than 10% of the variance. According to the extracted factors and variables that saturate the individual factors to the greatest extent, a total of five measuring dimensions were constructed: two market orientation factors (consumer orientation and strategic marketing) and three design orientation factors (the role of design, design as competitive market advantage and design level). After the construction of each factor, Cronbach’s alpha coefficients for each of them were calculated to see if the factors obtained were consistent (i.e., whether each of them measures one dimension of market or design orientation). All Cronbach’s alpha values are acceptable according to 55 Nunnally (1978), who offered a rule of thumb of 0.7. (More recently, scholars have cited 0.8 as a minimum alpha.) Regarding the internal consistency, Cronbach’s alpha coefficients results for each factor of both constructs show that all the variables of MO and DO initially used to calculate their factors remain in the analysis of the data. Table A1 in the Appendix shows MO and DO factors extracted on the final sample with Cronbach’s alpha coefficients. In the next step of the data analysis, we concentrate on the correlation between MO and DO in order to test the main hypothesis (Table 2). Moderate correlations in some pairs of factors are an additional indicator that exploratory factor analysis obtained relatively independent (but to some extent related) factors, which makes further analysis possible. Partial Least Square / Structural Equation Modelling (PLSSEM) analysis of the relationship between variables In the final stage of testing H1, H1a and H1b, we used PLS-SEM analysis. PLS-SEM offers a good approximation of common factor models in situations where factor-based SEM cannot deliver results due to its methodological limitations in terms of model complexity, sample size requirements, or inclusion of composite variables in the model (Reinartz et al., 2009; Sarstedt et al., 2016; Willaby et al., 2015, Sarstedt et al. in Homburg et al. (Eds.), 2017, p. 33). One of the most important advantages in using SEM is that it provides two kinds of weights: one measuring the impact of each indicator on the corresponding composite indicator and the other measuring relations among the composite indicators in the system (Trinchera et al., 2008). The PLS SEM model with factors of MO and DO is shown in Figure 1. The first step of analysis is the outer, measurement model. The construct of MO consists of two factors: strategic marketing (five indicators) and customer orientation (14 indicators). In strategic marketing, the indicator P2_3 (marketing communication activities planning) is the most influential (weight 0.764), the second is P2_5 (market research) and the third is P2_1 (long-term marketing plans). In customer orientation, the indicator P3_1 (Our commitment to serving customers is closely monitored) is the most influential, with a value of 0.903. The second most influential indicator is P4_9 (Our objectives and strategies are driven by increasing value for customers), while the indicators P4_1 (We systematically measure customer satisfaction) and P3_3 (We achieve rapid response to competitive actions) are the third most influential. The construct of DO consists of three factors: design as competitive advantage, the role of design in communication and management, and the level of design implementation. In the first of these factors, the indicator P9_2 (Design contributes significantly to benefits perceived by consumers) is the Table 2. Intercorrelations between factors of MO and DO Correlations (N = 112) Factor of strategic marketing (StraMarF) Pearson Correlation 1 .594 .336 .387 .526 Sig. (2-tailed) .000 .000 .000 .000 Factor of customer orientation (MarCustF) Pearson Correlation .594 1 .379 .469 .471 Sig. (2-tailed) .000 .000 .000 .000 Factor of design as competitive advantage (DesCompF) Pearson Correlation .336 .379 1 .622 .579 Sig. (2-tailed) .000 .000 .000 .000 Factor of the role of design (DesRoleF) Pearson Correlation .387 .469 .622 1 .581 Sig. (2-tailed) .000 .000 .000 .000 Factor of design levels (DesLevF) Pearson Correlation .526 .471 .579 .581 1 Sig. (2-tailed) .000 .000 .000 .000 MARKET ORIENTATION (MO) FACTORS StraMarF strategic marketing MarCustF customer orientation DESIGN ORIENTATION (DO) FACTORS DesCompF design as competitive advantage DesRoleF role of design (in Comm & Mngmnt) DesLevF level of design (implementation) Sanja Rocco, Aleksandra Selinšek: The Structure of Design Orientation and its Relationship with Market Orientation 56 NAŠE GOSPODARSTVO / OUR ECONOMY Vol. 65 No. 3 / September 2019 most influential of the three indicators (weight 0.785). The next most influential indicator is P9_1 (Design creates competitive advantage), and the third is indicator P9_4 (Design allows a company to sell at a higher price). The factor of the role of design in communication and management of the company has 13 indicators. The most influential is P9_16 (Design improves our long-term goals / return-on-investment) (weight 0.905). The second most influential indicator is P9_12 (Design improves our internal and external communication) (0.767), and the third most influential indicator is P9_10 (Design creates new niche markets) (0.764). Next is P9_6 (Design is a know-how that transforms the processes) (0.759). The factor of design level of implementation has three indicators. The most influential is P10_3 (We use design as a strategic resource for new business models (for strategic investments in customer experience design, long-term return on investment)) (0.834). The second step of analysis is the inner, structural model with path coefficients. These explain how strong the effect of one latent variable is on another latent variable. The weight of different path coefficients enables us to rank their relative statistical importance. The factor of strategic marketing has a strong influence on the factor of design levels (path coefficient weight 0.504). However, strategic marketing has a moderate effect on the factor of design as competitive advantage (0.184), and similar effect (0.179) is also found between strategic marketing and the role of design in a company’s communication and management. Figure 1. The PLS SEM model with factors of MO and DO 57 The factor of customer orientation has a strong effect on design’s role in the company (path coefficient 0.381) and has a relatively strong effect on the factor of design as competitive advantage (path coefficient 0.321). However, it has a moderate effect on the level of design implementation (0.194). The market orientation factors explain 22% of the variance of the design competitiveness factor, 27% of the role of design in management factor, and 43% of the variance of design as a level of implementation factor. The factor of strategic marketing in the company has a strong impact on the level of design implementation factor (0.504), while the factor of customer orientation has a strong relationship with the factor of the role of design in communication and management of the company. Observing the data, we come to the conclusion that looking at design’s role in communication and management, variable P9_16 (Design improves our long-term goals / return-on-investment) is the one with the strongest influence (0.905). Table 3 above shows values of path coefficients for market orientation, which are all statistically significant. The factor of customer orientation has the strongest impact on the role of design in the company (0.382), the impact on design as competitive advantage is not as strong (0.328) and the impact on design implementation has the lowest value (0.201). The factor of strategic marketing has the strongest influence on the factor of design implementation, while it does not have much influence on the other two factors of design orientation. As we can see in Table 4, the measurement of the variance inflation factor (VIF) shows that no collinearity measure exceeds the limit of 5.0, which makes the analysis acceptable (i.e., as mentioned before, there is no strong correlation between latent variables and factors). All the VIF values for measuring market and design orientation are acceptable (< 5.0), so there is no collinearity even when considering the variables in the model. The SRMR measure of fit of data in the equation model is 0.065, which is an acceptable value (the limit value is 0.1), and thus it can be considered that the model describes well the data and relationships between the variables and factors. At the end of the final stage, HTMT values were also calculated for the determination of discriminant validity in order to check whether constructs are sufficiently different to be acceptable as separate factors (Table 5). The values of the HTMT ratio should not exceed 0.9, which is also the case with this analysis. According to the results of the analysis, the hypothesis H1, regarding the positive relationship of market and design orientation, has been confirmed. However, there are different influences (i.e., the influence intensity of different factors of market orientation on factors of design orientation varies). Table 3. Path coefficient for market orientation Factor of design level Factor of design as competitive advantage Factor of the role of design Factor of customer orientation 0.201 0.328 0.382 Factor of strategic marketing 0.499 0.177 0.178 Table 4. Measures of coexistence - Variance inflation factor (VIF) Factor of design level Factor of design as competitive advantage Factor of the role of design Factor of customer orientation (MarCustF) 1.422 1.254 1.341 Factor of strategic marketing (StraMarF) 1.684 1.194 1.241 Table 5. Discriminant validity – HTMT Discriminant validity – HTMT Factor of design level Factor of customer orientation Factor of strategic marketing Factor of design as competitive advantage Factor of customer orientation (MarCustF) 0.536 Factor of strategic marketing (StraMarF) 0.641 0.670 Factor of design as competitive advantage (DesCompF) 0.729 0.440 0.413 Factor of the role of design (DesRolF) 0.664 0.499 0.440 0.732 Sanja Rocco, Aleksandra Selinšek: The Structure of Design Orientation and its Relationship with Market Orientation