Acontecimiento y tiempo

Figure 4.14 Research plan (c)

- Pre-pilot (LR) - Data Analysis (Pilot) - Data Analysis

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Figure 4.15 Contextualised framework for buying behaviour of SMEs in Turkey

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This is the stage for all results (Figure 4.14) and this framework summarises the results according to each product (Figure 4.15). The red zone is the most aversive/conservative, whereas the green zone indicates the most enjoyment. The orange and yellow zones reside between these extremes hierarchically. Therefore, the consolidated hypothesis is supported. Due to 30% greater aversive buying attitudes for intangible products in the red zone, a correlation exists between the tangibility of products and needs characteristics.

However, attributes do not always provide absolute explanations. As a matter of fact, correlation analysis shows that sector does not seem to be a factor. Neither staffing numbers, nor age is absolute attribute. Although the ‗30 to 39 mode‘ looks dominant in both the red and green zones, they don‘t represent a pattern. Therefore,

perceptions are more telling than those antecedents. Analyses of perceptions and their causes are part of the psychology area, which includes more cognitive studies. Questions such as ‗why are some needs perceived to be more interesting than others?‘ or ‗why do SMEs act like that?‘ are not topics of the study here. Therefore,

further research can be conducted to understand the reasoning behind this look. Inner (implicit) factors such as assumptions and values for all stages can be examined and results related to the current picture can be concluded.

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In terms of generalizability, this contextualised framework showed that the lack of attributes made this outcome more powerful than is expected. With this current look, it is possible to state that SMEs do also buy in non-normative zones, when they do they spend more, and when they spend more they do this for tangible products and even in economic crisis, they compromise less for tangible products.

In order to assess its impacts on stakeholders, both of them need to be discussed. Naming the stakeholders, numerical impacts of the different buying behaviour typologies and prioritization of impacts will be calculated through probability terms. However, before going there, a validation would increase the confidence on the questionnaire and results, in other words, the contextualised framework here.

Although even realizing this carries this context from the unknown axis to known and underlines the justification of the study, because of the lack of attributes, ‗which SME is which‘ is quite unanswered. In other words, in terms of reaching out one typology, ‗how to make a query‘ is still open. Knowing that this part is still

unknown, for stakeholders who want to contact different typologies, pull communication techniques (internet, web based announcement, mass media) will technically be more eligible to use rather than push communication techniques, because they cannot sort out the data from a source catalogue, or a government body‘s database, using the traditional metrics, like age, industry, size, title etc.

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From an application viewpoint, this study is unique. Its greatest contribution is that it urges researchers to consider the possibility that SMEs are subjects of individual buying behaviour models, rather than traditional organisational/corporate buying behaviour models. It also suggests various buying attitudes for different products. Communication/IT devices and vehicles lead in all zones, showing that participants do not compromise for those products as they do for others. They also do not seek rationality, because they choose communication devices least aversively in the red zone.

4.5 Chapter Summary

Since there are no studies of 'SME Buying Behaviour' previously completed, generalization was an important criterion for setting the sample size and its dimensions. In an ideal world, it would be preferred to sample the data with all aspects, including all sectors and segments possible. However, budget limitations required the creation a more narrow but valid sample which is enough to generalise the results. General trade, manufacturing and construction were the first three sectors that dominated the audience in terms of employee size and number of companies. The same budget limitations did not allow conducting the survey in Istanbul. According to government data, it was justified the use of another city, Eskisehir, with its industrial property developments, yearly average employment, electric consumption and most importantly economic value metrics. In this chapter, the consolidated hypothesis was tested and it was found that the following were

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supported: SMEs also buy within the leisure-routine axes and when they do, they spend more and faster as do individual consumers. Besides, even in an economic crisis environment, there were products that SMEs compromise less on and they are not necessarily perceived as highly tangible -professional- needs. The chapter ended with a contextualised framework which concludes SME buying behaviour in Turkey with its attributes. The next chapter will validate these results, while focusing on the possible impact on stakeholders, as well as suggesting possible strategies.

CHAPTER 5: VALIDATION AND FINAL FRAMEWORK FOR BUYING BEHAVIOUR