Consumer buying behaviour and the segmentation of consumer markets are widely researched. Amongst others, approaches can be found with regard to the consumers’ lifestyles (e.g. Burns & Harrison, 1979; Douglas & Urban, 1977; Villani & Lehmann, 1975) and consumer decision-making characteristics (e.g. Darden & Reynolds, 1971; Sproles & Kendall, 1986; Stephenson & Willet, 1969; Westbrook & Black, 1985). To the best of our knowledge, such approaches do not exist for B2B markets (business-to-business markets). Segmentation approaches and, therewith, the research of buying behaviour within the B2B sector are primarily focused on “hard facts”, such as geographic, “demographic”, situational, organisational and buying centre related characteristics of companies (e.g. Abratt, 1993; Shapiro & Bonoma, 1984; Weinstein, 2004).

It, however, appears plausible that companies and their buying centres, like consumers, show typical decision-making processes with regard to their procurement processes. Furthermore, it also makes sense to assume that understanding companies and buying centres in their decision-making can contribute more to understanding and predicting their behaviour than just focussing on the afore-mentioned “hard facts”, which can be seen as rather “superficial” with regard to making procurement decisions. Thus, we argue that the approach of consumer decision-making types and, therewith, the respective measurement instruments can be transferred from consumer markets to B2B markets, if adjusted accordingly.

Against this backdrop, we defined seven B2B decision-making styles, which are characterised as follows:

• The perfectionistic and quality conscious buyer represents an organisation that constantly and deliberately searches for the best quality products, spending a considerable amount of its time and effort in due diligence and information gathering, to make educated decisions. Since these companies seek to purchase the most perfect choices, their expectations on product excellence and superiority are very high. This makes product quality the most outstanding purchase criterion used in their decision-making. This pursuit of perfectionism goes hand in hand with the company’s competitive strategies, which will only be satisfied by products that are differentiable from the rest through high quality. In this sense, only exceptional products will catch this firm’s attention, leaving fairly good offers of a lower quality out of the company ́s choice spectrum.
• The confused and poorly informed buyer represents a company that is overwhelmed by the amount of information it receives from different suppliers and products, making the decision-making process difficult, slow, with a lot of hesitation, uncertainty and insecure decisions. This excess of information confuses the firm and produces doubt on to what extent each offer can satisfy the demands of the company. Additionally, this type of buyer has normally poor to none information sources, and therefore tends to rely on advertising stimuli to make decisions.
• The fast and careless buyer, unlike the perfectionistic and quality conscious buyer, does not plan the procurement process, nor invests time and effort in the buying decision. Such a company settles for the first supplier or product that appears to be sufficient. Since expectations on product performance and attributes are not very high, it makes quick and impulsive purchases. Occasionally, these thoughtless decisions present economic consequences that the firm regrets.
• The novelty and innovation seeking buyer represents a company that is very much into innovative and ground-breaking products, which play with the limits of the established technology. For this reason, its choice spectrum will only include novelty products. Such a company will direct a significant amount of its resources to purchase products within the latest trends because it is important to such a firm to maintain an up-to-date status of its inventories and portfolios.
• The habitual and loyal buyer represents a company whose buying behaviour is marked by its preference and loyalty toward its already existing suppliers. For each purchase situation, the company recurrently chooses its known and favourite suppliers because these satisfy the demands of the company fairly well. Since the company has experience with these suppliers, it has certainty that the business relationship will work, and that the products bought will meet the expectations.
• The price conscious buyer represents a company that usually tries to procure the best choice for the lowest possible price. In other words, it is interested in achieving the best value for money. Such a firm usually seeks for low prices, but does not neglect that the product still needs to provide some utility. The company dedicates resources into budgeting activities that will help to carefully plan and monitor its expenses.
• The brand and reputation conscious buyer represents a company that uses the reputation and popularity of a supplier’s brand as the main purchase criterion. Such a company considers only well-known brands in its choice spectrum and, therefore, does not spend much time or research efforts on analysing the real quality or value behind the offer. Furthermore, since the focus of such a company is set on reputation and the brand, the price is of lower relevance in the final purchase decision.

Based on the afore-described characterisation of the B2B decision-making styles, it can be assumed that these decision-making styles can predict companies’ expectations on service quality, price level, price value and price transparency of their suppliers.

It is assumed that the expectation on service quality is positively affected by the following B2B decision-making style: perfectionistic and quality conscious buyer. A negative effect is expected for the following B2B decision-making styles: confused and poorly informed buyer, and fast and careless buyer. No effect on the expectations on service quality is expected for the following B2B decision-making styles: novelty and innovation seeking buyer, habitual and loyal buyer, price conscious buyer, and brand and reputation conscious buyer.

It is assumed that the expectation on the price level is positively affected by the following B2B decision-making style: confused and poorly informed buyer, fast and careless buyer, habitual and loyal buyer, and price conscious buyer. For the following B2B decision-making styles no effect on the expectation on the price level is assumed: perfectionistic and quality conscious buyer, novelty and innovation seeking buyer, and brand and reputation conscious buyer.

Positive effects on the expectation on price value are hypothesised for the following B2B decision-making styles: perfectionistic and quality conscious buyer, habitual and loyal buyer, and price conscious buyer. Negative effects on the expectation on price level can be assumed for the following B2B decision-making style: confused and poorly informed buyer. The following B2B decision-making styles should have no effect on expectation on price level: fast and careless buyer, novelty and innovation seeking buyer, and brand and reputation buyer.

With regard to the expectation on price transparency, positive effects can be assumed for the following B2B decision-making styles: perfectionistic and quality conscious buyer, habitual and brand loyal buyer, and price and conscious buyer. Negative effects on the expectation on price transparency can be hypothesised for the following B2B decision-making style: confused and poorly informed buyer. The following B2B decision-making styles should have no effect on the expectation on price transparency: fast and careless buyer, novelty and innovation seeking buyer, and brand and reputation conscious buyer.

Item generation and selection

As described in the theory section, it appears plausible that consumers decision-making styles can be transferred to the decision-making of companies. Against this backdrop, we based the development of the B2B Decision-making Styles Scale on the Consumer Styles Inventory, developed by Sproles and Kendall (1986). The Consumer Styles Inventory consists of 40 items over eight dimensions. We focused only on seven dimensions because the five items of the “recreational, hedonistic consumer” cannot be applied to the B2B context, as buying centres and procurement managers do not purchase goods and services for their own (emotional) benefits but for the (rational) purpose of their employer. We reformulated the remaining 35 items of the afore-mentioned measurement instrument so that they can be applied in a B2B setting by not referring to the individual consumer but to the respective employer of the respondent. For instance, our first item “Procuring very good quality is very important for my company.” derives from Sproles and Kandall’s (1986) original item “Getting very good quality is very important to me.”

To empirically refine the measurement instrument, we applied a principal component analysis with varimax rotation and determined Cronbach’s alpha for the resulting components, using the R packages psych (Revelle, 2022) and psy (Falissard, 2022). We could extract 8 components with an eigenvalue larger than 1 (cf. Table 2).

Table 2

Principal Component Analysis of the initially analysed 35 Items – Eigenvalues (N = 314)

Table 3 shows the loadings, communalities and Cronbach’s alpha for the items and components. Following Comrey and Lee (1992), loadings (substantially) lower than .55 can be regarded as rather poor. Subsequently, we eliminated six items.

The item “My company usually chooses the more expensive supplier brands.” had to be inverted due to the inverse loadings of the other items of the respective component. Then, when recalculating the loadings without the six eliminated items, mentioned above, the loading of the inverted item dropped substantially to .35 so that this item, too, was eliminated.

Furthermore, component eight with two items was eliminated because of a poor Cronbach’s alpha of .40, following Hair, Page and Brunsveld (2019) who consider a minimum threshold for Cronbach’s alpha at .60. The elimination of this component is also supported by the content of the two respective items, which appear to be inconsistent and might be even considered contradictory (“To get variety, my company buys from different suppliers and chooses different brands.” and “My company purchases as much as possible at discount prices.”).

Table 3

Principal Component Analysis of the Initially Analysed 35 Items – Loadings, Communalities (h2) and Cronbach’s Alpha (N = 314)

After the just described refinement of the B2B Decision-making Styles Scale through principal component analysis, we confirmed the allocation of the items to their respective components by determining their loadings (see Section Item analyses) and tested the adequacy of our measurement instrument by determining Cronbach’s alpha, Dillon-Goldstein’s rho and the average variance extracted (see Section Reliability), using the R package plspm (Sanchez, 2013).

Samples

The B2B Decision-making Styles Scale was applied in an online survey between 30 October 2020 and 7 March 2021. Ad-hoc sampling was used to recruit the participants through online procurement forums, email and social media, mainly LinkedIn. In total, 473 people responded to the questionnaire, with, eventually, 314 fully answered questionnaire resulting. These fully answered questionnaires were used for the analysis. At the start of the questionnaire the company demographics were measured. Sociodemographic variables of the respondents were not collected, as not the individual decision-making styles but the companies’ decision-making styles in procurement processes were evaluated. The headquarters of the participants’ companies are based in Africa (1.91%), Asia (14.33%), Australia and Oceania (.96%), Europe (40.13%), Latin America (23.89%), Middle East (4.78%), and North America (14.01%). 53.19% of the participating companies have an international scope, 22.29% a national scope, 8.92% a regional scope and 15.61% a local scope. The size of the participating companies varied from small to large firms, with 15.61% having 1 to 9, 4.46% 10 to 19, 9.87% 20 to 49, 14.33% 50 to 249 and 55.73% 250 or more employees.

Item analyses

We used R (R Development Core Team, 2017) and the R package plspm (Sanchez, 2013) to determine the loadings of the items on their constructs. The results are presented in Table 4. The majority of the loadings is higher than .70; and no item loads below .60 on its construct. Against this backdrop, the loadings and, therewith, the structure of our measurement instrument can be considered satisfactory.

Table 4

Loadings of the Items on Their Respective Constructs (N = 314)

Item parameters

Table 5 shows the descriptive statistics for each item as well as their weight and the corrected item scale correlation for their respective construct.

Table 5

Arithmetic Mean (M), Standard Deviation (SD), Kurtosis (K) and Skewness (S) of the Items, and Weight (W) and Corrected Item Scale Correlation (r) of the Items for Their Respective Constructs (N = 314)

The corssloadings of the Items on the constructs are represented in Table 6.

Table 6

Crossloadings of the Items (N = 314)

5 Quality criteria

Objectivity

The B2B Decision-making Styles Scale is designed as an online or written questionnaire; however, it can be adjusted to personal or phone interviews with relative ease. When the measurement instrument is applied in its online or written version, a high degree of objectivity is indicated as the researcher cannot personally influence the participants during the collection of data.

When we collected the data for the development of the B2B Decision-making Styles Scale, we only provided our participants with a link to an online questionnaire and did not directly interfere when they answered this online questionnaire. This reduction of our personal involvement in the data collection process was meant to secure a high degree of objectivity.

To secure the objectivity of the B2B Decision-making Styles Scale, the following aspects are advised:

1. When applying the scale in a questionnaire, the instructions, the presented order of the items (or a randomisation of the items) and the labelling of the scale poles (“completely disagree” and “completely agree”), presented in the Section 2 Instrument, should be followed.
2. When analysing the data, scoring of the subscales should be realised by calculating the arithmetic mean of all of the items of one subscale, i.e. B2B decision-making style, for each participant (cf. Section 2 Instrument).
3. When interpreting the results, the results of our study, i.e. the arithmetic means of the B2B decision-making styles, should serve as general benchmarks (cf. Section Descriptive statistics), as we have covered a broad range of companies from multiple international regions (cf. Section Samples). However, it should be noted that it might be fruitful to develop refined benchmarks in particular industries through future research.

Reliability

We determined Cronbach’s alpha, Dillon-Goldstein’s rho and the average variance extracted (AVE) to test the adequacy of our measurement instrument (Table 7). The respective values can be considered satisfactory with the lowest values for Cronbach’s alpha of .57, Dillon-Goldstein’s rho of .81 and AVE of .52.

Table 7

Adequacy of the Measurement Instrument - Cronbach’s Alpha, Dillon-Goldstein’s Rho and Average Variance Extracted (AVE) (N = 314)

Validity

Indications for content validity can be drawn from a comparison of the B2B decision-making styles, described in the theory section, and the items allocated to these subconstructs, as described in the Section Item analysis. We regard it a fair assumption that the items reflect their respective B2B decision-making style well, which should be exemplified by the perfectionistic and quality conscious buyer.

The following items reflect the perfectionistic and quality conscious buyer:

1. Procuring very good quality is very important for my company.
2. When purchasing products or services, my company attempts to get the very best or perfect choice.
3. My company normally attempts to buy the best overall quality.
4. My company puts special efforts into choosing the very best quality products or services.
5. My company´s standards and expectations for product or service purchases are very high.
6. My company takes the time to carefully purchase the best option.

These items are reflected in the characterisation of the perfectionistic and quality conscious buyer (also cf. theory section):

• The perfectionistic and quality conscious buyer represents an organisation that constantly and deliberately searches for the best quality products, spending a considerable amount of its time and effort in due diligence and information gathering, to make educated decisions. Since these companies seek to purchase the most perfect choices, their expectations on product excellence and superiority are very high. This makes product quality the most outstanding purchase criterion used in their decision-making. This pursuit of perfectionism goes hand in hand with the company’s competitive strategies, which will only be satisfied by products that are differentiable from the rest through high quality. In this sense, only exceptional products will catch this firm’s attention, leaving fairly good offers of a lower quality out of the company ́s choice spectrum.

It should be noted that the number of our factors, i.e. B2B decision-making styles, deviates form the number of factors Sproles and Kendall (1986) developed as consumer decision-making styles. Furthermore, our allocation of items to these factors does not entirely match the one of Sproles and Kendall (1986). Subsequently, our characterisation of B2B decision-making styles is not entirely identical to the description of consumer decision-making styles by Sproles and Kendall (1986). An explanation for this can be found in the fundamental differences that underly the behaviour and objectives of consumers and businesses. According to the theory of economics, consumers strive after maximising their utilities, whilst companies strive after maximising their profits (e.g. Mankiw & Taylor, 2017). The consumers’ utilities can be linked to emotions and the businesses’ orientation on profits can be linked to rather rational decision-making. This difference between consumer and business decision making is also reflected in our factors, i.e. B2B decision-making styles. For instance, we could not replicate the recreational, hedonistic shopper or the impulsive shopper, Sproles and Kendall (1986) found (cf. Section Item generation and selection). This deviation from the Consumer Styles Inventory is plausible, as the two mentioned consumer styles are strongly associated with emotions, which do not fit into the predominantly rational “logic” of businesses.

To test the criterion validity of our measurement instrument, we examined the effects the B2B decision-making styles have on the expectations on service quality, price level, price value and price transparency, which are hypothesised in the theory section. The operationalisation of the expectations on service quality was based on the SERVQUAL approach by Parasuraman et al. (1988). To measure the expectations on price level, price value and price transparency, we adopted the price image scale, developed by Zielke (2006), to the B2B environment.

Figure 1 represents the results of our plspm analysis regarding the effects of the B2B decision-making styles on service quality. The results match all of the hypothesised effects, described in the theory section, with the exception of the effect of a brand and reputation conscious buyer on service quality.

Figure 1: Effects of the B2B decision-making styles on the relevance of service quality with path coefficients, significance level (*p < .05; **p < .01; ***p < .001) and R² (N = 314)

Figure 2 represents the results of our plspm analysis regarding the effects of the B2B decision-making styles on price level. The results match all of the hypothesised effects, described in the theory section, with the exception of the effect of a novelty and innovation seeking buyer on price level.

Figure 2: Effects of the B2B decision-making styles on the relevance of the price level with path coefficients, significance level (*p < .05; **p < .01; ***p < .001) and R² (N = 314)

Figure 3 represents the results of our plspm analysis regarding the effects of the B2B decision-making styles on price value. The results match all of the hypothesised effects, described in the theory section, with the exception of the effect of a brand and reputation conscious buyer on price value.

Figure 3: Effects of the B2B decision-making styles on the relevance of the price value with path coefficients, significance level (*p < .05; **p < .01; ***p < .001) and R² (N = 314)

Figure 4 represents the results of our plspm analysis regarding the effects of the B2B decision-making styles on price transparency. The results match all of the hypothesised effects, described in the theory section.

Figure 4: Effects of the B2B decision-making styles on the relevance of the price transparency with path coefficients, significance level (*p < .05; **p < .01; ***p < .001) and R² (N = 314)

In summary, 25 of the 28 hypothesised effects could be confirmed, indicating a satisfactory criterion validity of the B2B Decision-making Styles Scale.

Descriptive statistics (norming)

The descriptive statistics of the examined constructs are represented in Table 8.

Table 8

Descriptive statistics of the constructs on a scale from 1 to 6 (N = 314)

The correlation matrix of the subscales is represented in Table 9.

Table 9

Correlation Matrix of the Subscales (*p < .05; **p < .01; ***p < .001) (N = 314)

Prof. Dr. Hendrik Godbersen, FOM University of Applied Sciences, Study Centre Stuttgart, Rotebühlstr. 121, 70178 Stuttgart, Germany, hendrik.godbersen@fom.de