Understanding customers across national cultures: the influence of national cultural differences on designers’ empathic accuracy

Figures & data

Figure 1. The whole process and time span of the experiment.

Figure 2. Customer interview in the Vehicle Laboratory.

Table 1. Example of customer’s entry form.

TIME	THOUGHT OR FEELING	+, 0, -
07:15	I was: thinking this column is blocking my view so often.	+
		0
		$◯-$
08:03	I was: thinking you might ask that.	$◯+$
		0
		-
08:41	I was: feeling luckily the rain is not usually that heavy.	+
		$◯0$
		-

Table 2. An example of similarity rating

CUSTOMER’S ENTRY	DESIGNER’S INFERENCES	SIMILARITY SCORE
‘I feel like I am repeating my answer again.'	He was: thinking how there really is a time when you do not see the road and cannot control it.	0
‘I think I’ve seen this electronic component before.'	He was: feeling curious about something he sees in the car, otherwise felt ok being done with interview	1
‘Good point. Finding parking spots is always a problem for me'	He was: thinking how finding parking is also a problem and how this device could help.	2

Table 3. Examples of design-related ratings of users’ entries.

Customer’s entry	Relevance score	Rationale
‘This is an easy question.'	1	Not related to design brief, but instead focused on the interview situation or language.
‘Thinking good moments when driving with friends.'	2	Related to user’s life and broader context, but no direct connection to design brief.
‘I keep thinking is there any other information I need. I think I will use the GPS, and following its instructions. In China, the GPS is usually correct.'	3	Loose connection to design brief. Something that a designer might want to ask more about.
‘I am interested to hear what technology is used to make it see other cars.'	4	Clearly but indirectly related to the design brief, product, or accessory. Potentially specifying a need.
‘I do not think I really need a separate device to tell me this information because I drive often. I believe I can drive safely based on my driving experience'	5	Direct mention of product or accessory specified in the design brief.

Table 4. Summary of Hierarchical Regression Analysis for Variables predicting Empathic Accuracy.

Variable	b	β	t	R	R^2	ΔR^2
Step 1				.453	.206	.206
National Cultural Differences	−8.949	-.453	−2.492*
Step 2				.616	.380	.174
National Cultural Differences	−5.818	-.295	−1.678
Visiting Experience	−10.643	-.447	−2.543**

Note. N = 26; *p < .05, **p < .01, ***p < .001

Figure 3. A boxplot of designers’ empathic accuracy of understanding Finnish and Chinese users.

Figure 4. A bar chart of designers’ emotional tone accuracy of understanding different users.

Table 5. Summary of Hierarchical Regression Analysis for Variables predicting Emotional Tone Accuracy.

Variable	b	β	t	R	R^2	ΔR^2
Step 1				.044	.002	.002
National Cultural Differences	.767	.044	.217
Step 2				.046	.002	.000
National Cultural Differences	.681	.039	.176
Visiting Experience	.295	.014	.063

Note. N = 26; *p < .05, **p < .01, ***p < .001

Figure 5. A hierarchical linear model of predicting variances of empathic accuracy and emotional tone under independent variables of national cultural differences and visiting experience.

Figure 6. Comparison of designers’ empathic accuracy in two cultural groups.

Figure 7. Comparison of designers’ empathic accuracy under different visiting experiences.

Figure 8. Comparison of designers’ empathic accuracy under the independent variable of whether the customer’s entry is design-related.

Table 6. Comparison of designers’ empathic accuracy of inferring design-related and non-design-related entries.

Customer’s entries	N	M	SD	Sig. (2-tailed)
Design-related	143	35.48	29.19	.000
Non-design-related	507	24.10	26.76

Figure 9. A boxplot of designers’ design-related and non-design-related empathic accuracy.

Figure 10. A hierarchical linear model of predicting variances of design-related and non-design-related empathic accuracy under independent variables of national cultural differences and visiting experience.

Table 7. Summary of Hierarchical Regression Analysis for Variables predicting Design-related Empathic Accuracy.

Variable	b	β	t	R	R^2	ΔR^2
Step 1				.411	.169	.169
National Cultural Differences	−16.258	-.411	−2.206*
Step 2				.591	.350	.181
National Cultural Differences	−9.861	-.249	−1.385
Visiting Experience	−21.750	-.455	−2.530**

Note. N = 26; *p < .05, **p < .01, ***p < .001

Table 8. Summary of Hierarchical Regression Analysis for Variables predicting Non-design-related Empathic Accuracy.

Variable	b	β	t	R	R^2	ΔR^2
Step 1				.442	.195	.195
National Cultural Differences	−8.287	-.442	−2.413*
Step 2				.560	.313	.118
National Cultural Differences	−5.839	-.311	−1.684
Visiting Experience	−8.321	-.368	−1.989*

Note. N = 26; *p < .05, **p < .01, ***p < .001

Figure 11. Comparison of designers’ design-related and non-design-related empathic accuracy under the influence of national cultural differences.

Figure 12. Comparison of designers’ design-related and non-design-related empathic accuracy under the influence of visiting experience.

Table 9. Examples of opinions from designers and customers under the same topic