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Cultural Differences in Conceptual Models of Ride Comfort

for High-Speed Trains

Insoo Chung (KORAIL, Daejeon, Korea);

Myunghwan Yun(Department of industrial Eng in Seoul National University, Seoul, Korea)

Abstract

This study focuses on an analysis of the difference in cultural experiences for similar services,

analyzing the difference in conceptual models of ride comfort for passengers between KTX

(Korea Train eXpress) and TGV (Train a Grand Vitesse), which are operating with identical

platforms. For developing conceptual models of ride comfort, this study surveyed 200 KTX

passengers in Seoul:

Busan line, and surveyed 150 France TGV passengers in Paris: Marseilles line. In the results of

the study, though there were differences in body size and culture, the models of ride comfort for

both countries shared critical factors. However, there were significant differences in loading

values of ride comfort for these critical factors. In particular, there were differences of 1.5-2

times between the two models regarding the sub-factors seat factor and human fatigue

factor. In conclusion, this study elicits that experience factor is the most influential on ride

comfort, and cultural factors are applied as essential variables in ride comfort improvement.

1. Introduction

This study focuses on analyzing cultural differences that affect the loading values of critical

factors among local passengers of high-speed trains (Korea Train eXpress: KTX and Train a

Grande Vitesse: TGV, which share a platform) by comparing concept models of ride comfort.

KTX and TGV as high-speed trains have the same mechanical properties and design

engineering variables, and provide a similar compartment environment for passengers. However,

in KTX, complaints about ride comfort have increased because of the large number of tunnels,

noises, and backward-directional seats (KRRI, 2003). Objectively, KTX provides a better ride

quality than TGV based on compartment environment alone, but a general and institutional

analysis of the differences in passenger satisfaction and models of ride comfort for each country

is needed in order to analyze the cognitive differences of ride comfort (Linda et al., 2004). In this

study, we intended to understand the effect of local cultural characteristics on ride comfort,

comparing ride comfort of KTX with that of TGV. A boarding experiment involving local

passengers was conducted with an affective evaluation questionnaire of ride comfort, co-

developed by Seoul National University in Korea and AIX-Marseille University in France. As a

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result, based on the collected data, the loading value in critical factors of the conceptual model

for ride comfort was analyzed by the verified structural equation model (Kim et al., 2006).

2. Related research

Due to the globalization of services, services focusing on multinational markets should reflect on

the market properties of each sales country to meet the needs in foreign markets as well as in

the domestic market. Also, it should not be assumed that the reported service properties in the

service markets of other countries are contemporary, and service properties that can be elicited

through experimental evaluation for each country should be analyzed (Thomas, 1986). In the

case of high-speed trains, the introduction of a new high-speed train is considered only in its

mechanical aspect, despite the importance of cultural aspects like ride comfort. The main

reason for this is the difficulty in exactly defining and measuring the concept of culture. There

have been studies concerning the ride comfort of general vehicles that consider cultural aspects

(Allaman and Tardiff, 1982; Andersson et al., 1995). However, attention to locality has only been

shown in visual and physical aspects under the assumption that there is no difference in need

and demand in every country (Ashleigh and Daniel, 2004). In order to address these limits, this

study has prepared a boarding experiment that carries out a pre-examination of the cultural

variables of ergonomics and ride comfort related to trains (high-speed trains).

2.1 Cultural variables in ergonomics studies

Cultural differences will occur according to cultural preferences formed essentially by cultural

practices, which make a distinction among nations (Hofstede, 1996). The differences in cultural

preferences must be considered when making decisions regarding boarding, taking into account

the image of high-speed trains and subjects satisfaction (Penaloza and Gilly, 1999; Birgelen et

al., 2001). Especially in the case of trains, ride comfort is determined directly by affective state

and perceived performance, and it has been revealed that cultural effect is deeply involved with

affective state (Kuhlthau et al., 1980). In the study of Spreng and Page (2001), it was claimed

that there is a possibility of indicating different ride comfort levels according to the difference in

perceived performance and affective state, influenced by cultural differences. Hofstede (1996)

defined culture and members of a group as a collective mental programming in a particular

environment making it distinct from members of another group, and explains that cultural

meaning can be divided into three human mental models: individual, collective, and general

level. Also, many researchers have attempted to understand human behavior in a cultural

dimension (Ford et al., 2003; Nakata and Sivakumar, 1996; Marc, 1991). In the ergonomics field,

a comparative study was conducted on globalizing services and products like mobile interface,

car interior design, and web user interface (Choong and Salvendy, 1998; Hoft, 1996; Khaslavsky,

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1998; Singh et al., 2003). Cultural dimensions in cross-cultural studies can provide variables

that are effective in analyzing users activity. This study selected cultural variables involved in

ride comfort, and made the distinction of analyzing cultural dimensions suggested byHofstede(1996) and Ford (2003) for creating the questionnaire. it is recognized that a model for

cultural dimension has the largest meaning even in the study of customer behavior (Viren and

Martin, 2005; Hendon et al., 1999; Deci et al., 2001). Table 1 shows the content of arrangement

and analysis of their cultural dimensions, and is used for the questionnaire development in this

research.

Table 1: Cultural variables in ergonomics studies (amended model)

Cultural variables inergonomics

Specification

Uncertaintyavoidance (Hofstede,1996)

People of a culture who have a strong tendency of uncertaintyavoidance would hesitate to face uncertain situations and avoiduncertain situations through danger avoidance. On the other hand,people of a culture who have a weak tendency of that would acceptmore uncertainty and danger.

Individualism andcollectivism (Ford etal., 2003)

Individualism is the tendency to think that the profits of an individualcannot be sacrificed by the profits of a group, and collectivism is thetendency to believe that the profits of the individual can be sacrificedfor the profits of the group.

Context (Hofstede,1996)

It classified the orient cultures, including Korea, China and Japan,as high context, the European culture as low context, and it claimedthat communication in high context cultures has implicate, internaland indirect characteristics. It suggested the result that through

subject tests of the developers of China having high context and ofU.S.A having low context, American subjects in the modes ofcompounding letter and number, and Chinese subjects in the modesof icon-basis, indicated better results in performing tasks (Choongand Salvendy, 1998).

Time perception(Ford et al., 2003)

It classified time perception in a culture as pluralism and unit. In apluralism culture defined as concurrent, the culture deals withvarious works at the same time and shows a non-intentionaltendency. On the other hand, a unit culture defined as sequentialor linear does one task at one time, and acts intentionally and inorder.

Kerstin (2004) analyzed that there is cultural information within two categories of cultural

mentalities and cultural environments for developing services centered on cultural aspects. Thecultural mentalities that are especially important for service issues are shown in Figure 1. It is

determined by the cultural environments, which, in turn, determine the services.

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Figure 1: An approach to culture-specific machine design (Kerstin, 2004)

Helen (2004) showed that the cultural lens model provides a framework for understanding the

concept and origins of national culture. Figure 2 shows the cultural lens model. The model

assumes that members of a national group, having grown up in similar ecological and social

contexts, have shared experiences. The dimensions provide a lens through which each member

of a national group sees the world. The lens filters, organizes incoming information, focuses

sense making, structures planning and adaptation activities, and frames interactions and

communication.

Figure 2: The Cultural Lens Model (Helen, 2004)

2.2 Ride comfort studies in railroads (or high-speed trains)

Railroad companies and organizations such as the UIC former ORE (Office for Research and

Experiments of the International Union of Railways UIC), and now the ERRI (European Rail

Research Institute) have carried out ride comfort research. The CEN (European Committee for

Standardization) published a draft standard based on the research of the ORE/ERRI and there

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have been some publications from the members of the committee. Although the ISO is

responsible for ride comfort evaluation for not only railroad vehicles, but also for all kinds of

motion environments, a number of specific ISO standards for railroad applications have recentlybeen published. In particular ride comfort disturbances on high-speed trains (Andersson and

Nilstam, 1984). Japan has done extensive work on comfort and nausea for both very high-

speed trains and tilting trains (Koyanagi, 1985; Suzuki, 1996). Concerning motion sickness,

research to reach a fair understanding of the problem is still needed (Ohno, 1996). In Europe

where high-speed trains are advanced, the study for ride comfort of high-speed trains, which

were introduced to the EU focusing on England, Sweden, France, Germany, etc. is ongoing

(Cleon, 1986; Flink and Hulten, 1993; Forstberg, 1996; Persson, 1989; Whitelegg et al., 1993).

Korea was the first in the world to use the structural equation model for ride comfort of high-

speed trains (Yun et al., 2005). Table 2 shows the different comfort standards applicable for

different conditions on railroad environments.

Table 2: Some international standards for evaluation of ride comfort (CEN, ISO)

Types Non-tilting trains Tilting trainsHigh-speed

trains

Average comfortNMV, NVA, ISO 2631, Rideindex

Same as non-tiltingtrains

N/A

Comfortdisturbances

PDE (Discrete events)Same as non-tiltingtrains

N/A

Motion sickness MSDVZSame as non-tiltingtrains

N/A

It has been found in the results of related studies that a wide range of non-visual aspects of

culture should be considered. However, because theories that can measure or explain cultural

effects related to the localization of high-speed train service are not sufficient, it has been

concluded that verified models supporting these are needed at this time.

3. Method

3.1 Experiment

This study analyzed the factors affecting ride comfort of KTX and TGV passengers, and

processed in the manner demonstrated in Figure 3 for comparing its main effect, respectively.

Figure 3: The process of this study

Development of questionnaire

In paragraph 2.1, using classified cultural dimensions, questionnaires that were suitable to the

environment of high-speed train passengers were developed. In order to confirm whether each

questions were suitable to the ride comfort of high-speed train passengers, and to reduce

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language mistranslation between France and Korea, we performed a cross-translation (Korean

French, FrenchKorean) and interviewed professional experts. The final questionnaire was

validated through the review of ergonomics, medical, and related high-speed train professionals.

Figure 4: Upper: applied 9 point likert-scaling,

lower: Modified magnitude estimation scaling for ride comfort evaluation

Factors were developed as 49 questions and organized with 8 dependent variables: boarding

time, motion sickness, visual fatigue, physical fatigue, seat comfort, collective ride comfort, fare

satisfaction and overall satisfaction.

Design of experiment

Researchers conducted a boarding experiment and interviewed passengers of KTX and TGV

under the given experimental design. The testing was carried out under the condition of forward

and backward seats, respectively. In order to minimize the difference of ride comfort results

among boarding time, this study executed the boarding experiment 5 times for 30 minutes (30,

60, 90, 120, and 150 minutes). Table 3 shows the schedule and conditions of the boarding

experiment.

Table 3: Introduction to experimentTitle KTX experiment (K-TGV) TGV experiment (TGV ID-Duplex)

Date 2004. 9. 18-10. 17 (4 weeks) 2005. 1. 31-2. 5 (1 week)Subjects 200 persons 150 persons

MethodA boarding interview experimentSeoul-Busan (400km), 2hrs30min (every 30 minutes)

A boarding interview experimentParis-Marseille (420km), 2 hrs 40min(every 30 minutes)

AdministratorSeoul National University, Southof Korea, 10 persons

AIX-Marseille University, France, 6persons

3.2 Analysis method

In anthropometry, the statistical method is hardly used in analyzing and presenting data (Julia

and Michael, 1992). This is because anthropometry uses reciprocal qualitative data acquired

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only through local grassroots observation and investigation, rather than the quantitative

measurement method of anthropology, which leads in the use of statistical methods in social

science. Regression analysis and the structural equation model are commonly used as methodsfor understanding the effect of factors through users activity in order to analyze the degree of

cultural effect (Hoogland and Boomsma, 1998). The conceptual models of ride comfort in both

countries were compared by analyzing the similarities and effects of the path between factors of

the model inside ride comfort using the structural equation model. The covariance matrix was

used as input data after transforming it into a normal scale for analysis of the structural equation

model (Joreskog and Sordom, 1993). Data in the structural equation model is satisfied with

assumed demand by inputting and converting the data into a formal score, and by securing

univariate normality and multivariate normality of each measuring variable. This produces a

more accurate result estimating the parameters of the model of ride comfort. Also, it can

compare factor loading values between endogenous variables of multi-group analyses. These

analyze the model of KTX ride comfort and of TGV ride comfort, which is a sample of other

populations using the covariance matrix instead of the correlation matrix as input data (Bollen,

1989; Lynam et al., 1993). The modeling used LISREL 8 and analyzed the fitness of the sample

in both countries (Suzuki, 1998).

This study uses a model of the structural equation model for KTX ride comfort in research

verified and suggested by Kim et al. (2006). Figure 5 shows a final model of high-speed train

ride comfort.

Figure 5: Final ride comfort model (Kim et al., 2006)

4. Results

4.1 Analysis

Because the analysis of basic statistics shows a different number of samples in the

experimental subject, the General Linear Model (GLM) was used in this analysis (Kim, 2002).

The analytical software used was SAS 6.0. The average of ride comfort in TGV passengers is

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63.19% and the average of KTX passengers is 55.53%, so it was statistically similar in the

distribution of ride comfort between two groups (p=0.0031). Table 4 shows the basic results of

ride comfort, overall satisfaction, and motion sickness from a comparative test. In the case ofride comfort and satisfaction, all of the results show that TGV passengers are higher, and in the

case of motion sickness, it shows that only about 50% of TGV passengers experience motion

sickness.

Table 4: Raw data analysis (unit: %)

ScopeRide comfort Satisfaction Motion sickness

Forward seatBackward

seatForward

seatBackward

seatForward

seatBackward

seatKTX 59.67 55.15 65.24 62.93 28.7 31.5TGV 65.22 62.94 73.0 69.0 15.0 16.0

The results of motion sickness, visual fatigue, physical fatigue, etc. also indicate that TGVpassengers experience 5-10% less than KTX passengers. In all kinds of factors, TGV

passengers have 1.5-2 times better results than KTX passengers. In both cases, passenger ride

comfort and overall satisfaction indicated high results in the forward direction, and motion

sickness showed a slightly high result in the backward direction, but the effective degree in each

boarding direction was not statistically significant (p>0.1). The results of a basic statistic analysis

indicated that time distribution on average in ride comfort was similar in its distribution, but

distribution was very different in high time distribution of ride comfort. This is because the two

high-speed trains share the negative factors resulting in lower ride comfort on average, but

because TGV has the positive factors, one could imply that the ride comfort of passengers is

improved.

4.2 Comparison of ride comfort in both countries

Model fitness

Generally, the structural model regards a sample size of 150-200 as the proper level (Ding et al.,

1995). In that case the input data will satisfy assumptions, so it has multivariate normality, and

the analysis has not had any problems (Oborne, 1978). Therefore, to validate the acquired

responses, the fitness analysis was performed with a sample size that can be used in the

structural model (Korean: 200 subjects, French: 150 subjects). Overall fitness of the model of

KTX and TGV ride comfort through two population samples is shown in Table 5. GFI (Goodness

of Fitness Index), standard RMR (Root Mean square Residual), RMSEA (Root Mean Square

Error of Approximation), and Chi-Square, which can estimate the overall fitness of the model

indicated a fitness index of an acceptable level in both KTX and TGV. And all of KTX and TGV

ride comfort results were similar where the model fitness and the fitness of the path loading

value were at a 90% confidence interval. These results mean that the models of KTX and TGV

ride comfort are statistically significant (Maria et al., 2005).

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Table 5: Fitness index

Index (category)KTX ride comfort

modelTGV ride comfort

modelRemarks

Degree of Freedom 105 105Minimum fit function Chi-Square 339.618 (p=0) 185.227 (p=0.0) Model acceptance

Normal theory weightedleast square chi-square

344.604 (p=0) 181.997 (p=0.0) Path acceptance

Estimated non-centrally parameter(NCP)

239.604 76.997

90 percent confidence interval forNCP

(187.136 ;299.678)

(43.438 ; 118.421)

Goodness of Fit Index (GFI) 0.928 0.882 If GFI>0.9, acceptAdjusted Goodness of Fit Index

(AGFI)0.909 0.883 If AGFI>0.9, accept

Standard RMR 0.0219 0.0685Root Mean square Residual (RMR) 0.0189 0.0321

Normed Fit Index (NFI) 0.882 0.802 If NFI>0.9, acceptNon-Normed Fit Index (NNFI) 0.888 0.821 If GFI>0.9, acceptRoot Mean Square Error ofApproximation (RMSEA)

0.0442 0.117If RMSEA

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Seat factors 0.838 0.686 0.673 0.475 1Tunneling

effect factors0.827 0.631 -0.066 -0.089 0.019 1

Motion

sicknessfactors

0.847 0.656 -0.287 -0.420 -0.025 0.301 1

Humanfatigue factors

0.817 0.692 0.649 0.343 0.136 -0.128 -0.291 1

Comparison of models in final ride comfort

Fitness in conceptual models of KTX and TGV ride comfort using the structural equation model

indicated that the model of KTX ride comfort (GFI=0.928; RMSEA=0.0422) was higher than the

model of TGV ride comfort (GFI=0.882; RMSEA=0.117), and both ride comfort models have

reliability and validity which are satisfied statistically. Figure 6 shows the models of the final ride

comfort model for both countries. The final ride comfort was most influenced by seat factors

(positive effect: 0.430) related to seats in the model of KTX ride comfort, and by human fatigue

factors (negative effect: -0.474) in the model of TGV ride comfort. In the pre-study (Kim et al.,

2006; Yun et al., 2005), it was analyzed that tunneling effect was not significant on the model

of KTX ride comfort (as well as the TGV model). In the case of the TGV model, tunneling effect

especially indirectly influenced final ride comfort through the mediate of human fatigue factors.

Figure 6: The ride comfort conceptual models of KTX(upper) and TGV(lower)

(Factor loading, standard error, t-value)

In the results of comparing the conceptual models of KTX ride comfort and TGV ride comfort,

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the final ride comfort was most influenced by seat factors in KTX and by human fatigue

factors in TGV. Also, seat factors had little influence (negative effect: -0.006) on human

fatigue factors in the model of TGV ride comfort. Ambient factors and motion sicknessfactors had an influence on each of the ride comfort factors (positive effect: 0.340) and

human fatigue factors (positive effect: 0.162), and this was influenced 1.5-2 times more than in

the model (0.244; 0.089) of KTX ride comfort. Table 7 shows the effective degree of each factor

in the models of KTX and TGV ride comfort.

Table 7: Effect degree of exogenous variables

ItemKTX ride comfort model TGV ride comfort model

Ride comfortfactors

Human fatiguefactors

Ride comfort factorsHuman fatigue

factorsHuman fatigue

factors-0.373 - -0.474 -

Ambient factors 0.244 -0.298 0.340 -0.267Seat factors 0.430 -0.198 0.446 -0.006

Tunneling effectfactors

-0.046(not significant)

0.081-0.017

(not significant)0.056

Motion sicknessfactors

- 0.089 - 0.162

Finally, in the case of the model of KTX ride comfort shown in Table 8, the main factor in the

conceptual model of final ride comfort was seat pitch (0.789) was greater than seat width

(0.702) and seat shape (0.561), which are seat variables related to seat factors in order. In

the case of the conceptual model of TGV ride comfort, it indicated that physical fatigue (0.894)

was greater than visual fatigue (0.746) related to human fatigue in order. However, in the

model of TGV ride comfort, because seat factors have more influence than in the model of

KTX ride comfort. Finally, for improving ride comfort in both countries, as shown in Table 8, in

the model of TGV ride comfort, unlike in the model of KTX ride comfort, because human fatigue

factors have much more influence than seat factors, it can be recognized that individual

fatigue, regardless of seat size, mainly influences ride comfort.

Table 8: Completely standardized parameter estimates and t-value (Final model for ride

comfort of high-speed train in Korea)

Latent variable ItemKTX TGV

Factorloading

Standarderror

t-ValuesFactorloading

Standarderror

t-Values

Ambient factorsCabin air-condition 0.497 0.060 9.069 0.813 0.047 6.812

Cabin noise 0.666 0.082 11.138 0.458 0.044 4.387

Seat factors

Seat leg room 0.420 0.075 8.401 0.453 0.047 4.772Seat width 0.702 0.109 15.241 0.787 0.096 9.274Seat pitch 0.789 0.108 17.540 0.895 0.097 10.975

Seat shape 0.561 0.082 11.656 0.458 0.027 4.839

Tunneling

effect factors

Tunneling vibration 0.807 0.068 17.988 0.913 0.070 10.181

Tunneling noise 0.877 0.073 19.755 0.861 0.080 9.558

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Tunneling dazzling 0.478 0.068 9.989 0.466 0.036 4.974

Motionsicknessfactors

Nausea 0.716 0.104 12.372 0.732 0.048 7.602Headache 0.660 0.116 11.646 0.515 0.087 5.240Dizziness 0.416 0.152 7.606 0.827 0.070 8.583

Human fatiguefactors

Visual fatigue 0.718 -* -* 0.746 -* -*Physical fatigue 0.935 0.162 12.076 0.894 0.197 6.482

Ride comfortfactors

Seat comfort 0.740 -* 18.248 0.695 -* -*Satisfaction 0.877 0.089 18.032 0.763 0.089 7.115Ride comfort 0.864 0.081 -* 0.690 0.070 6.521

*: Indicates a parameter fixed at 1.0 in the original solution.

5. Discussion and conclusion

This paper is intended to compare conceptual models of ride comfort in both countries

passengers to figure out the effect of cultural differences. As a result, this study found that the

conceptual models of ride comfort have common factors that have an influence on each model

of KTX and TGV, but their relative importance has distinct characteristics. Ride comfort is

analyzed from the four viewpoints of cultural comparison discussed in Chapter 2, considering

degrees of effectiveness on structural models. Critical factors on structures of ride comfort were

classified into common factors and uncommon factors. Similar objective design engineering

variables are included in common factors and cultural preferences resulting from cultural habits

are included in uncommon factors.

5.1 Cognitive difference of uncertainty avoidance

Collectively, KTX and TGV have identified with design engineering variables of seats and

compartment spaces, with backward direction due to fixed seats and average operative speed

in common. There is a difference in the grade of seat recline, degrees of VOD, fares, number of

tunnels, and noise/vibration (KRRI, 2003). But the similarity in design engineering variables did

not guarantee equal ride comfort or structures of ride comfort. In particular, KTX passengers,

whose structure of body is small (KATS, 2003), have higher dissatisfaction regarding the same

seat (backward seat, seat pitch) than European passengers, whose structure of body is

relatively tall. Consequently, it reduced the ride comfort of KTX. Because KTX passengers have

a strong tendency avoid the unfamiliar, it was concluded that they have a reason not to use the

backward and reclining seats of high-speed trains, which they have never experienced.

Although it is not statistically significant, in the tunneling effect with topographical factors of both

countries, ride comfort of KTX passengers was influenced by a dazzling effect after passing

tunnels in the aspect of tunnel running, and ride comfort of TGV passengers was influenced by

a tilting vibration when passing tunnels. This has been explicated to the conclusion that factors

that cannot improve ride comfort regarding the dissatisfaction of Korean passengers caused by

noise/vibration were of little relatively.

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5.2 Experience differences in context and time perception

In the aspect of compartment environment, KTX passengers overemphasized the safety andcomfort of the seats, and the dissatisfaction of passengers regarding backward seats is shown

as one of the critical factors of ride comfort. But in the case of TGV passengers, vibrations and

noises caused by amenities and the running train are the critical factors affecting ride comfort.

This implies that because TGV passengers (such as European) are from a pluralistic culture

that emphasizes synchronism through consciousness of space and time, they demand and

expect to be provided with other various services as well as with planned services at the same

time, and they had a high dissatisfaction with environments. Moreover, they show a different

satisfactory result for the same time delay.

Also, the dissatisfaction of TGV passengers regarding backward seats did not influence ride

comfort. In the case of TGV passengers, it was analyzed that noises and vibrations within the

train compartment caused by the running train are critical factors affecting ride comfort by

weighting human fatigue factors. This is caused by the difference in cultural experience

between KTX passengers who prefer a comfortable seat to the running environment and TGV

passengers who prefer comfortable environments within the train compartment to the seat

architecture itself. it means that boarding backward seats in TGV has not dropped the

preferences. Finally, it can be recognized that experience factors have more influence on the

ride comfort model, and this cultural-embeddedness operates as a main variable in the

improvement of ride comfort.

6. Acknowledgements

This project is supported and financed by a grant from the KOrea RAILroad(KORAIL) National-

2004-425 (the ergonomics study of ride comfort model development for Korea high-speed rail).

The authors gratefully acknowledge the assistant researchers of Seoul National University in

Korea and AIX-Marseille University in France.

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List of Tables

Table 1 Cultural variables in ergonomics studiesTable 2 Some international standards for evaluation of ride comfortTable 3 Introduction to the experimentTable 4 Raw data analysisTable 5 Fitness indexTable 6 Correlation matrix of endogenous variablesTable 7 Effect degree of exogenous variablesTable 8 Completely standardized parameter estimates and t-value

List of Figures

Figure 1 An approach to culture-specific machine designFigure 2 The Cultural Lens ModelFigure 3 The process of this studyFigure 4 Upper: Applied 9 point likert-scaling

Lower: Modified magnitude estimation scaling for ride comfort evaluationFigure 5 Final ride comfort modelFigure 6 The ride comfort conceptual models of KTX (upper) and TGV (lower)