CORD-19-Sentences  

CORD-19:eabb51d9cc4d09b9bb231c404d4fe55aaddab881 JSONTXT 9 Projects

Annnotations TAB TSV DIC JSON TextAE-old TextAE

Id Subject Object Predicate Lexical cue
TextSentencer_T1 0-68 Sentence denotes Measuring the part worth of the mode of transport in a trip package:
TextSentencer_T1 0-68 Sentence denotes Measuring the part worth of the mode of transport in a trip package:
TextSentencer_T2 69-136 Sentence denotes An extended Bradley-Terry model for paired-comparison conjoint data
TextSentencer_T2 69-136 Sentence denotes An extended Bradley-Terry model for paired-comparison conjoint data
TextSentencer_T3 138-146 Sentence denotes Abstract
TextSentencer_T3 138-146 Sentence denotes Abstract
TextSentencer_T4 147-312 Sentence denotes This study measures the travelers' perceived change in utility by accepting one of the modes of transport air, rail, or bus as one component of a packaged city trip.
TextSentencer_T4 147-312 Sentence denotes This study measures the travelers' perceived change in utility by accepting one of the modes of transport air, rail, or bus as one component of a packaged city trip.
TextSentencer_T5 313-428 Sentence denotes The part-worth values for the trip product elements are expected to depend on a number of traveler characteristics.
TextSentencer_T5 313-428 Sentence denotes The part-worth values for the trip product elements are expected to depend on a number of traveler characteristics.
TextSentencer_T6 429-552 Sentence denotes The predictors hypothesized are city travel experience, general modal preference, socio-economic status, and car ownership.
TextSentencer_T6 429-552 Sentence denotes The predictors hypothesized are city travel experience, general modal preference, socio-economic status, and car ownership.
TextSentencer_T7 553-673 Sentence denotes In the survey, the combinations of trip attributes differed between the two subgroups of leisure and business travelers.
TextSentencer_T7 553-673 Sentence denotes In the survey, the combinations of trip attributes differed between the two subgroups of leisure and business travelers.
TextSentencer_T8 674-792 Sentence denotes The leisure travelers rated three levels of mode, length of stay, and price, but only one level of the hotel category.
TextSentencer_T8 674-792 Sentence denotes The leisure travelers rated three levels of mode, length of stay, and price, but only one level of the hotel category.
TextSentencer_T9 793-914 Sentence denotes The business travelers were shown four mode alternatives and only two levels for each of the other trip product elements.
TextSentencer_T9 793-914 Sentence denotes The business travelers were shown four mode alternatives and only two levels for each of the other trip product elements.
TextSentencer_T10 915-1000 Sentence denotes The conjoint measurements were elaborated by fitting an Extended Bradley-Terry Model.
TextSentencer_T10 915-1000 Sentence denotes The conjoint measurements were elaborated by fitting an Extended Bradley-Terry Model.
TextSentencer_T11 1001-1076 Sentence denotes Demonstrating the application of the EBTM is the main purpose of the paper.
TextSentencer_T11 1001-1076 Sentence denotes Demonstrating the application of the EBTM is the main purpose of the paper.
TextSentencer_T12 1077-1164 Sentence denotes The EBTM offers several advantages over the more popular versions of conjoint analysis.
TextSentencer_T12 1077-1164 Sentence denotes The EBTM offers several advantages over the more popular versions of conjoint analysis.
TextSentencer_T13 1165-1378 Sentence denotes It correctly treats ties and allows for simultaneous estimation of the trip package ('object') parameters, object covariates (trip attributes), subject covariates (traveler characteristics) and their interactions.
TextSentencer_T13 1165-1378 Sentence denotes It correctly treats ties and allows for simultaneous estimation of the trip package ('object') parameters, object covariates (trip attributes), subject covariates (traveler characteristics) and their interactions.
TextSentencer_T14 1379-1498 Sentence denotes For both the business and the leisure travelers, the mode of transport dominated the assessment of a city trip package.
TextSentencer_T14 1379-1498 Sentence denotes For both the business and the leisure travelers, the mode of transport dominated the assessment of a city trip package.
TextSentencer_T15 1499-1655 Sentence denotes For leisure tourists, e.g., switching from train 2nd class to an economy flight boosted the trip package more than twice as much as replacing train for bus.
TextSentencer_T15 1499-1655 Sentence denotes For leisure tourists, e.g., switching from train 2nd class to an economy flight boosted the trip package more than twice as much as replacing train for bus.
TextSentencer_T16 1656-1761 Sentence denotes A variation of the package price was much more important for the leisure than for the business travelers.
TextSentencer_T16 1656-1761 Sentence denotes A variation of the package price was much more important for the leisure than for the business travelers.
TextSentencer_T17 1762-1883 Sentence denotes The socio-economic status proved to be an important factor and was particularly influential among the business travelers.
TextSentencer_T17 1762-1883 Sentence denotes The socio-economic status proved to be an important factor and was particularly influential among the business travelers.
TextSentencer_T18 1884-2036 Sentence denotes In the leisure tourists' sub-sample age was not only important for valuing the mode of transport, but had a preferential impact for all trip components.
TextSentencer_T18 1884-2036 Sentence denotes In the leisure tourists' sub-sample age was not only important for valuing the mode of transport, but had a preferential impact for all trip components.
TextSentencer_T19 2037-2164 Sentence denotes Finally, the limitations of this demonstration study that discourage extrapolation to city travelers in general are emphasized.
TextSentencer_T19 2037-2164 Sentence denotes Finally, the limitations of this demonstration study that discourage extrapolation to city travelers in general are emphasized.
TextSentencer_T20 2166-2286 Sentence denotes This research uses data from a project aimed at assessing the 'importance of air transport' for the Greater Vienna area.
TextSentencer_T20 2166-2286 Sentence denotes This research uses data from a project aimed at assessing the 'importance of air transport' for the Greater Vienna area.
TextSentencer_T21 2287-2420 Sentence denotes While many different ways may be conceived of how to tackle this issue, the authors decided to focus on the travelers' point of view.
TextSentencer_T21 2287-2420 Sentence denotes While many different ways may be conceived of how to tackle this issue, the authors decided to focus on the travelers' point of view.
TextSentencer_T22 2421-2565 Sentence denotes If a raison d'être exists for air transport thenin the simple mind of a marketing scientistthe reason likely relates to the airlines' customers.
TextSentencer_T22 2421-2565 Sentence denotes If a raison d'être exists for air transport thenin the simple mind of a marketing scientistthe reason likely relates to the airlines' customers.
TextSentencer_T23 2566-2698 Sentence denotes The problem was downsized to a workable version involving travelers ex Vienna on leisure or business trips to another European city.
TextSentencer_T23 2566-2698 Sentence denotes The problem was downsized to a workable version involving travelers ex Vienna on leisure or business trips to another European city.
TextSentencer_T24 2699-2827 Sentence denotes From the consumer behavior point of view the 'importance' of air transport may be interpreted in terms of preference or utility.
TextSentencer_T24 2699-2827 Sentence denotes From the consumer behavior point of view the 'importance' of air transport may be interpreted in terms of preference or utility.
TextSentencer_T25 2828-3085 Sentence denotes Its value becomes apparent as a variation in the height of preference or the amount of perceived utilitythe 'part worth' in the terminology of classical conjoint analysisthe airplane seat contributes to the overall benefit attributed to a city trip package.
TextSentencer_T25 2828-3085 Sentence denotes Its value becomes apparent as a variation in the height of preference or the amount of perceived utilitythe 'part worth' in the terminology of classical conjoint analysisthe airplane seat contributes to the overall benefit attributed to a city trip package.
TextSentencer_T26 3086-3167 Sentence denotes Measuring the travelers perceived utility of a means of transport is nothing new.
TextSentencer_T26 3086-3167 Sentence denotes Measuring the travelers perceived utility of a means of transport is nothing new.
TextSentencer_T27 3168-3279 Sentence denotes In transport studies, of course, the choice of a mode of transport represents one of the most popular problems.
TextSentencer_T27 3168-3279 Sentence denotes In transport studies, of course, the choice of a mode of transport represents one of the most popular problems.
TextSentencer_T28 3280-3431 Sentence denotes It may be analyzed on aggregate level by means of cross elasticities (Wardman, 1997) or by discrete choice micromodels (such as the multinomial logit).
TextSentencer_T28 3280-3431 Sentence denotes It may be analyzed on aggregate level by means of cross elasticities (Wardman, 1997) or by discrete choice micromodels (such as the multinomial logit).
TextSentencer_T29 3432-3547 Sentence denotes During the 1970s, MNL models were introduced by 2000 Nobel Laureate Daniel McFadden for investigating modal choice.
TextSentencer_T29 3432-3547 Sentence denotes During the 1970s, MNL models were introduced by 2000 Nobel Laureate Daniel McFadden for investigating modal choice.
TextSentencer_T30 3548-3689 Sentence denotes Today, they are standard tools in transportation research and consulting practice (Wardman et al., 1992; Cambridge Systematics, Inc., 2002) .
TextSentencer_T30 3548-3689 Sentence denotes Today, they are standard tools in transportation research and consulting practice (Wardman et al., 1992; Cambridge Systematics, Inc., 2002) .
TextSentencer_T31 3690-3829 Sentence denotes Later, choice models were embraced by marketing scientists and have become one of the major threads in advanced consumer behavior research.
TextSentencer_T31 3690-3829 Sentence denotes Later, choice models were embraced by marketing scientists and have become one of the major threads in advanced consumer behavior research.
TextSentencer_T32 3830-4052 Sentence denotes A comprehensive review of choice models in tourism is provided by Crouch and Louviere (2001) ; among the 38 pieces of research itemized, however, there is none dealing with alternative modes of transport in a trip package.
TextSentencer_T32 3830-4052 Sentence denotes A comprehensive review of choice models in tourism is provided by Crouch and Louviere (2001) ; among the 38 pieces of research itemized, however, there is none dealing with alternative modes of transport in a trip package.
TextSentencer_T33 4053-4175 Sentence denotes Sheldon and Mak (1987) applied logistic regression to analyze various attributes of package tours and traveler covariates.
TextSentencer_T33 4053-4175 Sentence denotes Sheldon and Mak (1987) applied logistic regression to analyze various attributes of package tours and traveler covariates.
TextSentencer_T34 4176-4225 Sentence denotes The mode of transport, however, was not included.
TextSentencer_T34 4176-4225 Sentence denotes The mode of transport, however, was not included.
TextSentencer_T35 4226-4305 Sentence denotes In this study the mode of transport will be a prominent part of a trip package.
TextSentencer_T35 4226-4305 Sentence denotes In this study the mode of transport will be a prominent part of a trip package.
TextSentencer_T36 4306-4445 Sentence denotes Its utility as perceived by the travelers then may be compared to those of the other trip components simultaneously present in the package.
TextSentencer_T36 4306-4445 Sentence denotes Its utility as perceived by the travelers then may be compared to those of the other trip components simultaneously present in the package.
TextSentencer_T37 4446-4577 Sentence denotes A conjoint analysis approach is usually preferred for exploring the portions of utility contributed by individual product features.
TextSentencer_T37 4446-4577 Sentence denotes A conjoint analysis approach is usually preferred for exploring the portions of utility contributed by individual product features.
TextSentencer_T38 4578-4649 Sentence denotes Again, this is not new methodology in tourism and hospitality research.
TextSentencer_T38 4578-4649 Sentence denotes Again, this is not new methodology in tourism and hospitality research.
TextSentencer_T39 4650-4770 Sentence denotes Renaghan and Kay (1987) analyzed the part-worth utilities aroused by the services tied together in a convention product.
TextSentencer_T39 4650-4770 Sentence denotes Renaghan and Kay (1987) analyzed the part-worth utilities aroused by the services tied together in a convention product.
TextSentencer_T40 4771-4988 Sentence denotes One of the most popular sample applications of conjoint analysis for very complex mixtures of services also originates from hospitality research; it is the "Courtyard by Marriott" case outlined by Wind et al. (1989) .
TextSentencer_T40 4771-4988 Sentence denotes One of the most popular sample applications of conjoint analysis for very complex mixtures of services also originates from hospitality research; it is the "Courtyard by Marriott" case outlined by Wind et al. (1989) .
TextSentencer_T41 4989-5120 Sentence denotes Carmichael (1992) applied a standard version of conjoint analysis to analyze artificial attribute bundles representing ski resorts.
TextSentencer_T41 4989-5120 Sentence denotes Carmichael (1992) applied a standard version of conjoint analysis to analyze artificial attribute bundles representing ski resorts.
TextSentencer_T42 5121-5325 Sentence denotes Mazanec (2002) analyzed the effects of Euro versus old currency pricing of tour packages; he used a conjoint model with random coefficients to allow for traveler heterogeneity in the part-worth estimates.
TextSentencer_T42 5121-5325 Sentence denotes Mazanec (2002) analyzed the effects of Euro versus old currency pricing of tour packages; he used a conjoint model with random coefficients to allow for traveler heterogeneity in the part-worth estimates.
TextSentencer_T43 5326-5378 Sentence denotes The link between tourism and transport is ambiguous.
TextSentencer_T43 5326-5378 Sentence denotes The link between tourism and transport is ambiguous.
TextSentencer_T44 5379-5526 Sentence denotes The literature offers two interpretations of the transport-tourism interface: the transport "for" tourism or the transport "as" tourism philosophy.
TextSentencer_T44 5379-5526 Sentence denotes The literature offers two interpretations of the transport-tourism interface: the transport "for" tourism or the transport "as" tourism philosophy.
TextSentencer_T45 5527-5694 Sentence denotes The former acknowledges only the utilitarian character of transport services while the latter admits "intrinsic value as tourism experience" (Lumsdon and Page, 2004) .
TextSentencer_T45 5527-5694 Sentence denotes The former acknowledges only the utilitarian character of transport services while the latter admits "intrinsic value as tourism experience" (Lumsdon and Page, 2004) .
TextSentencer_T46 5695-5859 Sentence denotes Regardless of which interpretation one chooses to follow, the role of the mode of transport in the travelers' evaluation of a trip package seems largely unexplored.
TextSentencer_T46 5695-5859 Sentence denotes Regardless of which interpretation one chooses to follow, the role of the mode of transport in the travelers' evaluation of a trip package seems largely unexplored.
TextSentencer_T47 5860-6016 Sentence denotes There are, of course, innumerous travel and guest surveys from commercial sources including the mode of transport among their repertoire of trip attributes.
TextSentencer_T47 5860-6016 Sentence denotes There are, of course, innumerous travel and guest surveys from commercial sources including the mode of transport among their repertoire of trip attributes.
TextSentencer_T48 6017-6220 Sentence denotes However, these studies present their results in a usually narrative manner reporting about the frequencies of modes preferred without exploring the modes' contribution to the overall utility of the trip.
TextSentencer_T48 6017-6220 Sentence denotes However, these studies present their results in a usually narrative manner reporting about the frequencies of modes preferred without exploring the modes' contribution to the overall utility of the trip.
TextSentencer_T49 6221-6411 Sentence denotes One of the rare exceptions employing an up-to-date model of mode choice in a tourism setting is Nerhagen (2003) 's recent analysis of the influence of previous experience on choice behavior.
TextSentencer_T49 6221-6411 Sentence denotes One of the rare exceptions employing an up-to-date model of mode choice in a tourism setting is Nerhagen (2003) 's recent analysis of the influence of previous experience on choice behavior.
TextSentencer_T50 6412-6565 Sentence denotes This author proposes a binomial probit model with train and car as the alternatives and a linear utility function combining mode and traveler attributes.
TextSentencer_T50 6412-6565 Sentence denotes This author proposes a binomial probit model with train and car as the alternatives and a linear utility function combining mode and traveler attributes.
TextSentencer_T51 6566-6676 Sentence denotes She also estimates the willingness-to-pay for a fictitious return trip dependent on former car or train usage.
TextSentencer_T51 6566-6676 Sentence denotes She also estimates the willingness-to-pay for a fictitious return trip dependent on former car or train usage.
TextSentencer_T52 6677-6742 Sentence denotes This study demonstrates a new method for analyzing conjoint data.
TextSentencer_T52 6677-6742 Sentence denotes This study demonstrates a new method for analyzing conjoint data.
TextSentencer_T53 6743-6828 Sentence denotes The extended Bradley-Terry Model (EBTM) has not yet been applied in tourism research.
TextSentencer_T53 6743-6828 Sentence denotes The extended Bradley-Terry Model (EBTM) has not yet been applied in tourism research.
TextSentencer_T54 6829-6988 Sentence denotes This study employs it for measuring the travelers' perceived change in utility by adopting one of the modes air, train, or bus as part of a packaged city trip.
TextSentencer_T54 6829-6988 Sentence denotes This study employs it for measuring the travelers' perceived change in utility by adopting one of the modes air, train, or bus as part of a packaged city trip.
TextSentencer_T55 6989-7071 Sentence denotes The respondents assess a set of fictitious city trips on a ten-point rating scale.
TextSentencer_T55 6989-7071 Sentence denotes The respondents assess a set of fictitious city trips on a ten-point rating scale.
TextSentencer_T56 7072-7132 Sentence denotes They indicate the likelihood of booking such a trip package.
TextSentencer_T56 7072-7132 Sentence denotes They indicate the likelihood of booking such a trip package.
TextSentencer_T57 7133-7322 Sentence denotes Given the questionable metric properties of the rating data only the preferential relationships among pairs of trip alternatives (preferred, not preferred, no preference) will be exploited.
TextSentencer_T57 7133-7322 Sentence denotes Given the questionable metric properties of the rating data only the preferential relationships among pairs of trip alternatives (preferred, not preferred, no preference) will be exploited.
TextSentencer_T58 7323-7458 Sentence denotes The trip packages consist of the key product elements destination, mode of transport, type of accommodation, length of stay, and price.
TextSentencer_T58 7323-7458 Sentence denotes The trip packages consist of the key product elements destination, mode of transport, type of accommodation, length of stay, and price.
TextSentencer_T59 7459-7591 Sentence denotes Realistic combinations were formed after examining the catalogues of 17 tour operators offering city trips to European destinations.
TextSentencer_T59 7459-7591 Sentence denotes Realistic combinations were formed after examining the catalogues of 17 tour operators offering city trips to European destinations.
TextSentencer_T60 7592-7707 Sentence denotes The part-worth values for the trip product elements are expected to depend on a number of traveler characteristics.
TextSentencer_T60 7592-7707 Sentence denotes The part-worth values for the trip product elements are expected to depend on a number of traveler characteristics.
TextSentencer_T61 7708-7832 Sentence denotes The predictors hypothesized are: city travel experience, general modal preference, socio-economic status, and car ownership.
TextSentencer_T61 7708-7832 Sentence denotes The predictors hypothesized are: city travel experience, general modal preference, socio-economic status, and car ownership.
TextSentencer_T62 7833-7971 Sentence denotes Fig. 1 condenses the underlying hypotheses into a starting model to guide the data collection and the subsequent steps of model selection.
TextSentencer_T62 7833-7971 Sentence denotes Fig. 1 condenses the underlying hypotheses into a starting model to guide the data collection and the subsequent steps of model selection.
TextSentencer_T63 7972-8081 Sentence denotes Socio-economic status is represented by the interaction effect of the two variables education and occupation.
TextSentencer_T63 7972-8081 Sentence denotes Socio-economic status is represented by the interaction effect of the two variables education and occupation.
TextSentencer_T64 8082-8250 Sentence denotes Restricting the levels of the trip variables to a small number (Table 1 ) simplified the task for the respondents while covering a reasonable range of attribute values.
TextSentencer_T64 8082-8250 Sentence denotes Restricting the levels of the trip variables to a small number (Table 1 ) simplified the task for the respondents while covering a reasonable range of attribute values.
TextSentencer_T65 8251-8363 Sentence denotes The data collection included travelers flying from Vienna on leisure or business trips to another European city.
TextSentencer_T65 8251-8363 Sentence denotes The data collection included travelers flying from Vienna on leisure or business trips to another European city.
TextSentencer_T66 8364-8450 Sentence denotes Travelers were interviewed while waiting for take-off at Vienna International Airport.
TextSentencer_T66 8364-8450 Sentence denotes Travelers were interviewed while waiting for take-off at Vienna International Airport.
TextSentencer_T67 8451-8723 Sentence denotes The fieldwork occurred during September, the only month in 2003 with a significant proportion of inter-city leisure trips which was not impacted by disturbances such as the Iraq War, the Severe Acute Respiratory Syndrome (SARS), or the pilots' strike at Austrian Airlines.
TextSentencer_T67 8451-8723 Sentence denotes The fieldwork occurred during September, the only month in 2003 with a significant proportion of inter-city leisure trips which was not impacted by disturbances such as the Iraq War, the Severe Acute Respiratory Syndrome (SARS), or the pilots' strike at Austrian Airlines.
TextSentencer_T68 8724-8889 Sentence denotes Two multistep random samples (day, departure time, flight) were taken, one was 600 people departing on a leisure trip and the other comprises 600 business travelers.
TextSentencer_T68 8724-8889 Sentence denotes Two multistep random samples (day, departure time, flight) were taken, one was 600 people departing on a leisure trip and the other comprises 600 business travelers.
TextSentencer_T69 8890-9146 Sentence denotes Note that the following restrictions of the sampling approach forbid generalization to a wider population of city travelers: focus on air travelers residing in the Greater Vienna area, on trips to European city destinations, on the month of September only.
TextSentencer_T69 8890-9146 Sentence denotes Note that the following restrictions of the sampling approach forbid generalization to a wider population of city travelers: focus on air travelers residing in the Greater Vienna area, on trips to European city destinations, on the month of September only.
TextSentencer_T70 9147-9267 Sentence denotes Designs were sought for a reasonable number of 8-9 combinations of the five trip attribute factors each with 2-4 values.
TextSentencer_T70 9147-9267 Sentence denotes Designs were sought for a reasonable number of 8-9 combinations of the five trip attribute factors each with 2-4 values.
TextSentencer_T71 9268-9371 Sentence denotes The combinations of trip attributes differ between the two subgroups of leisure and business travelers.
TextSentencer_T71 9268-9371 Sentence denotes The combinations of trip attributes differ between the two subgroups of leisure and business travelers.
TextSentencer_T72 9372-9490 Sentence denotes The leisure travelers rated three levels of mode, length of stay, and price, but only one level of the hotel category.
TextSentencer_T72 9372-9490 Sentence denotes The leisure travelers rated three levels of mode, length of stay, and price, but only one level of the hotel category.
TextSentencer_T73 9491-9612 Sentence denotes The business travelers were shown four mode alternatives and only two levels for each of the other trip product elements.
TextSentencer_T73 9491-9612 Sentence denotes The business travelers were shown four mode alternatives and only two levels for each of the other trip product elements.
TextSentencer_T74 9613-9699 Sentence denotes An orthogonal design with 9 artificial trip packages was chosen for leisure travelers.
TextSentencer_T74 9613-9699 Sentence denotes An orthogonal design with 9 artificial trip packages was chosen for leisure travelers.
TextSentencer_T75 9700-9826 Sentence denotes For the business travelers a compromise had to be drawn between perfect orthogonality and sufficiently realistic combinations.
TextSentencer_T75 9700-9826 Sentence denotes For the business travelers a compromise had to be drawn between perfect orthogonality and sufficiently realistic combinations.
TextSentencer_T76 9827-9959 Sentence denotes Levels correlated up to .71 (mode and length) and .44 (mode and hotel) were accepted to yield a nontrivial set of trip combinations.
TextSentencer_T76 9827-9959 Sentence denotes Levels correlated up to .71 (mode and length) and .44 (mode and hotel) were accepted to yield a nontrivial set of trip combinations.
TextSentencer_T77 9960-10064 Sentence denotes The respondents assessed each package on a ten-point rating scale expressing their degree of preference.
TextSentencer_T77 9960-10064 Sentence denotes The respondents assessed each package on a ten-point rating scale expressing their degree of preference.
TextSentencer_T78 10065-10203 Sentence denotes Further processing was limited to those respondents with a complete set of covariate values and who differentiated at least five packages.
TextSentencer_T78 10065-10203 Sentence denotes Further processing was limited to those respondents with a complete set of covariate values and who differentiated at least five packages.
TextSentencer_T79 10204-10277 Sentence denotes This leaves 499 (536) cases from a N = 600 sample for leisure (business).
TextSentencer_T79 10204-10277 Sentence denotes This leaves 499 (536) cases from a N = 600 sample for leisure (business).
TextSentencer_T80 10278-10369 Sentence denotes The conjoint exercise will be elaborated by fitting an Extended Bradley-Terry Model (EBTM).
TextSentencer_T80 10278-10369 Sentence denotes The conjoint exercise will be elaborated by fitting an Extended Bradley-Terry Model (EBTM).
TextSentencer_T81 10370-10478 Sentence denotes The EBTM offers several advantages over more popular versions of conjoint analysis (Dittrich et al., 1998) .
TextSentencer_T81 10370-10478 Sentence denotes The EBTM offers several advantages over more popular versions of conjoint analysis (Dittrich et al., 1998) .
TextSentencer_T82 10479-10681 Sentence denotes In particular, it allows for simultaneous estimation of the trip package ('object') parameters, object covariates (trip attributes), subject covariates (traveler characteristics) and their interactions.
TextSentencer_T82 10479-10681 Sentence denotes In particular, it allows for simultaneous estimation of the trip package ('object') parameters, object covariates (trip attributes), subject covariates (traveler characteristics) and their interactions.
TextSentencer_T83 10682-10928 Sentence denotes In fact, the EBTM is a model for paired comparison data, i.e., the aim is to obtain estimated overall rankings of objects (with locations on an interval scale), where each subject (or judge) makes one or more comparisons between pairs of objects.
TextSentencer_T83 10682-10928 Sentence denotes In fact, the EBTM is a model for paired comparison data, i.e., the aim is to obtain estimated overall rankings of objects (with locations on an interval scale), where each subject (or judge) makes one or more comparisons between pairs of objects.
TextSentencer_T84 10929-11237 Sentence denotes This type of model can be applied to rating data as recorded in the current study by simply transforming the ratings of two trip packages, A and B say, into a paired comparison response which can be either 'A preferred', 'B preferred' or 'equal preference' depending on the rating value for the two packages.
TextSentencer_T84 10929-11237 Sentence denotes This type of model can be applied to rating data as recorded in the current study by simply transforming the ratings of two trip packages, A and B say, into a paired comparison response which can be either 'A preferred', 'B preferred' or 'equal preference' depending on the rating value for the two packages.
TextSentencer_T85 11238-11366 Sentence denotes Using such models may prove useful in overcoming problems arising from questionable metric properties of rating scale responses.
TextSentencer_T85 11238-11366 Sentence denotes Using such models may prove useful in overcoming problems arising from questionable metric properties of rating scale responses.
TextSentencer_T86 11367-11540 Sentence denotes This section provides a short presentation of the Bradley Terry (BT) Model (Bradley and Terry, 1952) and an extended version (EBTM) as introduced by Dittrich et al. (1998) .
TextSentencer_T86 11367-11540 Sentence denotes This section provides a short presentation of the Bradley Terry (BT) Model (Bradley and Terry, 1952) and an extended version (EBTM) as introduced by Dittrich et al. (1998) .
TextSentencer_T87 11541-11589 Sentence denotes The basic Bradley-Terry (BT) Model is defined by
TextSentencer_T87 11541-11589 Sentence denotes The basic Bradley-Terry (BT) Model is defined by
TextSentencer_T88 11590-11849 Sentence denotes where in a given comparison of object j to object k denoted by ( jk), π ( jk) j is the probability that object j (O j ) is preferred to object k (O k ) and π j and π k are non-negative parameters describing the location of the objects on the preference scale.
TextSentencer_T88 11590-11849 Sentence denotes where in a given comparison of object j to object k denoted by ( jk), π ( jk) j is the probability that object j (O j ) is preferred to object k (O k ) and π j and π k are non-negative parameters describing the location of the objects on the preference scale.
TextSentencer_T89 11850-11951 Sentence denotes The Bradley-Terry Model may be fitted using ordinary methods for binomial logistic regression models.
TextSentencer_T89 11850-11951 Sentence denotes The Bradley-Terry Model may be fitted using ordinary methods for binomial logistic regression models.
TextSentencer_T90 11952-12016 Sentence denotes Alternatively, the BT model can be fitted as a log-linear model.
TextSentencer_T90 11952-12016 Sentence denotes Alternatively, the BT model can be fitted as a log-linear model.
TextSentencer_T91 12017-12097 Sentence denotes Given J objects, J 2 distinct pairwise comparisons between objects are possible.
TextSentencer_T91 12017-12097 Sentence denotes Given J objects, J 2 distinct pairwise comparisons between objects are possible.
TextSentencer_T92 12098-12282 Sentence denotes Let n ( jk) be the number of comparisons between object j and object k and let Y ( jk) j be the number of preferences for object j and Y ( jk) k the number of preferences for object k.
TextSentencer_T92 12098-12282 Sentence denotes Let n ( jk) be the number of comparisons between object j and object k and let Y ( jk) j be the number of preferences for object j and Y ( jk) k the number of preferences for object k.
TextSentencer_T93 12283-12438 Sentence denotes The outcome of a paired comparison experiment can be regarded as a J 2 Â J incomplete twodimensional object pair × decision for object j contingency table.
TextSentencer_T93 12283-12438 Sentence denotes The outcome of a paired comparison experiment can be regarded as a J 2 Â J incomplete twodimensional object pair × decision for object j contingency table.
TextSentencer_T94 12439-12518 Sentence denotes E.g, given three objects the appropriate contingency table is given as follows:
TextSentencer_T94 12439-12518 Sentence denotes E.g, given three objects the appropriate contingency table is given as follows:
TextSentencer_T95 12519-12531 Sentence denotes Total number
TextSentencer_T95 12519-12531 Sentence denotes Total number
TextSentencer_T96 12532-12570 Sentence denotes For object 1 For object 2 For object 3
TextSentencer_T96 12532-12570 Sentence denotes For object 1 For object 2 For object 3
TextSentencer_T97 12571-12660 Sentence denotes The random variables Y ( jk) j and Y ( jk)k are assumed to follow a Poisson distribution.
TextSentencer_T97 12571-12660 Sentence denotes The random variables Y ( jk) j and Y ( jk)k are assumed to follow a Poisson distribution.
TextSentencer_T98 12661-12768 Sentence denotes Conditional on fixed n ( jk) , the (Y ( jk) j , Y ( jk)k ) are multinomially (here binomially) distributed.
TextSentencer_T98 12661-12768 Sentence denotes Conditional on fixed n ( jk) , the (Y ( jk) j , Y ( jk)k ) are multinomially (here binomially) distributed.
TextSentencer_T99 12769-12884 Sentence denotes The expected number of preferences of object j to object k is denoted by m ( jk) j and given by n ( jk) π ( jk) j .
TextSentencer_T99 12769-12884 Sentence denotes The expected number of preferences of object j to object k is denoted by m ( jk) j and given by n ( jk) π ( jk) j .
TextSentencer_T100 12885-13086 Sentence denotes Using a respecification for the π ( jk) j 's and standard notation for log-linear models for contingency tables the log-linear formulation of the basic BT model is given by the following two equations:
TextSentencer_T100 12885-13086 Sentence denotes Using a respecification for the π ( jk) j 's and standard notation for log-linear models for contingency tables the log-linear formulation of the basic BT model is given by the following two equations:
TextSentencer_T101 13087-13331 Sentence denotes where μ ( jk) j = μ ( jk)k are nuisance parameters and may be interpreted as interaction parameters representing the objects involved in the respective comparisons, fixing therefore the corresponding marginal distribution, i.e., the n ( jk) 's.
TextSentencer_T101 13087-13331 Sentence denotes where μ ( jk) j = μ ( jk)k are nuisance parameters and may be interpreted as interaction parameters representing the objects involved in the respective comparisons, fixing therefore the corresponding marginal distribution, i.e., the n ( jk) 's.
TextSentencer_T102 13332-13429 Sentence denotes The λ j O 's represent object parameters (O is used for objects) and are related to the π j 's by
TextSentencer_T102 13332-13429 Sentence denotes The λ j O 's represent object parameters (O is used for objects) and are related to the π j 's by
TextSentencer_T103 13430-13505 Sentence denotes So far, there is no advantage in using the log-linear over the logit model.
TextSentencer_T103 13430-13505 Sentence denotes So far, there is no advantage in using the log-linear over the logit model.
TextSentencer_T104 13506-13572 Sentence denotes However, there are often situations where no decision can be made.
TextSentencer_T104 13506-13572 Sentence denotes However, there are often situations where no decision can be made.
TextSentencer_T105 13573-13819 Sentence denotes This indeterminate state of preference for a pair of alternatives (ties) is easily incorporated into the log-linear form of the basic BT model when using another respecification for the π ( jk) j 's, i.e., by adding a third equation to the above,
TextSentencer_T105 13573-13819 Sentence denotes This indeterminate state of preference for a pair of alternatives (ties) is easily incorporated into the log-linear form of the basic BT model when using another respecification for the π ( jk) j 's, i.e., by adding a third equation to the above,
TextSentencer_T106 13820-13969 Sentence denotes where lnm ( jk)0 is the expected number of 'no decision' in the comparison ( jk) and the parameter δ represents a general tendency to indecisiveness.
TextSentencer_T106 13820-13969 Sentence denotes where lnm ( jk)0 is the expected number of 'no decision' in the comparison ( jk) and the parameter δ represents a general tendency to indecisiveness.
TextSentencer_T107 13970-14141 Sentence denotes A major advantage of the log-linear formulation is the possibility to extend the basic BT model by incorporating parameters for subject (rater) and object characteristics.
TextSentencer_T107 13970-14141 Sentence denotes A major advantage of the log-linear formulation is the possibility to extend the basic BT model by incorporating parameters for subject (rater) and object characteristics.
TextSentencer_T108 14142-14403 Sentence denotes Considering subject covariates allows for moving away from the assumption of equal preference orderings for all subjects and object covariates allow for investigating certain characteristics of objects that make up the degree of preference for a certain object.
TextSentencer_T108 14142-14403 Sentence denotes Considering subject covariates allows for moving away from the assumption of equal preference orderings for all subjects and object covariates allow for investigating certain characteristics of objects that make up the degree of preference for a certain object.
TextSentencer_T109 14404-14579 Sentence denotes Moreover, possible interaction effects might reflect .0000 aliased Amsterdam Train/2nd 4 4 ⁎ 258 different importance of object characteristics according to subject variables.
TextSentencer_T109 14404-14579 Sentence denotes Moreover, possible interaction effects might reflect .0000 aliased Amsterdam Train/2nd 4 4 ⁎ 258 different importance of object characteristics according to subject variables.
TextSentencer_T110 14580-14805 Sentence denotes To initially illustrate the approach for incorporating subject specific covariates, such as gender, assume that the judges are classified according to one categorical covariate S (S is for subjects as opposed to the O above).
TextSentencer_T110 14580-14805 Sentence denotes To initially illustrate the approach for incorporating subject specific covariates, such as gender, assume that the judges are classified according to one categorical covariate S (S is for subjects as opposed to the O above).
TextSentencer_T111 14806-14966 Sentence denotes Let m ( jk) j|l be the expected number of preferences for object j (when compared to object k) where the judges are classified in covariate class l, l = 1,…, L.
TextSentencer_T111 14806-14966 Sentence denotes Let m ( jk) j|l be the expected number of preferences for object j (when compared to object k) where the judges are classified in covariate class l, l = 1,…, L.
TextSentencer_T112 14967-15070 Sentence denotes The log-linear representation of this extended Bradley-Terry Model is given by the following equations:
TextSentencer_T112 14967-15070 Sentence denotes The log-linear representation of this extended Bradley-Terry Model is given by the following equations:
TextSentencer_T113 15071-15433 Sentence denotes The set of (nuisance) parameters λ l S represent the main effects of the subject covariate measured on the l-th level; λ jl OS and λ kl OS are the (useful) subject-object interaction parameters describing the effect of the subject covariate observed on category l on the preference for objects j and k, respectively, and δ is again the 'no preference' parameter.
TextSentencer_T113 15071-15433 Sentence denotes The set of (nuisance) parameters λ l S represent the main effects of the subject covariate measured on the l-th level; λ jl OS and λ kl OS are the (useful) subject-object interaction parameters describing the effect of the subject covariate observed on category l on the preference for objects j and k, respectively, and δ is again the 'no preference' parameter.
TextSentencer_T114 15434-15690 Sentence denotes Effectively, a separate contingency table is constructed for each level of the categorical covariate, giving the dimension of the complete table as J 2 Â J Â L, that is, number of comparisons × number of objects × number of levels of the subject covariate.
TextSentencer_T114 15434-15690 Sentence denotes Effectively, a separate contingency table is constructed for each level of the categorical covariate, giving the dimension of the complete table as J 2 Â J Â L, that is, number of comparisons × number of objects × number of levels of the subject covariate.
TextSentencer_T115 15691-15767 Sentence denotes The expansion to several subject parameters is conceptually straightforward.
TextSentencer_T115 15691-15767 Sentence denotes The expansion to several subject parameters is conceptually straightforward.
TextSentencer_T116 15768-16393 Sentence denotes The level l is replaced by a combination of levels for several covariates (L then denotes the total number of levels given by the crossclassification of all subject variables in case of only categorical covariates, otherwise it is the total number of subjects n), the nuisance parameter λ l S is the highest interaction term between all subject variables if they are all categorical (otherwise it is a parameter having n levels) and the λ jl OS are the (interesting) parameters describing the effect of subject characteristics (main effects or interaction terms between subject variables) on the preference value of object j.
TextSentencer_T116 15768-16393 Sentence denotes The level l is replaced by a combination of levels for several covariates (L then denotes the total number of levels given by the crossclassification of all subject variables in case of only categorical covariates, otherwise it is the total number of subjects n), the nuisance parameter λ l S is the highest interaction term between all subject variables if they are all categorical (otherwise it is a parameter having n levels) and the λ jl OS are the (interesting) parameters describing the effect of subject characteristics (main effects or interaction terms between subject variables) on the preference value of object j.
TextSentencer_T117 16394-16503 Sentence denotes A second extension is to take into account the effects of object covariates on the preferences of the judges.
TextSentencer_T117 16394-16503 Sentence denotes A second extension is to take into account the effects of object covariates on the preferences of the judges.
TextSentencer_T118 16504-16659 Sentence denotes A common idea is to reparameterize the object parameters as a linear combination of P covariates X 1 ,…, X P , which represent P properties of the objects.
TextSentencer_T118 16504-16659 Sentence denotes A common idea is to reparameterize the object parameters as a linear combination of P covariates X 1 ,…, X P , which represent P properties of the objects.
TextSentencer_T119 16660-16783 Sentence denotes In order to incorporate object covariates the object-related parameters λ j O are replaced by the linear reparameterization
TextSentencer_T119 16660-16783 Sentence denotes In order to incorporate object covariates the object-related parameters λ j O are replaced by the linear reparameterization
TextSentencer_T120 16784-16920 Sentence denotes where the x jp 's denote the covariates describing the p-th property of the object j and the β p X 's are unknown regression parameters.
TextSentencer_T120 16784-16920 Sentence denotes where the x jp 's denote the covariates describing the p-th property of the object j and the β p X 's are unknown regression parameters.
TextSentencer_T121 16921-17074 Sentence denotes The log-linear representation of the Extended Bradley-Terry Model including the effects of one categorical subject covariate and one object covariate is:
TextSentencer_T121 16921-17074 Sentence denotes The log-linear representation of the Extended Bradley-Terry Model including the effects of one categorical subject covariate and one object covariate is:
TextSentencer_T122 17075-17119 Sentence denotes the other equations are defined analogously.
TextSentencer_T122 17075-17119 Sentence denotes the other equations are defined analogously.
TextSentencer_T123 17120-17366 Sentence denotes The EBTM is a multinomial log-linear model and thus a Generalized Linear Model (see, e.g., McCullagh and Nelder, 1999) and can be fitted using standard ML techniques with any software capable of computing log-linear models for contingency tables.
TextSentencer_T123 17120-17366 Sentence denotes The EBTM is a multinomial log-linear model and thus a Generalized Linear Model (see, e.g., McCullagh and Nelder, 1999) and can be fitted using standard ML techniques with any software capable of computing log-linear models for contingency tables.
TextSentencer_T124 17367-17527 Sentence denotes The 'overall utility' values correspond to the object parameters estimated for the two series of artificial trip packages, one for leisure and one for business.
TextSentencer_T124 17367-17527 Sentence denotes The 'overall utility' values correspond to the object parameters estimated for the two series of artificial trip packages, one for leisure and one for business.
TextSentencer_T125 17528-17662 Sentence denotes The part-worth utilities in conjoint terminology are related to the parameters of the object covariates (trip attributes) in the EBTM.
TextSentencer_T125 17528-17662 Sentence denotes The part-worth utilities in conjoint terminology are related to the parameters of the object covariates (trip attributes) in the EBTM.
TextSentencer_T126 17663-17780 Sentence denotes The parameters for the subject covariates show the influence of the traveler characteristics hypothesized in Fig. 1 .
TextSentencer_T126 17663-17780 Sentence denotes The parameters for the subject covariates show the influence of the traveler characteristics hypothesized in Fig. 1 .
TextSentencer_T127 17781-17862 Sentence denotes The model selection process commences with the object parameters for the packages
TextSentencer_T127 17781-17862 Sentence denotes The model selection process commences with the object parameters for the packages
TextSentencer_T128 17864-17961 Sentence denotes Separate parameter estimates were obtained for the two samples of leisure and business travelers.
TextSentencer_T128 17864-17961 Sentence denotes Separate parameter estimates were obtained for the two samples of leisure and business travelers.
TextSentencer_T129 17962-18014 Sentence denotes Consider the results for business first ( Table 2) .
TextSentencer_T129 17962-18014 Sentence denotes Consider the results for business first ( Table 2) .
TextSentencer_T130 18015-18359 Sentence denotes The object parameters describing the overall utility of the pre-designed packages range between .263 (for the 2 days' trip to Amsterdam/Brussels/Rome, business class, a five-star hotel, priced 642 Euro) and − .131 (for a 1 day trip to Prague/ Budapest/Munich, train first-class with sleeping compartment, five-star hotel, also priced 642 Euro).
TextSentencer_T130 18015-18359 Sentence denotes The object parameters describing the overall utility of the pre-designed packages range between .263 (for the 2 days' trip to Amsterdam/Brussels/Rome, business class, a five-star hotel, priced 642 Euro) and − .131 (for a 1 day trip to Prague/ Budapest/Munich, train first-class with sleeping compartment, five-star hotel, also priced 642 Euro).
TextSentencer_T131 18360-18555 Sentence denotes Note that the scaling is arbitrary and was determined by setting one object parameter to zero (viz. for the 2 days' trip to Amsterdam/Brussels/Rome by train 1st class, 5-star hotel, at 424 Euro).
TextSentencer_T131 18360-18555 Sentence denotes Note that the scaling is arbitrary and was determined by setting one object parameter to zero (viz. for the 2 days' trip to Amsterdam/Brussels/Rome by train 1st class, 5-star hotel, at 424 Euro).
TextSentencer_T132 18556-18714 Sentence denotes To disentangle the intricate pattern of part-worth utilities contributed by each trip attribute, the parameter estimates for the object covariates are needed.
TextSentencer_T132 18556-18714 Sentence denotes To disentangle the intricate pattern of part-worth utilities contributed by each trip attribute, the parameter estimates for the object covariates are needed.
TextSentencer_T133 18715-18752 Sentence denotes Table 3 and Fig. 2 show these values.
TextSentencer_T133 18715-18752 Sentence denotes Table 3 and Fig. 2 show these values.
TextSentencer_T134 18753-18912 Sentence denotes For each object covariate the value shows the difference to be gained by switching from the reference level to one of the other categories of a trip attribute.
TextSentencer_T134 18753-18912 Sentence denotes For each object covariate the value shows the difference to be gained by switching from the reference level to one of the other categories of a trip attribute.
TextSentencer_T135 18913-19013 Sentence denotes The attribute level not shown always represents a value of zero (i.e., mode: train/1st class; price:
TextSentencer_T135 18913-19013 Sentence denotes The attribute level not shown always represents a value of zero (i.e., mode: train/1st class; price:
TextSentencer_T136 19014-19033 Sentence denotes 424 €; destination:
TextSentencer_T136 19014-19033 Sentence denotes 424 €; destination:
TextSentencer_T137 19034-19077 Sentence denotes Prague, Budapest or Munich; length of stay:
TextSentencer_T137 19034-19077 Sentence denotes Prague, Budapest or Munich; length of stay:
TextSentencer_T138 19078-19091 Sentence denotes 1 day; hotel:
TextSentencer_T138 19078-19091 Sentence denotes 1 day; hotel:
TextSentencer_T139 19092-19098 Sentence denotes 4 ⁎ ).
TextSentencer_T139 19092-19098 Sentence denotes 4 ⁎ ).
TextSentencer_T140 19099-19282 Sentence denotes For example, changing the mode of transport from train/1st class (which is the zero base) to train/1st class with sleeping compartment (T1S) produces an insignif-icant value of .0298.
TextSentencer_T140 19099-19282 Sentence denotes For example, changing the mode of transport from train/1st class (which is the zero base) to train/1st class with sleeping compartment (T1S) produces an insignif-icant value of .0298.
TextSentencer_T141 19283-19425 Sentence denotes An economy class flight (EC) entails a preference effect of .239 and a business class seat (BC) generates .293, both of which are significant.
TextSentencer_T141 19283-19425 Sentence denotes An economy class flight (EC) entails a preference effect of .239 and a business class seat (BC) generates .293, both of which are significant.
TextSentencer_T142 19426-19466 Sentence denotes Recall that the values are in log scale.
TextSentencer_T142 19426-19466 Sentence denotes Recall that the values are in log scale.
TextSentencer_T143 19467-19522 Sentence denotes Thus, a meaningful comparison involves the odds ratios.
TextSentencer_T143 19467-19522 Sentence denotes Thus, a meaningful comparison involves the odds ratios.
TextSentencer_T144 19523-19715 Sentence denotes For example, the estimated odds of preferring EC vs. not preferring EC are exp(0.239) = 1.27 times higher than the estimated odds of preferring T1S (reference category) vs. not preferring T1S.
TextSentencer_T144 19523-19715 Sentence denotes For example, the estimated odds of preferring EC vs. not preferring EC are exp(0.239) = 1.27 times higher than the estimated odds of preferring T1S (reference category) vs. not preferring T1S.
TextSentencer_T145 19716-19859 Sentence denotes The practical importance of these changes may be assessed by comparing them with the consequence of a price increase (P6) from 424 to 642 Euro.
TextSentencer_T145 19716-19859 Sentence denotes The practical importance of these changes may be assessed by comparing them with the consequence of a price increase (P6) from 424 to 642 Euro.
TextSentencer_T146 19860-20085 Sentence denotes Such a rise in price exerts a negative effect of .030; so the impact on the overall attractiveness of the trip owing to a change from economy to business is roughly equivalent to a positive change for a price cut of 130 Euro.
TextSentencer_T146 19860-20085 Sentence denotes Such a rise in price exerts a negative effect of .030; so the impact on the overall attractiveness of the trip owing to a change from economy to business is roughly equivalent to a positive change for a price cut of 130 Euro.
TextSentencer_T147 20086-20211 Sentence denotes In the business travelers' mind sets the mode of transport clearly dominates the formation of preferences for a trip package.
TextSentencer_T147 20086-20211 Sentence denotes In the business travelers' mind sets the mode of transport clearly dominates the formation of preferences for a trip package.
TextSentencer_T148 20212-20330 Sentence denotes All the other components such as length of stay (2D), Hotel (5 ⁎ ) or destination category (AMS) exert less influence.
TextSentencer_T148 20212-20330 Sentence denotes All the other components such as length of stay (2D), Hotel (5 ⁎ ) or destination category (AMS) exert less influence.
TextSentencer_T149 20331-20446 Sentence denotes For the leisure travelers the packages including an economy class seat (#8, #3, and #6) achieve the highest values.
TextSentencer_T149 20331-20446 Sentence denotes For the leisure travelers the packages including an economy class seat (#8, #3, and #6) achieve the highest values.
TextSentencer_T150 20447-20532 Sentence denotes A bus or a train ride (unless lowest priced) seem to lead to poor overall (Table 4 ).
TextSentencer_T150 20447-20532 Sentence denotes A bus or a train ride (unless lowest priced) seem to lead to poor overall (Table 4 ).
TextSentencer_T151 20533-20652 Sentence denotes The parameter values for the object covariates again give more distinct guidance about the role of the trip attributes.
TextSentencer_T151 20533-20652 Sentence denotes The parameter values for the object covariates again give more distinct guidance about the role of the trip attributes.
TextSentencer_T152 20653-20725 Sentence denotes All the estimates in Table 5 and Fig. 3 have very small standard errors.
TextSentencer_T152 20653-20725 Sentence denotes All the estimates in Table 5 and Fig. 3 have very small standard errors.
TextSentencer_T153 20726-20840 Sentence denotes For the leisure travelers, too, the mode of transport most strongly acts on the assessment of a city trip package.
TextSentencer_T153 20726-20840 Sentence denotes For the leisure travelers, too, the mode of transport most strongly acts on the assessment of a city trip package.
TextSentencer_T154 20841-20978 Sentence denotes Switching from train 2nd class (T2) to an economy flight (EC) boosts the trip package more than twice as much as replacing train for bus.
TextSentencer_T154 20841-20978 Sentence denotes Switching from train 2nd class (T2) to an economy flight (EC) boosts the trip package more than twice as much as replacing train for bus.
TextSentencer_T155 20979-21159 Sentence denotes A variation of the package price is much more important in comparison with its effect among the business travelers (where only 10% had to pay for the trip out of their own pocket).
TextSentencer_T155 20979-21159 Sentence denotes A variation of the package price is much more important in comparison with its effect among the business travelers (where only 10% had to pay for the trip out of their own pocket).
TextSentencer_T156 21160-21248 Sentence denotes Again, the attribute categories not shown represent zero values (i.e., mode: bus; price:
TextSentencer_T156 21160-21248 Sentence denotes Again, the attribute categories not shown represent zero values (i.e., mode: bus; price:
TextSentencer_T157 21249-21268 Sentence denotes 258 €; destination:
TextSentencer_T157 21249-21268 Sentence denotes 258 €; destination:
TextSentencer_T158 21269-21312 Sentence denotes Prague, Budapest or Munich; length of stay:
TextSentencer_T158 21269-21312 Sentence denotes Prague, Budapest or Munich; length of stay:
TextSentencer_T159 21313-21321 Sentence denotes 2 days).
TextSentencer_T159 21313-21321 Sentence denotes 2 days).
TextSentencer_T160 21322-21493 Sentence denotes In the log-linear variant of the EBTM the relationships hypothesized in Fig. 1 are examined by analyzing the interaction terms involving the object and subject covariates.
TextSentencer_T160 21322-21493 Sentence denotes In the log-linear variant of the EBTM the relationships hypothesized in Fig. 1 are examined by analyzing the interaction terms involving the object and subject covariates.
TextSentencer_T161 21494-21572 Sentence denotes Only the main effects of each subject covariate on the objects are considered.
TextSentencer_T161 21494-21572 Sentence denotes Only the main effects of each subject covariate on the objects are considered.
TextSentencer_T162 21573-21712 Sentence denotes Recall, however, that a 'socio-economic status' variable was formed by combining the two observables 'level of education' and 'occupation'.
TextSentencer_T162 21573-21712 Sentence denotes Recall, however, that a 'socio-economic status' variable was formed by combining the two observables 'level of education' and 'occupation'.
TextSentencer_T163 21713-21833 Sentence denotes Table 6 lists the χ 2 values for the contingency tables supporting those main effects which survive the model selection.
TextSentencer_T163 21713-21833 Sentence denotes Table 6 lists the χ 2 values for the contingency tables supporting those main effects which survive the model selection.
TextSentencer_T164 21834-21979 Sentence denotes The χ 2 values give the differences of deviances (i.e. the likelihood-ratio tests) for the final model and a model without the respective effect.
TextSentencer_T164 21834-21979 Sentence denotes The χ 2 values give the differences of deviances (i.e. the likelihood-ratio tests) for the final model and a model without the respective effect.
TextSentencer_T165 21980-22252 Sentence denotes The substantial number of significant subject covariates demonstrates that the travelers are fairly heterogeneous in their assessing of a trip package and that the traveler characteristics proposed are appropriate for capturing quite a lot of this interpersonal variation.
TextSentencer_T165 21980-22252 Sentence denotes The substantial number of significant subject covariates demonstrates that the travelers are fairly heterogeneous in their assessing of a trip package and that the traveler characteristics proposed are appropriate for capturing quite a lot of this interpersonal variation.
TextSentencer_T166 22253-22457 Sentence denotes The summary tables in the Appendix report on the parameter estimates thus showing the strength of the influence of the traveler characteristics (values for level #1 of each subject covariate set to zero).
TextSentencer_T166 22253-22457 Sentence denotes The summary tables in the Appendix report on the parameter estimates thus showing the strength of the influence of the traveler characteristics (values for level #1 of each subject covariate set to zero).
TextSentencer_T167 22458-22555 Sentence denotes The socio-economic status (made up of education and occupation) proved to be an important factor.
TextSentencer_T167 22458-22555 Sentence denotes The socio-economic status (made up of education and occupation) proved to be an important factor.
TextSentencer_T168 22556-22698 Sentence denotes Judging from the parameter estimates it is particularly influential for the business travelers' perceived part-worth of the mode of transport.
TextSentencer_T168 22556-22698 Sentence denotes Judging from the parameter estimates it is particularly influential for the business travelers' perceived part-worth of the mode of transport.
TextSentencer_T169 22699-22821 Sentence denotes Each section of Fig. 4 exhibits the marginal means of the parameter estimates averaged over all other traveler covariates.
TextSentencer_T169 22699-22821 Sentence denotes Each section of Fig. 4 exhibits the marginal means of the parameter estimates averaged over all other traveler covariates.
TextSentencer_T170 22822-22904 Sentence denotes Fig. 4 (b) -(d), e.g., visualizes the combined effect of education and occupation.
TextSentencer_T170 22822-22904 Sentence denotes Fig. 4 (b) -(d), e.g., visualizes the combined effect of education and occupation.
TextSentencer_T171 22905-23041 Sentence denotes With [− .2, .4 ] these scales span a larger interval than the scales for age (a), general mode preference (e), or travel experience (f).
TextSentencer_T171 22905-23041 Sentence denotes With [− .2, .4 ] these scales span a larger interval than the scales for age (a), general mode preference (e), or travel experience (f).
TextSentencer_T172 23042-23234 Sentence denotes Clearly visible, the estimates for train/1st class plus sleeping compartment (marked with T1S), businesses (BC) and economy class (EC) vary significantly over the education/ occupation levels.
TextSentencer_T172 23042-23234 Sentence denotes Clearly visible, the estimates for train/1st class plus sleeping compartment (marked with T1S), businesses (BC) and economy class (EC) vary significantly over the education/ occupation levels.
TextSentencer_T173 23235-23369 Sentence denotes In terms of age only the 50+ travelers and regarding the general modal preference only the car lovers' reaction is slightly different.
TextSentencer_T173 23235-23369 Sentence denotes In terms of age only the 50+ travelers and regarding the general modal preference only the car lovers' reaction is slightly different.
TextSentencer_T174 23370-23562 Sentence denotes Fig. 5 summarizes the supported relationships proving that age and travel experience were overestimated in their expected influence on the business travelers' evaluation of city trip packages.
TextSentencer_T174 23370-23562 Sentence denotes Fig. 5 summarizes the supported relationships proving that age and travel experience were overestimated in their expected influence on the business travelers' evaluation of city trip packages.
TextSentencer_T175 23563-23691 Sentence denotes All part-worth utilities except 'hotel category' appear to be subject to the traveler's educational and occupational background.
TextSentencer_T175 23563-23691 Sentence denotes All part-worth utilities except 'hotel category' appear to be subject to the traveler's educational and occupational background.
TextSentencer_T176 23692-23878 Sentence denotes The part worths attached to the mode of transport and to the price level are more strongly influenced by traveler characteristics than are destination, hotel category, or length of stay.
TextSentencer_T176 23692-23878 Sentence denotes The part worths attached to the mode of transport and to the price level are more strongly influenced by traveler characteristics than are destination, hotel category, or length of stay.
TextSentencer_T177 23879-24022 Sentence denotes According to Table 7 there is a significant influence of the leisure travelers' personal characteristics on their valuation of trip attributes.
TextSentencer_T177 23879-24022 Sentence denotes According to Table 7 there is a significant influence of the leisure travelers' personal characteristics on their valuation of trip attributes.
TextSentencer_T178 24023-24134 Sentence denotes Again, the socio-economic status composed of education and occupation interferes with all part-worth utilities.
TextSentencer_T178 24023-24134 Sentence denotes Again, the socio-economic status composed of education and occupation interferes with all part-worth utilities.
TextSentencer_T179 24135-24285 Sentence denotes Unlike the business sub-sample, the leisure tourists' age is not only important for valuing the mode of transport, but impacts on all trip components.
TextSentencer_T179 24135-24285 Sentence denotes Unlike the business sub-sample, the leisure tourists' age is not only important for valuing the mode of transport, but impacts on all trip components.
TextSentencer_T180 24286-24509 Sentence denotes Turning to the strength of the interaction between the contribution of utility experienced from a trip attribute and the leisure travelers' characteristics Fig. 6 (a)-(g) demonstrates the effect of these subject covariates.
TextSentencer_T180 24286-24509 Sentence denotes Turning to the strength of the interaction between the contribution of utility experienced from a trip attribute and the leisure travelers' characteristics Fig. 6 (a)-(g) demonstrates the effect of these subject covariates.
TextSentencer_T181 24510-24583 Sentence denotes Level #1 of each object covariate again serves as the benchmark category.
TextSentencer_T181 24510-24583 Sentence denotes Level #1 of each object covariate again serves as the benchmark category.
TextSentencer_T182 24584-24856 Sentence denotes Comparing the scales for the education/occupation factor in (c)-(e) with the other single-criterion factors one recognizes a more diversified influence of the combined factor as the occupation groups show distinctly different patterns within each of the education classes.
TextSentencer_T182 24584-24856 Sentence denotes Comparing the scales for the education/occupation factor in (c)-(e) with the other single-criterion factors one recognizes a more diversified influence of the combined factor as the occupation groups show distinctly different patterns within each of the education classes.
TextSentencer_T183 24857-25005 Sentence denotes Hence, for the leisure travelers too, the socio-economic status emerges as a high-priority segmentation criterion when targeting city trip packages.
TextSentencer_T183 24857-25005 Sentence denotes Hence, for the leisure travelers too, the socio-economic status emerges as a high-priority segmentation criterion when targeting city trip packages.
TextSentencer_T184 25006-25033 Sentence denotes Age (a) is also noticeable.
TextSentencer_T184 25006-25033 Sentence denotes Age (a) is also noticeable.
TextSentencer_T185 25034-25146 Sentence denotes Car ownership (b), general mode preference (f), and even travel experience (g) generate less pronounced effects.
TextSentencer_T185 25034-25146 Sentence denotes Car ownership (b), general mode preference (f), and even travel experience (g) generate less pronounced effects.
TextSentencer_T186 25147-25510 Sentence denotes As a summary consider Fig. 7 which exhibits the modified model from the point of view of the leisure travelers. (Note that the hotel category was uniformly set to 4 stars, where the business travelers had 4 and 5 stars among their set of choice alternatives.) Two of the hypothesized relationships remained unconfirmed (experience → price; car ownership → price).
TextSentencer_T186 25147-25510 Sentence denotes As a summary consider Fig. 7 which exhibits the modified model from the point of view of the leisure travelers. (Note that the hotel category was uniformly set to 4 stars, where the business travelers had 4 and 5 stars among their set of choice alternatives.) Two of the hypothesized relationships remained unconfirmed (experience → price; car ownership → price).
TextSentencer_T187 25511-25708 Sentence denotes Not expected beforehand, the leisure tourists as well as their business counterparts seem to make their evaluation of an urban destination dependent on a general preference for a mode of transport.
TextSentencer_T187 25511-25708 Sentence denotes Not expected beforehand, the leisure tourists as well as their business counterparts seem to make their evaluation of an urban destination dependent on a general preference for a mode of transport.
TextSentencer_T188 25709-25862 Sentence denotes The major difference regarding subject covariates occurs for age, which plays a prominent role for leisure while staying largely irrelevant for business.
TextSentencer_T188 25709-25862 Sentence denotes The major difference regarding subject covariates occurs for age, which plays a prominent role for leisure while staying largely irrelevant for business.
TextSentencer_T189 25863-26034 Sentence denotes The research findings provide evidence that business and leisure travelers make different assessments of the trip product elements bundled together in a city trip package.
TextSentencer_T189 25863-26034 Sentence denotes The research findings provide evidence that business and leisure travelers make different assessments of the trip product elements bundled together in a city trip package.
TextSentencer_T190 26035-26180 Sentence denotes Moreover, both groups are internally heterogeneous regarding their assessments and a number of covariates seem to account for this heterogeneity.
TextSentencer_T190 26035-26180 Sentence denotes Moreover, both groups are internally heterogeneous regarding their assessments and a number of covariates seem to account for this heterogeneity.
TextSentencer_T191 26181-26268 Sentence denotes Pondering on the empirical results one must not overlook the limitations of this study.
TextSentencer_T191 26181-26268 Sentence denotes Pondering on the empirical results one must not overlook the limitations of this study.
TextSentencer_T192 26269-26452 Sentence denotes There are geographical and temporal restrictions, and, not to forget, the sample consists of air travelers; so one cannot expect a balanced view of the alternative modes of transport.
TextSentencer_T192 26269-26452 Sentence denotes There are geographical and temporal restrictions, and, not to forget, the sample consists of air travelers; so one cannot expect a balanced view of the alternative modes of transport.
TextSentencer_T193 26453-26613 Sentence denotes An equivalent survey sponsored by rail and bus for their passengers would be desirable to learn about the bias provoked by the respective consumption situation.
TextSentencer_T193 26453-26613 Sentence denotes An equivalent survey sponsored by rail and bus for their passengers would be desirable to learn about the bias provoked by the respective consumption situation.
TextSentencer_T194 26614-26796 Sentence denotes One may rightly expect such a bias as the general preference for a mode of transport turned out to influence the assessment of the trip components mode and price in both sub-samples.
TextSentencer_T194 26614-26796 Sentence denotes One may rightly expect such a bias as the general preference for a mode of transport turned out to influence the assessment of the trip components mode and price in both sub-samples.
TextSentencer_T195 26797-26894 Sentence denotes The present study does not claim to confirm an explanatory model of city trip package evaluation.
TextSentencer_T195 26797-26894 Sentence denotes The present study does not claim to confirm an explanatory model of city trip package evaluation.
TextSentencer_T196 26895-26996 Sentence denotes The analysis follows a model selection scheme guided by an initial set of hypothesized relationships.
TextSentencer_T196 26895-26996 Sentence denotes The analysis follows a model selection scheme guided by an initial set of hypothesized relationships.
TextSentencer_T197 26997-27022 Sentence denotes The final versions (Figs.
TextSentencer_T197 26997-27022 Sentence denotes The final versions (Figs.
TextSentencer_T198 27023-27281 Sentence denotes 5 and 7) result from a series of likelihood ratio tests gradually simplifying the model by removing nonsignificant (p N 0.05) subject effects (i.e. subject main effects ⁎ objects covariates interactions) as common practice in backward-elimination strategies.
TextSentencer_T198 27023-27281 Sentence denotes 5 and 7) result from a series of likelihood ratio tests gradually simplifying the model by removing nonsignificant (p N 0.05) subject effects (i.e. subject main effects ⁎ objects covariates interactions) as common practice in backward-elimination strategies.
TextSentencer_T199 27282-27400 Sentence denotes The versions surviving the model selection process would have to be exposed to new data for being conclusively tested.
TextSentencer_T199 27282-27400 Sentence denotes The versions surviving the model selection process would have to be exposed to new data for being conclusively tested.
TextSentencer_T200 27401-27500 Sentence denotes Working on the contingency tables the EBTM as all log-linear models requires a fairly large sample.
TextSentencer_T200 27401-27500 Sentence denotes Working on the contingency tables the EBTM as all log-linear models requires a fairly large sample.
TextSentencer_T201 27501-27616 Sentence denotes There were not plenty of cases in this study, therefore, making provision for a hold-out sample was not considered.
TextSentencer_T201 27501-27616 Sentence denotes There were not plenty of cases in this study, therefore, making provision for a hold-out sample was not considered.
TextSentencer_T202 27617-27704 Sentence denotes Despite of all these caveats there are a few lessons to learn for future hypothesizing.
TextSentencer_T202 27617-27704 Sentence denotes Despite of all these caveats there are a few lessons to learn for future hypothesizing.
TextSentencer_T203 27705-27899 Sentence denotes With so much emphasis on the marketing of destinations the importance of the mode of transport may have been underrated until the market success of the low-cost carriers began to tell otherwise.
TextSentencer_T203 27705-27899 Sentence denotes With so much emphasis on the marketing of destinations the importance of the mode of transport may have been underrated until the market success of the low-cost carriers began to tell otherwise.
TextSentencer_T204 27900-28045 Sentence denotes On the other hand, tour operators have always offered a set of catalogues sorted by the means of transport (city flights, rail tours, bus tours).
TextSentencer_T204 27900-28045 Sentence denotes On the other hand, tour operators have always offered a set of catalogues sorted by the means of transport (city flights, rail tours, bus tours).
TextSentencer_T205 28046-28096 Sentence denotes This seems natural for predetermined modal choice.
TextSentencer_T205 28046-28096 Sentence denotes This seems natural for predetermined modal choice.
TextSentencer_T206 28097-28261 Sentence denotes But, at second glance, it does not facilitate the traveler's understanding of a higher price due to the value-enhancing function of transport speed and convenience.
TextSentencer_T206 28097-28261 Sentence denotes But, at second glance, it does not facilitate the traveler's understanding of a higher price due to the value-enhancing function of transport speed and convenience.
TextSentencer_T207 28262-28411 Sentence denotes Finally, socio-economic status (for business and leisure) and age (for leisure only) should be among the candidates for market segmentation criteria.
TextSentencer_T207 28262-28411 Sentence denotes Finally, socio-economic status (for business and leisure) and age (for leisure only) should be among the candidates for market segmentation criteria.
TextSentencer_T208 28412-28504 Sentence denotes These characteristics seem to act on the assessment of all components in the product bundle.
TextSentencer_T208 28412-28504 Sentence denotes These characteristics seem to act on the assessment of all components in the product bundle.
TextSentencer_T209 28505-28662 Sentence denotes In terms of methodology the EBTM proved its ability of handling fairly complex systems of relationships involving rating data and many categorical variables.
TextSentencer_T209 28505-28662 Sentence denotes In terms of methodology the EBTM proved its ability of handling fairly complex systems of relationships involving rating data and many categorical variables.
TextSentencer_T210 28663-28754 Sentence denotes One tempting refinement of the methodology relates to the order information in the ratings.
TextSentencer_T210 28663-28754 Sentence denotes One tempting refinement of the methodology relates to the order information in the ratings.
TextSentencer_T211 28755-28920 Sentence denotes The transforming of the observed ratings into paired comparisons ignores the number of rating points stretching between a respondent's judgments of two alternatives.
TextSentencer_T211 28755-28920 Sentence denotes The transforming of the observed ratings into paired comparisons ignores the number of rating points stretching between a respondent's judgments of two alternatives.
TextSentencer_T212 28921-29061 Sentence denotes At least ordinal information may hide behind these differences and may remain unexploited after the downgrading of the level of measurement.
TextSentencer_T212 28921-29061 Sentence denotes At least ordinal information may hide behind these differences and may remain unexploited after the downgrading of the level of measurement.
TextSentencer_T213 29062-29207 Sentence denotes Actually, the EBTM lends itself for further extensions that account for the rank differences in the preference data (cf. Dittrich et al., 2004) .
TextSentencer_T213 29062-29207 Sentence denotes Actually, the EBTM lends itself for further extensions that account for the rank differences in the preference data (cf. Dittrich et al., 2004) .
TextSentencer_T214 29208-29328 Sentence denotes Tentatively, this was tried for the present data set and no remarkable effects on the parameter estimates were detected.
TextSentencer_T214 29208-29328 Sentence denotes Tentatively, this was tried for the present data set and no remarkable effects on the parameter estimates were detected.
TextSentencer_T215 29329-29383 Sentence denotes But this is another story pointing to future research.
TextSentencer_T215 29329-29383 Sentence denotes But this is another story pointing to future research.
TextSentencer_T216 29384-29427 Sentence denotes Levels of the subject covariates (business)
TextSentencer_T216 29384-29427 Sentence denotes Levels of the subject covariates (business)
TextSentencer_T217 29428-29599 Sentence denotes Travel experience (# of trips) 1) Some high-school N = 54 1) b=1 N = 122 2) high-school N = 137 2) 4-9 Parameter estimates for the object-subject interactions (business) (
TextSentencer_T217 29428-29599 Sentence denotes Travel experience (# of trips) 1) Some high-school N = 54 1) b=1 N = 122 2) high-school N = 137 2) 4-9 Parameter estimates for the object-subject interactions (business) (