CN104850903A - Construction and budget method of local tourism popularity index - Google Patents

Abstract

The invention provides a construction and budget method of a local tourism popularity index. The method comprises the following steps of (1) obtaining the index of tourism popularity by visitors, (2) building a structural equation model according to the index of tourism popularity, wherein the structural equation model is obtained through a covariance structure analysis method based on maximum likelihood estimation or a variance analysis method based on partial least squares regression, and (3) carrying out budgeting according to the structural equation model. Through the method, an effective model for measuring investment and production is realized, and a good budget effect is achieved for promoting visitors to go to a destination for tourism and adding visitor tourism desire by a brand equity element.

Description

A kind of method of local tourism popularity index construction and budget

Technical field

The present invention relates to the technical field of tourism index, be specifically related to a kind of method of local tourism popularity index construction and budget.

Background technology

Since 1890s, brand assets (Brand Equity) has become major issue (Aaker, 1991,1996 based on Perspective of Customers research marketing performance; Keller, 1993; Kim & Kim, 2005; Srivastava & Shocker, 1991; Yoo & Donthu, 2001).Meanwhile, brand assets has become the key factor (Bailey & Ball, 2006 that promote the market competitiveness and differentiated marketing strategies; Boo, Busser & Baloglu, 2009; Chang & Liu, 2009).In tourism destination research field, some scholars point out that tourist famous-city brand assets weighs important channel and brand-new visual angle (Camarero et al., 2010 of tourism destination performance; Kone_cnik & Gartner, 2007; Williams et al., 2004; Woodside, et al., 2007).

Due to the singularity of destination product, destination brand is by the restriction of geographic name, and in general, destination brand name is equal to geographic name, and therefore, the brand assets based on consumer reflects the cognition of traveller to destination.Brand assets based on consumer comprises the dimensions such as brand loyalty, perceived value, brand image, brand conspicuousness, brand strength, brand recognition, brand recognition equals brand conspicuousness, brand strength equals brand image to have scholar to think, is the different expression of same dimension.To the relation between each dimension of destination brand assets, scholars generally set up by theory and applying the model be made up of some variablees, and then are verified the relation between model and each dimension by real example collection data.

When measuring the brand assets based on consumer, brand (destination) popularity research will determine the position that destination is residing in cognitive level, crucial will identification is positioned at the first destination of consciousness cognition, decision domain formation and behavior intention, measures by design open-ended question; Brand (destination) association is the consistance between brand body and brand image, in order to measure the impact that location strategy is formed the desirable brand strength in destination, a series of quantitative and qualitative analysis measuring method can be taked, it is more that relevant brand image surveys quantifier elimination, and scale is relative maturity also; Perceived value, namely to the perception of destination quality and price, measures destination traveller and non-traveller and whether feels destination product price is worthwhile (value for money); Brand (destination) is loyal, mainly through oral marketing with revisit two indices and measure, owing to keeping old traveller lower than the cost obtaining new traveller, when the funds of marketing are limited, destination values the value of traveller's loyalty more.

To in the measurement of brand assets, Yoo and Donthu (2001) demonstrates the reliability of brand assets survey instrument, thinks that brand assets extends to brand loyalty, perceived quality and brand image.In all travel literatures, brand assets is generally weighed by three different angles: the angle (Kim & Kim, 2005) of the angle based on client, the angle based on finance and mixing.According to reported literature, researcher generally studies (Aaker, 1991 to this four dimensions of brand assets, brand image, perceived quality and brand loyalty in document before; Kone_cnik & Gartner, 2007; Yoo & Donthu, 2001).At present, domestic a lot of local government drops into a large amount of man power and materials, to promote the development of local inbound tourism.But also lack one at present and weigh the valid model of input-output ratio, therefore, research brand assets key element is gone to destination to travel and is increased the effect that visitor travels in wish and just seem particularly important promoting visitor.

Summary of the invention

The object of this invention is to provide a kind of method of local tourism popularity index construction and budget, to overcome prior art above shortcomings.

The object of the invention is to be achieved through the following technical solutions:

A method for local tourism popularity index construction and budget, comprises the steps:

S1, obtains the index of visitor to tourism popularity;

S2, the index according to tourism popularity builds structural equation model; Structural equation model is based on the analysis of covariance structures method of maximal possibility estimation by a kind of or obtained based on the method for analysis of variance of partial least squares regression;

S3, carries out budget according to described structural equation model.

Preferably, when described tourist information comprises immigration tourist information;

Described tourist famous-city information comprises social condition, accidental factor, awareness degree, familiarity, perceived quality and tourism loyalty;

Described social context is the social environmental factor of tourist famous-city;

Described social environmental factor comprises tourist area politics, tourist area economy and tourist area cultural environment;

Described accidental factor comprises the tourist famous-city major event occurring/hold and object disaster factors of travelling;

Described awareness degree comprises tourist to China and knows the degree whether tourist famous-city exist;

Described familiarity comprises the familiarity of tourist to China to tourist famous-city;

Described perceived quality comprises the actual perceived level of tourist to China to the service quality in tourism that tourist famous-city provides;

Described tourism loyalty comprises tourist to China in tourism purchase decision, shows the behavior reaction a certain tourist famous-city being had to skewed popularity at least one times;

Described social context and described accidental factor are as the exogenous variable of tourist to China local tourism popularity index basis measurement model;

Described awareness degree, described familiarity, described perceived quality and described tourism loyalty are as the endogenous variable of tourist to China local tourism popularity index basis measurement model;

Tourist to China local tourism popularity index is divided into three levels, and the first level index is made up of latent variable; Second level index is made up of the measurand of latent variable; Third layer time index is made up of the segmentation evaluation index of measurand; Measurand is tourist resources; Tourist resources comprises tourist communications, tourist catering and tourist lodging;

Described social context, described accidental factor, described awareness degree, described familiarity and described perceived quality are as the input variable of the described tourism loyalty of impact; Described tourism loyalty is as output variable;

Described awareness degree, described perceived quality and described familiarity and described tourism loyalty correlation;

Under identical awareness degree or perceived quality, if familiarity is higher, then tourist to China tourism loyalty is higher.

Be more preferably, adopt PLS estimation technique to set up to tourist to China local tourism popularity index basis measurement model, the tourist to China local tourism popularity exponential model of foundation is by the offset minimum binary SIMCA-P process by specialty.

Be more preferably, be linear weighted function relation between hypothesized model structure variable and between structure variable and measurand, be one group of linear structural equation by model specification, specifically comprise two submodels, one is latent variable model or structural model, for the relation between description scheme variable; One is measurement model, for describing the relation between latent variable and measurand.

Be more preferably, the mathematical form of structural model is abbreviated as:

η＝Bη+Γξ+ζ；

In overseas Simulation local tourism popularity exponential model, η represents awareness degree, degree of recognition, familiarity and tourism wish.And in immigration model, η represents awareness degree, perceived quality, familiarity and tourism loyalty;

Structure variable model expands into:

$\left(\begin{array}{c}{\mathrm{\η}}_1\\ {\mathrm{\η}}_2\\ {\mathrm{\η}}_5\\ {\mathrm{\η}}_6\end{array}\right)=\left\{\begin{array}{cccc}0& 0& 0& 0\\ {{\mathrm{\β}}_{21}}^{*}& 0& {\mathrm{\β}}_{25}& 0\\ {\mathrm{\β}}_{51}& 0& 0& 0\\ {\mathrm{\β}}_{61}& {\mathrm{\β}}_{62}& {\mathrm{\β}}_{65}& 0\end{array}\right)*\left(\begin{array}{c}{\mathrm{\η}}_1\\ {\mathrm{\η}}_2\\ {\mathrm{\η}}_5\\ {\mathrm{\η}}_6\end{array}\right)+\left(\begin{array}{cc}{{\mathrm{\γ}}_{11}}^{*}& {{\mathrm{\γ}}_{12}}^{*}\\ {{\mathrm{\γ}}_{21}}^{*}& {{\mathrm{\γ}}_{22}}^{*}\\ {\mathrm{\γ}}_{51}& {\mathrm{\γ}}_{52}\\ 0& 0\end{array}\right)*\left(\begin{array}{c}{\mathrm{\ξ}}_1\\ {\mathrm{\ξ}}_2\end{array}\right)+\left(\begin{array}{c}{{\mathrm{\ζ}}_1}^{*}\\ {{\mathrm{\ζ}}_2}^{*}\\ {\mathrm{\ζ}}_5\\ {\mathrm{\ζ}}_6\end{array}\right);$

Measurand model expands into:

Measurand model expands into:

$\left(\begin{array}{c}{x}_1\\ x_2\\ .\\ .\\ .\\ x_7\\ x_8\\ x_9\end{array}\right)=\left(\begin{array}{cc}{{\mathrm{\λ}}_{x11}}^{*}& 0\\ {{\mathrm{\λ}}_{x21}}^{*}& 0\\ .& .\\ .& .\\ .& .\\ {{\mathrm{\λ}}_{x71}}^{*}& 0\\ 0& {{\mathrm{\λ}}_{x82}}^{*}\\ 0& {{\mathrm{\λ}}_{x92}}^{*}\end{array}\right)*\left(\begin{array}{c}{\mathrm{\ξ}}_1\\ {\mathrm{\ξ}}_2\end{array}\right)+\left(\begin{array}{c}{{\mathrm{\δ}}_1}^{*}\\ {{\mathrm{\δ}}_2}^{*}\\ {{\mathrm{\δ}}_3}^{*}\\ {{\mathrm{\δ}}_4}^{*}\\ {{\mathrm{\δ}}_5}^{*}\\ {{\mathrm{\δ}}_6}^{*}\end{array}\right);$

$\left(\begin{array}{c}{y}_1\\ .\\ .\\ .\\ y_7\\ y_{11}\\ .\\ .\\ .\\ y_{19}\\ y_{23}\\ y_{24}\end{array}\right)=\left(\begin{array}{cccc}{\mathrm{\λ}}_{y11}& 0& 0& 0\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ 0& {\mathrm{\λ}}_{y72}& 0& 0\\ 0& 0& {\mathrm{\λ}}_{y115}& 0\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ 0& 0& {\mathrm{\λ}}_{y195}& 0\\ 0& 0& 0& {\mathrm{\λ}}_{y236}\\ 0& 0& 0& {\mathrm{\λ}}_{y246}\end{array}\right)=\left(\begin{array}{c}{\mathrm{\η}}_1\\ {\mathrm{\η}}_2\\ {\mathrm{\η}}_5\\ {\mathrm{\η}}_6\end{array}\right)+\left(\begin{array}{c}{\mathrm{\ϵ}}_1\\ {\mathrm{\ϵ}}_2\\ {\mathrm{\ϵ}}_3\\ .\\ .\\ .\\ {\mathrm{\ϵ}}_{21}\\ {\mathrm{\ϵ}}_{22}\\ {\mathrm{\ϵ}}_{23}\end{array}\right).$

Be more preferably, described tourist information comprise overseas Simulation information time; Then definition structure variable, is specially:

Social context refers to the social environmental factor of tourist famous-city;

Awareness degree refers to the degree that overseas Simulation is known tourist famous-city and whether existed;

Familiarity refers to that Simulation is to the familiarity of tourist famous-city overseas;

Degree of recognition refers to the overseas Simulation degree to the good opinion of tourist famous-city, trust, receiving;

Tourism wish refers to that Simulation buys the wish degree of a certain ground travelling products;

There is following relation between variable: the index system of Simulation local tourism popularity index is divided into two each and every one levels overseas, the first level index is made up of latent variable; Second level index is made up of the measurand of latent variable;

According to the cause-effect relationship principle of overseas Simulation local tourism popularity measurement model, in the first level index, social context, accidental factor, awareness degree, degree of recognition and familiarity five variablees affect the tourism wish of Simulation, it is the input variable of model, also referred to as prerequisite variable, and the tourism wish of Simulation is output variable, be also called outcome variable.Prerequisite variable and outcome variable, all there is complicated correlationship between prerequisite variable and between outcome variable, these correlationships carry out detailed analysis & verification by calculation using models;

Prerequisite variable determination result variable; Social context, accidental factor, awareness degree, degree of recognition and familiarity directly/affect indirectly the tourism wish of Simulation; Awareness degree, degree of recognition and familiarity and overseas Simulation are traveled wish correlation, and awareness degree, degree of recognition, familiarity index are higher, and the tourism wish of visitor is stronger; Meanwhile, familiarity also plays partial intermediary effect in awareness degree with degree of recognition impact tourism wish: under identical awareness degree or degree of recognition situation, the familiarity of visitor to tourist famous-city is higher, then the wish going to the tourism of this ground is stronger;

Also correlativity is there is between each prerequisite variable.Awareness degree and degree of recognition, degree of recognition and familiarity, between awareness degree and familiarity, all there is positive correlation; Higher awareness degree can produce high degree of recognition; High degree of recognition and awareness degree can produce high familiarity; In addition, awareness degree, degree of recognition and familiarity are subject to the impact of exogenous variable social context, accidental factor.

Be more preferably, overseas Simulation local tourism popularity index basis measurement model adopts PLS estimation technique to set up, and the Simulation popularity exponential model of foundation is by the offset minimum binary SIMCA-P process by specialty.

Be more preferably, be linear weighted function relation between hypothesized model structure variable and between structure variable and measurand, consider measuring error factor, it is one group of linear structural equation by model specification, specifically comprise two submodels, one is latent variable model or structural model, for the relation between description scheme variable; One is measurement model, for describing the relation between latent variable and measurand.

Be more preferably, the mathematical form of structural model is abbreviated as:

η＝Bη+Γξ+ζ；

In structure variable, social context and accidental factor are exogenous variables, are represented by ξ; Awareness degree, degree of recognition, familiarity and tourism wish are endogenous variables, are represented by η.B, Γ are respectively the construction coefficient matrix of η and ξ, and ζ is the error vector of structure variable model;

Structure variable model expands into:

$\left(\begin{array}{c}{\mathrm{\η}}_1\\ {\mathrm{\η}}_2\\ {\mathrm{\η}}_3\\ {\mathrm{\η}}_4\end{array}\right)=\left\{\begin{array}{cccc}0& 0& 0& 0\\ {\mathrm{\β}}_{21}& 0& {\mathrm{\β}}_{23}& 0\\ {\mathrm{\β}}_{31}& 0& 0& 0\\ {\mathrm{\β}}_{41}& {\mathrm{\β}}_{42}& {\mathrm{\β}}_{43}& 0\end{array}\right)*\left(\begin{array}{c}{\mathrm{\η}}_1\\ {\mathrm{\η}}_2\\ {\mathrm{\η}}_3\\ {\mathrm{\η}}_4\end{array}\right)+\left(\begin{array}{cc}{\mathrm{\γ}}_{11}& {\mathrm{\γ}}_{12}\\ {\mathrm{\γ}}_{21}& {\mathrm{\γ}}_{22}\\ {\mathrm{\γ}}_{31}& {\mathrm{\γ}}_{32}\\ 0& 0\end{array}\right)*\left(\begin{array}{c}{\mathrm{\ξ}}_1\\ {\mathrm{\ξ}}_2\end{array}\right)+\left(\begin{array}{c}{\mathrm{\ζ}}_1\\ {\mathrm{\ζ}}_2\\ {\mathrm{\ζ}}_3\\ {\mathrm{\ζ}}_4\end{array}\right);$

The mathematical form of measurand model is abbreviated as:

x＝Λ _xξ+δ；

y＝Λ _yη+ε；

X, y are respectively raw observational variable vector in external observational variable vector sum, Λ _x, Λ _yrespectively represent x to ξ's and y to the regression coefficient matrix of η, i.e. matrix of loadings;

Measurand model expands into:

$\left(\begin{array}{c}{x}_1\\ x_2\\ .\\ .\\ .\\ x_7\\ x_8\\ x_9\end{array}\right)=\left(\begin{array}{cc}{\mathrm{\λ}}_{x11}& 0\\ {\mathrm{\λ}}_{x21}& 0\\ .& .\\ .& .\\ .& .\\ {\mathrm{\λ}}_{x71}& 0\\ 0& {\mathrm{\λ}}_{x82}\\ 0& {\mathrm{\λ}}_{x92}\end{array}\right)*\left(\begin{array}{c}{\mathrm{\ζ}}_1\\ {\mathrm{\ζ}}_2\end{array}\right)+\left(\begin{array}{c}{\mathrm{\δ}}_1\\ {\mathrm{\δ}}_2\\ {\mathrm{\δ}}_3\\ {\mathrm{\δ}}_4\\ {\mathrm{\δ}}_5\\ {\mathrm{\δ}}_6\end{array}\right);$

$\left(\begin{array}{c}{y}_1\\ y_2\\ y_3\\ .\\ .\\ .\\ y_{10}\\ y_{20}\\ y_{21}\\ y_{22}\end{array}\right)=\left(\begin{array}{cccc}{\mathrm{\λ}}_{y11}& 0& 0& 0\\ {\mathrm{\λ}}_{y21}& 0& 0& 0\\ {\mathrm{\λ}}_{y31}& 0& 0& 0\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ \text{0}& 0& {\mathrm{\λ}}_{y103}& 0\\ 0& 0& 0& {\mathrm{\λ}}_{y204}\\ 0& 0& 0& {\mathrm{\λ}}_{y214}\\ 0& 0& 0& {\mathrm{\λ}}_{y224}\end{array}\right)*\left(\begin{array}{c}{\mathrm{\η}}_1\\ {\mathrm{\η}}_2\\ {\mathrm{\η}}_3\\ {\mathrm{\η}}_4\end{array}\right)+\left(\begin{array}{c}{\mathrm{\ϵ}}_1\\ {\mathrm{\ϵ}}_2\\ {\mathrm{\ϵ}}_3\\ .\\ .\\ .\\ {\mathrm{\ϵ}}_{21}\\ {\mathrm{\ϵ}}_{22}\\ {\mathrm{\ϵ}}_{23}\end{array}\right).$

Wherein, described PLS is partial least square method, is a kind of mathematical optimization techniques, and it finds the optimal function of one group of data to mate by the quadratic sum of minimum error.Try to achieve some absolute unknowable true value by the simplest method, and make square-error sum be minimum.Be generally used for curve.Much other optimization problem is also expressed by minimization of energy or maximization entropy least squares formalism.

Wherein, described soft sim CA-P is the mathematical statistics analysis software calculating partial least square method, the UMETRICS company created for Wood and his co-workers developed in 1987, the data analysis software run under windows, explained in order to the calculating and result supporting partial least squares regression.

Beneficial effect of the present invention is:

Realize weighing the valid model of input-output ratio by the present invention, brand assets key element is gone to destination to travel and increased visitor and travel and play good budget effect in wish promoting visitor.

Accompanying drawing explanation

Fig. 1 is that market study local tourism popularity index of the present invention forms schematic diagram;

Fig. 2 is the local tourism of Simulation overseas popularity construction of indexes model latus rectum figure of the present invention;

Fig. 3 is tourist to China local tourism popularity construction of indexes model latus rectum figure of the present invention.

Embodiment

As Figure 1-3 for the present invention realizes a kind of method of local tourism popularity index construction and budget, specifically to be described in conjunction with following embodiment: local tourism popularity index is measured from many aspects, wherein, the core that market study local tourism popularity index is whole model is built.According to domestic and international pertinent literature, larger difference is there is in tourist to China and overseas Simulation to the cognitive assessment of local tourism popularity, therefore, this research is carried out measuring process from visitor visual angle to local tourism popularity, will from tourist to China and overseas Simulation two dimensions, adopt two different measurement models to measure respectively.Wherein, from immigration team visitor and immigration individual traveler, tourist to China is measured respectively.Market study local tourism popularity index is formed as shown in Figure 1;

(1), overseas Simulation local tourism popularity index

1. model variable

Overseas Simulation local tourism popularity index basis measurement model is made up of social context, accidental factor, awareness degree, degree of recognition, familiarity and tourism wish 6 variablees.

1.1 defining variable

The definition of 6 structure variables: social context refers to the social environmental factor of tourist famous-city, as somewhere politics, economy, cultural environment etc.; Accidental factor refers to major event, disaster etc. that tourist famous-city occurs/holds; Awareness degree refers to the degree that overseas Simulation is known tourist famous-city and whether existed; Familiarity refers to that Simulation is to the familiarity of tourist famous-city overseas; Degree of recognition refers to the overseas Simulation degree to the good opinion of tourist famous-city, trust, receiving; Tourism wish refers to that Simulation buys the wish degree of a certain ground travelling products.

Distinguish endogenous variable and exogenous variable: social context and accidental factor are the exogenous variables of Simulation local tourism popularity index basis measurement model overseas, and awareness degree, familiarity, degree of recognition, tourism wish are its endogenous variables.

Relation between 1.2 variablees

Overseas the index system of Simulation local tourism popularity index is divided into two each and every one levels, and the first level index is made up of latent variable; Second level index is made up of the measurand of latent variable.

According to the cause-effect relationship principle of overseas Simulation local tourism popularity measurement model, in the first level index, social context, accidental factor, awareness degree, degree of recognition and familiarity five variablees affect the tourism wish of Simulation, it is the input variable of model, also referred to as prerequisite variable, and the tourism wish of Simulation is output variable, be also called outcome variable.Prerequisite variable and outcome variable, all there is complicated correlationship between prerequisite variable and between outcome variable, these correlationships carry out detailed analysis & verification by calculation using models.

Prerequisite variable determination result variable.Social context, accidental factor, awareness degree, degree of recognition and familiarity directly/affect indirectly the tourism wish of Simulation.Awareness degree, degree of recognition and familiarity and overseas Simulation are traveled wish correlation, and awareness degree, degree of recognition, familiarity index are higher, and the tourism wish of visitor is stronger.Meanwhile, familiarity also plays partial intermediary effect in awareness degree with degree of recognition impact tourism wish: under identical awareness degree or degree of recognition situation, the familiarity of visitor to tourist famous-city is higher, then the wish going to the tourism of this ground is stronger.

Also correlativity is there is between each prerequisite variable.Awareness degree and degree of recognition, degree of recognition and familiarity, between awareness degree and familiarity, all there is positive correlation.Higher awareness degree can produce high degree of recognition; High degree of recognition and awareness degree can produce high familiarity.In addition, awareness degree, degree of recognition and familiarity are subject to the impact of exogenous variable social context, accidental factor.

2. model latus rectum figure

According to the relation between structure variable, overseas the latus rectum figure of Simulation local tourism popularity index (TAI-P) structural model is as shown in Figure 2,

Ellipse represents a structure variable, and the line between two structure variables represents between them and has cause-effect relationship, and arrow represents causal direction.γ, β are path coefficient, raw dependent variable in first subscript mark of path coefficient, and second subscript mark causal variable, when causal variable is exogenous variable, represents with γ; When causal variable is another endogenous variable, then represent with β.

3. assessment indicator system

With reference to external top tourism academic journal " Annals of Tourism Research ", " Tourism Management ", " Journal of Travel Research ", " International Marketing Review " etc. in recent years publish about tourism destination performance appraisal (METDM, Measuring the Effective of Tourism Destination Marketing), tourist famous-city brand assets (TDBE, Tourism Destination Brand Equity), based on the brand assets (CBBE at visitor visual angle, Consumer-based Brand Equity) etc. the classical documents of aspect (as Konecnik and Gartner, 2007, Boo et al., 2009, Pike, 2010 etc.), and in conjunction with domestic and international tourist famous-city popularity, tourism destination performance appraisal experience, three Hierarchy indicataors system of the local tourism popularity index of Simulation overseas, in table 1.

Local tourism popularity index three grades of index systems guide look of table 1 overseas Simulation

4. model is estimated

At present, two large class estimation techniques are mainly contained to build structural equation model.Be the analysis of covariance structures method based on maximal possibility estimation, be often called as " die type " (hard modeling), with LISREL method for representative; Another kind is the method for analysis of variance based on partial least squares regression, is called as " soft model " (soft modeling), with PLS method for representative.

At present, although the model that Simulation local tourism popularity index is overseas studied in the whole world is not quite similar, deflected secondary air (PLS) is mostly adopted to carry out Modling model.Because the object utilizing PLS modeling method to carry out the research of local tourism popularity obtains Simulation local tourism popularity index overseas, understand the mutual relationship of each variable in model, and finally obtain Simulation local tourism popularity index overseas, LISREL method requires that measurand meets and obeys multivariate normal distribution and separate harsh conditions, and the measurand of popularity index Questionaire is difficult to meet these harsh conditions, overseas the theory of Simulation local tourism popularity index is ripe not enough simultaneously, therefore the experience of various countries is considered, the object of research and the condition restriction of each side, overseas Simulation local tourism popularity index basis measurement model adopts PLS estimation technique to set up, the Simulation popularity exponential model set up is by the offset minimum binary soft sim CA-P process by specialty.

5, model mathematical form

Be linear weighted function relation between hypothesized model structure variable and between structure variable and measurand, consider measuring error factor, it is one group of linear structural equation by model specification, specifically comprise two submodels, one is latent variable model or structural model, for the relation between description scheme variable; One is measurement model, for describing the relation between latent variable and measurand.

The mathematical form of structural model is abbreviated as:

η＝Bη+Γξ+ζ (1)

In structure variable, social context and accidental factor are exogenous variables, are represented by ξ; Awareness degree, degree of recognition, familiarity and tourism wish are endogenous variables, are represented by η.B, Γ are respectively the construction coefficient matrix of η and ξ, and ζ is the error vector of structure variable model.

Structure variable model expands into:

$\left(\begin{array}{c}{\mathrm{\η}}_1\\ {\mathrm{\η}}_2\\ {\mathrm{\η}}_3\\ {\mathrm{\η}}_4\end{array}\right)=\left\{\begin{array}{cccc}0& 0& 0& 0\\ {\mathrm{\β}}_{21}& 0& {\mathrm{\β}}_{23}& 0\\ {\mathrm{\β}}_{31}& 0& 0& 0\\ {\mathrm{\β}}_{41}& {\mathrm{\β}}_{42}& {\mathrm{\β}}_{43}& 0\end{array}\right)*\left(\begin{array}{c}{\mathrm{\η}}_1\\ {\mathrm{\η}}_2\\ {\mathrm{\η}}_3\\ {\mathrm{\η}}_4\end{array}\right)+\left(\begin{array}{cc}{\mathrm{\γ}}_{11}& {\mathrm{\γ}}_{12}\\ {\mathrm{\γ}}_{21}& {\mathrm{\γ}}_{22}\\ {\mathrm{\γ}}_{31}& {\mathrm{\γ}}_{32}\\ 0& 0\end{array}\right)*\left(\begin{array}{c}{\mathrm{\ξ}}_1\\ {\mathrm{\ξ}}_2\end{array}\right)+\left(\begin{array}{c}{\mathrm{\ζ}}_1\\ {\mathrm{\ζ}}_2\\ {\mathrm{\ζ}}_3\\ {\mathrm{\ζ}}_4\end{array}\right)---\left(2\right)$

The mathematical form of measurand model is abbreviated as:

x＝Λ _xξ+δ (3)

y＝Λ _yη+ε (4)

X, y are respectively raw observational variable vector in external observational variable vector sum, Λ _x, Λ _yrespectively represent x to ξ's and y to the regression coefficient matrix of η, i.e. matrix of loadings.

Measurand model expands into:

$\left(\begin{array}{c}{x}_1\\ x_2\\ .\\ .\\ .\\ x_7\\ x_8\\ x_9\end{array}\right)=\left(\begin{array}{cc}{\mathrm{\λ}}_{x11}& 0\\ {\mathrm{\λ}}_{x21}& 0\\ .& .\\ .& .\\ .& .\\ {\mathrm{\λ}}_{x71}& 0\\ 0& {\mathrm{\λ}}_{x82}\\ 0& {\mathrm{\λ}}_{x92}\end{array}\right)*\left(\begin{array}{c}{\mathrm{\ζ}}_1\\ {\mathrm{\ζ}}_2\end{array}\right)+\left(\begin{array}{c}{\mathrm{\δ}}_1\\ {\mathrm{\δ}}_2\\ {\mathrm{\δ}}_3\\ {\mathrm{\δ}}_4\\ {\mathrm{\δ}}_5\\ {\mathrm{\δ}}_6\end{array}\right)---\left(5\right)$

$\left(\begin{array}{c}{y}_1\\ y_2\\ y_3\\ .\\ .\\ .\\ y_{10}\\ y_{20}\\ y_{21}\\ y_{22}\end{array}\right)=\left(\begin{array}{cccc}{\mathrm{\λ}}_{y11}& 0& 0& 0\\ {\mathrm{\λ}}_{y21}& 0& 0& 0\\ {\mathrm{\λ}}_{y31}& 0& 0& 0\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ \text{0}& 0& {\mathrm{\λ}}_{y103}& 0\\ 0& 0& 0& {\mathrm{\λ}}_{y204}\\ 0& 0& 0& {\mathrm{\λ}}_{y214}\\ 0& 0& 0& {\mathrm{\λ}}_{y224}\end{array}\right)*\left(\begin{array}{c}{\mathrm{\η}}_1\\ {\mathrm{\η}}_2\\ {\mathrm{\η}}_3\\ {\mathrm{\η}}_4\end{array}\right)+\left(\begin{array}{c}{\mathrm{\ϵ}}_1\\ {\mathrm{\ϵ}}_2\\ {\mathrm{\ϵ}}_3\\ .\\ .\\ .\\ {\mathrm{\ϵ}}_{21}\\ {\mathrm{\ϵ}}_{22}\\ {\mathrm{\ϵ}}_{23}\end{array}\right)---\left(6\right)$

(2), tourist to China local tourism popularity index

1. model variable

The structure variable of tourist to China local tourism popularity index basis measurement model is made up of social context, accidental factor, awareness degree, perceived quality, familiarity and tourism loyalty 6 variablees.Immigration team visitor local tourism popularity exponential sum immigration individual traveler local tourism popularity index has identical structure variable and model latus rectum, and just the measurand of latent variable is slightly different.

1.1 defining variable

The definition of 6 structure variables: social context refers to the social environmental factor of tourist famous-city, as somewhere politics, economy, cultural environment etc.; Accidental factor refers to major event, disaster etc. that tourist famous-city occurs/holds; Awareness degree refers to the degree that tourist to China is known tourist famous-city and whether existed; Familiarity refers to the familiarity of tourist to China to tourist famous-city; Perceived quality refers to the actual perceived level of tourist to China to the service quality in tourism that tourist famous-city provides; Tourism loyalty refers to that tourist to China is in tourism purchase decision, repeatedly shows the behavior reaction a certain tourist famous-city being had to skewed popularity.

Distinguish endogenous variable and exogenous variable: social context and accidental factor are the exogenous variables of tourist to China local tourism popularity index basis measurement model, awareness degree, familiarity, perceived quality and tourism loyalty are the endogenous variables of tourist to China local tourism popularity index basis measurement model.

Relation between 1.2 variablees

The index system of tourist to China local tourism popularity index is divided into three levels equally, and the first level index is made up of latent variable; Second level index is made up of the measurand of latent variable; For the measurand of the tourist resources such as tourist communications, tourist catering, tourist lodging, be provided with again concrete segmentation evaluation index respectively ⁱ, segmentation evaluation index forms third layer time index.The difference of immigration team visitor local tourism popularity exponential sum immigration individual traveler local tourism popularity index mainly concentrates on choosing with in the difference of the concrete segmentation index of the tourist resources measurand such as travel agency of the measurand of part latent variable.

According to the cause-effect relationship principle of tourist to China local tourism popularity exponential model, in the first level index, social context, accidental factor, awareness degree, familiarity and perceived quality affect the tourism loyalty of tourist to China, it is the input variable of model, also referred to as prerequisite variable, and visitor travels, loyalty is output variable, is also called outcome variable.Prerequisite variable and outcome variable, all there is complicated correlationship between prerequisite variable and between outcome variable, these correlationships carry out detailed analysis & verification by calculation using models.

Prerequisite variable determination result variable.Social context, accidental factor, awareness degree, perceived quality and familiarity directly affect and decide the tourism loyalty of tourist to China.The tourism loyalty correlation of awareness degree, perceived quality and familiarity and tourist to China, awareness degree or perceived quality, also or familiarity index is higher, the tourism loyalty of visitor is higher.Meanwhile, familiarity also plays partial intermediary effect in awareness degree with perceived quality impact tourism loyalty: under identical awareness degree or perceived quality, if familiarity is higher, then tourist to China tourism loyalty is higher.

Also correlativity is there is between each prerequisite variable.Awareness degree and perceived quality, perceived quality and familiarity, between awareness degree and familiarity, all there is positive correlation.Higher awareness degree can produce high perceived quality; High awareness degree and perceived quality can produce high familiarity.In addition, awareness degree, familiarity by and perceived quality to the impact of exogenous variable social context, accidental factor.

2. model latus rectum figure

According to the relation between structure variable, the latus rectum figure of tourist to China local tourism popularity index (TAI-I) structural model;

3. tourist to China local tourism popularity assessment indicator system

With reference to external top tourism academic journal " Annals of Tourism Research ", " Tourism Management ", " Journal of Travel Research ", " International Marketing Review " etc. in recent years publish about tourism destination performance appraisal (METDM, Measuring the Effective of Tourism Destination Marketing), tourist famous-city brand assets (TDBE, Tourism Destination Brand Equity), based on the brand assets (CBBE at visitor visual angle, Consumer-based Brand Equity) etc. the classical documents of aspect (as Konecnik and Gartner, 2007, Boo et al., 2009, Pike, 2010 etc.), and in conjunction with domestic and international tourist famous-city popularity, tourism destination performance appraisal experience, overseas three Hierarchy indicataors system of the local tourism popularity index of Simulation see the following form.

The index system guide look of table 2 tourist to China local tourism popularity index

4. model is estimated

In view of identical the considering with overseas Simulation local tourism popularity exponential model, we adopt PLS estimation technique to set up to tourist to China local tourism popularity index basis measurement model, and the tourist to China local tourism popularity exponential model of foundation is by the offset minimum binary soft sim CA-P process by specialty.

5. model mathematical form

With overseas Simulation local tourism popularity exponential model is identical, be linear weighted function relation between our hypothesized model structure variable and between structure variable and measurand, consider measuring error factor, it is one group of linear structural equation by model specification, specifically comprise two submodels, one is latent variable model or structural model, for the relation between description scheme variable; One is measurement model, for describing the relation between latent variable and measurand.

The mathematical form of structural model is abbreviated as:

η＝Bη+Γξ+ζ (1)

In overseas Simulation local tourism popularity exponential model, η represents awareness degree, degree of recognition, familiarity and tourism wish.And in immigration model, η represents awareness degree, perceived quality, familiarity and tourism loyalty.

Structure variable model expands into:

$\left(\begin{array}{c}{\mathrm{\η}}_1\\ {\mathrm{\η}}_2\\ {\mathrm{\η}}_5\\ {\mathrm{\η}}_6\end{array}\right)=\left\{\begin{array}{cccc}0& 0& 0& 0\\ {{\mathrm{\β}}_{21}}^{*}& 0& {\mathrm{\β}}_{25}& 0\\ {\mathrm{\β}}_{51}& 0& 0& 0\\ {\mathrm{\β}}_{61}& {\mathrm{\β}}_{62}& {\mathrm{\β}}_{65}& 0\end{array}\right)*\left(\begin{array}{c}{\mathrm{\η}}_1\\ {\mathrm{\η}}_2\\ {\mathrm{\η}}_5\\ {\mathrm{\η}}_6\end{array}\right)+\left(\begin{array}{cc}{{\mathrm{\γ}}_{11}}^{*}& {{\mathrm{\γ}}_{12}}^{*}\\ {{\mathrm{\γ}}_{21}}^{*}& {{\mathrm{\γ}}_{22}}^{*}\\ {\mathrm{\γ}}_{51}& {\mathrm{\γ}}_{52}\\ 0& 0\end{array}\right)*\left(\begin{array}{c}{\mathrm{\ξ}}_1\\ {\mathrm{\ξ}}_2\end{array}\right)+\left(\begin{array}{c}{{\mathrm{\ζ}}_1}^{*}\\ {{\mathrm{\ζ}}_2}^{*}\\ {\mathrm{\ζ}}_5\\ {\mathrm{\ζ}}_6\end{array}\right)---\left(7\right)$

Measurand model expands into:

$\left(\begin{array}{c}{x}_1\\ x_2\\ .\\ .\\ .\\ x_7\\ x_8\\ x_9\end{array}\right)=\left(\begin{array}{cc}{{\mathrm{\λ}}_{x11}}^{*}& 0\\ {{\mathrm{\λ}}_{x21}}^{*}& 0\\ .& .\\ .& .\\ .& .\\ {{\mathrm{\λ}}_{x71}}^{*}& 0\\ 0& {{\mathrm{\λ}}_{x82}}^{*}\\ 0& {{\mathrm{\λ}}_{x92}}^{*}\end{array}\right)*\left(\begin{array}{c}{\mathrm{\ζ}}_1\\ {\mathrm{\ζ}}_2\end{array}\right)+\left(\begin{array}{c}{{\mathrm{\δ}}_1}^{*}\\ {{\mathrm{\δ}}_2}^{*}\\ {{\mathrm{\δ}}_3}^{*}\\ {{\mathrm{\δ}}_4}^{*}\\ {{\mathrm{\δ}}_5}^{*}\\ {{\mathrm{\δ}}_6}^{*}\end{array}\right)---\left(8\right)$

$\left(\begin{array}{c}{y}_1\\ .\\ .\\ .\\ y_7\\ y_{11}\\ .\\ .\\ .\\ y_{19}\\ y_{23}\\ y_{24}\end{array}\right)=\left(\begin{array}{cccc}{\mathrm{\λ}}_{y11}& 0& 0& 0\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ 0& {\mathrm{\λ}}_{y72}& 0& 0\\ 0& 0& {\mathrm{\λ}}_{y115}& 0\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ 0& 0& {\mathrm{\λ}}_{y195}& 0\\ \text{0}& 0& 0& {\mathrm{\λ}}_{y236}\\ 0& 0& 0& {\mathrm{\λ}}_{y246}\end{array}\right)*\left(\begin{array}{c}{\mathrm{\η}}_1\\ {\mathrm{\η}}_2\\ {\mathrm{\η}}_5\\ {\mathrm{\η}}_6\end{array}\right)+\left(\begin{array}{c}{\mathrm{\ϵ}}_1\\ {\mathrm{\ϵ}}_2\\ {\mathrm{\ϵ}}_3\\ .\\ .\\ .\\ {\mathrm{\ϵ}}_{21}\\ {\mathrm{\ϵ}}_{22}\\ {\mathrm{\ϵ}}_{23}\end{array}\right)---\left(9\right)$

The present invention is described in detail in preferred embodiment above by concrete; but those skilled in the art should be understood that; the present invention is not limited to the above embodiment; within the spirit and principles in the present invention all; any amendment of doing, equivalent replacement etc., all should be included within protection scope of the present invention.

Claims (9)

1. a method for local tourism popularity index construction and budget, is characterized in that, comprises the steps:

S1, obtains the index of visitor to tourism popularity;

S2, the index according to tourism popularity builds structural equation model; Structural equation model is based on the analysis of covariance structures method of maximal possibility estimation by a kind of or obtained based on the method for analysis of variance of partial least squares regression;

S3, carries out budget according to described structural equation model.

2. the method for local tourism popularity index construction according to claim 1 and budget, is characterized in that:

When described tourist information comprises immigration tourist information;

Described tourist famous-city information comprises social condition, accidental factor, awareness degree, familiarity, perceived quality and tourism loyalty;

Described social context is the social environmental factor of tourist famous-city;

Described social environmental factor comprises tourist area politics, tourist area economy and tourist area cultural environment;

Described accidental factor comprises the tourist famous-city major event occurring/hold and object disaster factors of travelling;

Described awareness degree comprises tourist to China and knows the degree whether tourist famous-city exist;

Described familiarity comprises the familiarity of tourist to China to tourist famous-city;

Described perceived quality comprises the actual perceived level of tourist to China to the service quality in tourism that tourist famous-city provides;

Described tourism loyalty comprises tourist to China in tourism purchase decision, shows the behavior reaction a certain tourist famous-city being had to skewed popularity at least one times;

Described social context and described accidental factor are as the exogenous variable of tourist to China local tourism popularity index basis measurement model;

Described awareness degree, described familiarity, described perceived quality and described tourism loyalty are as the endogenous variable of tourist to China local tourism popularity index basis measurement model;

Tourist to China local tourism popularity index is divided into three levels, and the first level index is made up of latent variable; Second level index is made up of the measurand of latent variable; Third layer time index is made up of the segmentation evaluation index of measurand; Measurand is tourist resources; Tourist resources comprises tourist communications, tourist catering and tourist lodging;

Described social context, described accidental factor, described awareness degree, described familiarity and described perceived quality are as the input variable of the described tourism loyalty of impact; Described tourism loyalty is as output variable;

Described awareness degree, described perceived quality and described familiarity and described tourism loyalty correlation;

Under identical awareness degree or perceived quality, if familiarity is higher, then tourist to China tourism loyalty is higher.

3. the method for local tourism popularity index construction according to claim 2 and budget, it is characterized in that: adopt PLS estimation technique to set up to tourist to China local tourism popularity index basis measurement model, the tourist to China local tourism popularity exponential model of foundation is by the offset minimum binary SIMCA-P process by specialty.

4. the method for local tourism popularity index construction described in 3 and budget is wanted according to right, it is characterized in that: be linear weighted function relation between hypothesized model structure variable and between structure variable and measurand, it is one group of linear structural equation by model specification, specifically comprise two submodels, one is latent variable model or structural model, for the relation between description scheme variable; One is measurement model, for describing the relation between latent variable and measurand.

5. want the method for local tourism popularity index construction described in 4 and budget according to right, it is characterized in that:

The mathematical form of structural model is abbreviated as:

η＝Bη+Γξ+ζ；

In overseas Simulation local tourism popularity exponential model, η represents awareness degree, degree of recognition, familiarity and tourism wish; And in immigration model, η represents awareness degree, perceived quality, familiarity and tourism loyalty;

Structure variable model expands into:

Measurand model expands into:

6. want the method for local tourism popularity index construction described in 1 and budget according to right, it is characterized in that:

Described tourist information comprise overseas Simulation information time; Then definition structure variable, is specially:

Social context refers to the social environmental factor of tourist famous-city;

Awareness degree refers to the degree that overseas Simulation is known tourist famous-city and whether existed;

Familiarity refers to that Simulation is to the familiarity of tourist famous-city overseas;

Degree of recognition refers to the overseas Simulation degree to the good opinion of tourist famous-city, trust, receiving;

Tourism wish refers to that Simulation buys the wish degree of a certain ground travelling products;

There is following relation between variable: the index system of Simulation local tourism popularity index is divided into two each and every one levels overseas, the first level index is made up of latent variable; Second level index is made up of the measurand of latent variable;

According to the cause-effect relationship principle of overseas Simulation local tourism popularity measurement model, in the first level index, social context, accidental factor, awareness degree, degree of recognition and familiarity five variablees affect the tourism wish of Simulation, it is the input variable of model, also referred to as prerequisite variable, and the tourism wish of Simulation is output variable, be also called outcome variable; Prerequisite variable and outcome variable, all there is complicated correlationship between prerequisite variable and between outcome variable, these correlationships carry out detailed analysis & verification by calculation using models;

Prerequisite variable determination result variable; Social context, accidental factor, awareness degree, degree of recognition and familiarity directly/affect indirectly the tourism wish of Simulation; Awareness degree, degree of recognition and familiarity and overseas Simulation are traveled wish correlation, and awareness degree, degree of recognition, familiarity index are higher, and the tourism wish of visitor is stronger; Meanwhile, familiarity also plays partial intermediary effect in awareness degree with degree of recognition impact tourism wish: under identical awareness degree or degree of recognition situation, the familiarity of visitor to tourist famous-city is higher, then the wish going to the tourism of this ground is stronger;

Also correlativity is there is between each prerequisite variable; Awareness degree and degree of recognition, degree of recognition and familiarity, between awareness degree and familiarity, all there is positive correlation; Higher awareness degree can produce high degree of recognition; High degree of recognition and awareness degree can produce high familiarity; In addition, awareness degree, degree of recognition and familiarity are subject to the impact of exogenous variable social context, accidental factor.

7. the method for local tourism popularity index construction described in 6 and budget is wanted according to right, it is characterized in that: overseas Simulation local tourism popularity index basis measurement model adopts PLS estimation technique to set up, and the Simulation popularity exponential model of foundation is by the offset minimum binary SIMCA-P process by specialty.

8. the method for local tourism popularity index construction described in 7 and budget is wanted according to right, it is characterized in that: be linear weighted function relation between hypothesized model structure variable and between structure variable and measurand, consider measuring error factor, it is one group of linear structural equation by model specification, specifically comprise two submodels, one is latent variable model or structural model, for the relation between description scheme variable; One is measurement model, for describing the relation between latent variable and measurand.

9. want the method for local tourism popularity index construction described in 8 and budget according to right, it is characterized in that:

The mathematical form of structural model is abbreviated as:

η＝Bη+Γξ+ζ；

In structure variable, social context and accidental factor are exogenous variables, are represented by ξ; Awareness degree, degree of recognition, familiarity and tourism wish are endogenous variables, are represented by η; B, Γ are respectively the construction coefficient matrix of η and ξ, and ζ is the error vector of structure variable model;

Structure variable model expands into:

The mathematical form of measurand model is abbreviated as:

x＝Λ _xξ+δ；

y＝Λ _yη+ε；

X, y are respectively raw observational variable vector in external observational variable vector sum, Λ _x, Λ _yrespectively represent x to ξ's and y to the regression coefficient matrix of η, i.e. matrix of loadings;

Measurand model expands into: