productivity growth of taiwanese international tourist hotels in a metafrontier framework li-hsueh...

Productivity growth of Taiwanese

international tourist hotels in a

metafrontier framework

Li-Hsueh Chen

Department of Transportation Science, National Taiwan Ocean University, Taiwan

22

Outline

Introduction

Methodology

Empirical implementation

Discussion

Conclusions

33

Outline

Introduction

Methodology


Discussion

Conclusions

44

The expansion of tourism has increased the demand for hotels and the competitive pressure in the hotel industry.

In this highly competitive environment, how to survive has become an important issue for hotel operators.

In the long run, the performance of a firm is an important determinant of its survival (Anderson, Fok, and Scott 2000).

Hence, hotel operators need more information regarding their performance to maintain or promote their competitiveness in the hotel industry.

Introduction

55

To identify and assess performance, productivity measurement approaches are often applied.

Studies now tend to use the total factor productivity (TFP) approach to measure productivity.

The Malmquist productivity index (MPI) has become a popular approach to estimate the TFP.

The MPI can further decompose the productivity change into the components of technical change (TC) and efficiency change (EC).

Introduction

66

The shortcomings of conventional MPI

Circularity

Infeasibility

The assumption of the same technology.

The metafrontier approach proposed by Oh and Lee (2010) can overcome the above shortcomings.

It can further decompose MPI into

within-group EC (the catching-up effect),

within-group TC (the innovation effect),

technical leadership change (the technology leading effect).

Introduction

77

Early studies assessed the performance of hotels with various financial indicators.

After Morey and Dittman (1995), a greater number of studies applied data envelopment approach (DEA) to evaluate the performance of hotels.

Due to the differences in the operational styles, it cannot be reasonably assumed that hotels face the same benchmark technology.

The major contribution of this study is to compare the productivity changes among international tourist hotel (ITHs) by using the metafrontier MPI based on recent ITH data.

Introduction

88

Outline

Introduction

Methodology


Discussion

Conclusions

99

Methodology

To define an output-oriented MPI, it is assumed that an ITH uses a vector of N inputs, , to produce a vector of M outputs, , in period t,

The benchmark technology, , satisfies the assumptions of convexity and free disposability as described in Färe et al. (1994).

The output distance function in period t can be defined as

• is the ratio of the vector of outputs to the production frontier represented by P in period t.

1( , , ) t t t NNx x x R

1( , , ) t t t MMy y y R 1, , t T

{( , ) : can produce }t t t t tP x y x y

θ

1010

Methodology

If the contemporaneous benchmark technology set of group is assumed to be , , then the intertemporal and global benchmark technology sets can be defined as and

.

The metafrontier MPI can be formed as

lU l

tUP 1, , l L

1{ } l l l

I TU U UP conv P P

1{ }

L

G I IU UP conv P P

1111

Methodology

can be further decomposed as

(3)

GMPI

1 1

1 1 1 1 1

1 1 1

1 1 1 1 1 1 1

1 1 1 1 1

, , ,

, , ,

, , ,

, , , ,

, , , ,

G t t t to

t t t G t t t t to o o

t t t t t t G t to o o

t t t I t t t t t G t to o o o

t t t t t t I t t I t to o o o

MPI x y x y

D x y D x y D x y

D x y D x y D x y

TE x y D x y D x y D x y D

TE x y D x y D x y D x y

1 1 1 1 1 1 1 1 11 1 1

, 11 1 1

,

,

, , , ,,

, , , , ,

,

,

I t to

G t to

I t t t t t G t t I t tt t to o o oo

t t t I t t t t t G t t I t to o o o o

I tt t t to o

t t to

x y

D x y

D x y D x y D x y D x yTE x y

TE x y D x y D x y D x y D x y

TE x y BPG x

TE x y

1 1 1 1 1

,

1 1 1 1 1 1

, ,

, ,

, , , , , , , , , ,

t t t to

I t t t t t too

t t t t t t t t t t t t

y TGR x y

BPG x y TGR x y

EC x y x y BPC x y x y TGC x y x y

1212

Methodology

Exhibit 1 illustrates the concept of the metafrontier in the Malmquist productivity framework.

A decision making unit (DMU) is observed to produce an output vector A in period 1 and an output vector E in period 2.

Exhibit 1: Concept of the Metafrontier MPI.

1313

Methodology

To compute the metafrontier MPI and its components, six output distance functions in Equation 3 need to be calculated by DEA.

For each hotel, , the output distance functions can be obtained by solving the following LP problem with a variable returns-to-scale (VRS) technology

subject to

(4)• represents the intensity variable, .

lk U

1,, max ,

k ss s so Ck kD x y

,, , , 1, , ,

l

k ss s sj j m C k m

j U

z y y m M

, , , 1, , ,

l

s s sj j n k n

j U

z x x n N

1,

l

sj

j U

z 0,sjz

sjz , 1 s t t

1414

Methodology

If denotes the optimal solution to Equation 4, then the intertemporal distance function, which uses all ITHs over all periods within a specific group , can be computed by the model

subject to

(5)

lU

1,, ( , max ,k sI s s s s s

o o Ik k k kD x y D x y

,,, ,

,

ˆ , 1, , ,l

k ss s k s sj j m I C k m

j U s

z y y m M

, ,,

, 1, , ,l

s s sj j n k n

j U s

z x x n N

,

1,l

sj

j U s

z

,̂k sC

0, ψ 1, , . sjz T

1515

Methodology

If denotes the optimal solution to Equation 5, then the global distance function, which uses all ITHs and periods over all groups, can be calculated as

subject to

(6)

1,, ( , max ,k sG s s I s s

o o Gk k k kD x y D x y

,, ,, ,

,

ˆ ˆ , 1, , ,k ss s k s k s sj j m IG C k m

j U s

z y y m M

, ,,

, 1, , ,s s sj j n k n

j U s

z x x n N

,

1,sj

j U s

z

,ˆ k sI

10, , ψ 1, , .sj Lz U U U T

1616

Outline

Introduction

Methodology

Empirical Implementation

Data descriptions

Empirical results

Discussion

Conclusions

1717

Data descriptions

Data: 54 ITSs from 2008 to 2011.

Inputs:The number of guest rooms,

The number of employees,

The total floor area of food and beverage,

Other expenses.

Outputs:Room revenues,

Food and beverage revenues,

Other revenues.

1818

Data descriptions

Operational style: Chain hotels,

Independent hotels.

1919

Outline

Introduction

Methodology


Data and specification of inputs and outputs

Empirical results• Comparison between chain hotels and

independent hotels

• Comparing individual hotel productivity

Discussion

Conclusions

2020

Comparison between chain hotels and independent hotels

First, we must confirm that chain hotels and independent hotels operate under different technologies.

We assess the statistical significance of the differences between the technology gap ratios (TGRs) of these two groups by the Wilcoxon–Mann–Whitney test (Beltrán-Esteve et al. 2014).

The result shows that chain hotels and independent hotels have different technologies.

It is adequate to use metafrontier MPI to estimate the productivity change of ITHs.

2121


The hotels operating under different technologies will lead to distinct results.

The productivity for chain hotels has deteriorated.

Independent hotels have improved their productivity.

MPI EC BPC TGCChain hotels

2008-2009 0.951 0.960 0.978 1.0132009-2010 1.013 1.026 0.988 1.0002010-2011 1.032 1.008 1.028 0.9962008-2011 0.995 0.993 0.993 1.009

Independent hotels2008-2009 0.966 0.999 0.969 0.9982009-2010 1.084 1.030 1.051 1.0012010-2011 1.039 1.027 1.018 0.9942008-2011 1.089 1.058 1.036 0.994

Exhibit 3: Productivity Growth between Chain and Independent Hotels.

2222


For the decomposition of productivity change

Chain hotels have moved further away from the contemporaneous frontiers.

Independent hotels have gotten closer to the contemporaneous frontiers.

Chain hotels have regressed technically.

Independent hotels have shown technical progress.


2008-2009 0.951 0.960 0.978 1.0132009-2010 1.013 1.026 0.988 1.0002010-2011 1.032 1.008 1.028 0.9962008-2011 0.995 0.993 0.993 1.009



2323


Independent hotels have moved further away from the global frontier.

For both independent hotels and chain hotels, the change of productivity was mainly driven by within-group EC and TC from 2008 to 2011.


2008-2009 0.951 0.960 0.978 1.0132009-2010 1.013 1.026 0.988 1.0002010-2011 1.032 1.008 1.028 0.9962008-2011 0.995 0.993 0.993 1.009



2424


The value of TGR for most chain hotels over time are close to 1.

The value of TGR for independent hotels are more dispered

The chain hotels’ intertemporal frontier is closer to the global frontier than independent hotels’ intertemporal frontier.

The curvatures of chain hotels’ intertemporal frontier and global frontier are more similar. Exhibit 4: Distribution of Technical Gap Ratios for Chain Hotels (CH) and Independent Hotels (IH).

2525


Chain hotels are the technology leaders, and independent hotels are the followers.

Exhibit 4: Distribution of Technical Gap Ratios for Chain Hotels (CH) and Independent Hotels (IH).

2626


To thoroughly investigate the differences in patterns between chain and independent hotels

These two groups display similar patterns of productivity change with improved productivity after 2010.

The cumulative productivity growth in independent hotels is higher than that in chain hotels.

The cumulative productivity growth in chain hotels is also lower than 1 over the sample period.

Exhibit 5: Cumulative Productivity Change in Chain and Independent Hotels.

2727


The sources of productivity change for chain hotels

In 2009, the technical leadership progress alleviated the productivity deterioration for chain hotels.

In 2010, the within-group efficiency improvement resisted the within-group technical and technical leadership regress and facilitated productivity growth.

Exhibit 6: Average Annual Growth in Productivity and Its Decomposition in Chain Hotels.

2828


Although the within-group efficiency improvement and within-group technical progress contributed toward the productivity of chain hotels, the positive effects were offset by the slowdown of technical leadership progress, resulting in productivity in 2011 being still lower than that in 2008.

Exhibit 6: Average Annual Growth in Productivity and Its Decomposition in Chain Hotels.

2929


The sources of productivity change for independent hotels

The negative relationship with the productivity change and technical leadership change in 2011.

The productivity change for independent hotels had a similar pattern with its decompositions.

Exhibit 7: Average Annual Growth in Productivity and Its Decomposition in Independent Hotels.

3030


The within-group technical progress was the dominant factor facilitating productivity growth before 2010.

The within-group efficiency improvement was the dominant one after 2010.

Exhibit 7: Average Annual Growth in Productivity and Its Decomposition in Independent Hotels.

3131

Outline

Introduction

Methodology


Data and specification of inputs and outputs

Empirical results• Comparison between chain hotels and

independent hotels

• Comparing individual hotel productivity

Discussion

Conclusions

3232

Comparing individual hotel productivity

CH10, CH12, CH22, CH23, and IH01 defined the global frontier in both 2008 and 2011, so MPI = 1.

Fifteen chain hotels and sixteen independent hotels had higher productivity in 2011 than that in 2008.

Twelve chain hotels and six independent hotels had lower productivity in 2011 than that in 2008.

3333

Exhibit 8: Cumulated Productivity Growth for Individual Hotels, 2008-2011.


CH01 0.863 0.941 0.917 1.000CH02 0.971 1.056 0.895 1.027CH03 1.086 1.000 1.009 1.075CH04 1.191 1.000 1.188 1.003CH05 1.120 1.000 1.120 1.000CH06 0.598 0.604 0.932 1.062CH07 0.996 0.994 1.002 1.000CH08 1.209 1.029 1.175 1.000CH09 1.529 1.379 1.109 1.000CH10 1.000 1.000 1.000 1.000CH11 0.712 0.761 0.956 0.978CH12 1.000 1.000 1.000 1.000CH13 0.857 0.695 1.226 1.005CH14 0.991 1.106 0.925 0.969CH15 1.045 0.908 1.167 0.987CH16 0.873 0.882 0.986 1.004CH17 1.024 1.209 0.865 0.979CH18 1.050 1.168 0.894 1.006CH19 0.813 0.819 0.911 1.090CH20 0.932 1.000 0.932 1.000CH21 1.074 1.000 1.082 0.993CH22 1.000 1.000 1.000 1.000CH23 1.000 1.000 1.000 1.000CH24 1.052 1.000 1.000 1.052CH25 1.049 0.993 1.026 1.030CH26 1.004 0.999 1.005 1.000CH27 1.153 1.191 0.968 1.000

CH28 0.861 0.986 0.854 1.023CH29 1.257 1.438 0.874 1.000CH30 0.897 1.047 0.850 1.008CH31 1.056 1.000 1.053 1.003

Average 0.995 0.993 0.993 1.009Independent hotels

IH01 1.000 1.000 1.000 1.000IH02 0.892 0.974 0.939 0.976IH03 1.222 1.190 1.085 0.947IH04 0.926 0.923 1.047 0.959IH05 1.119 1.000 1.000 1.119IH06 1.124 1.111 1.040 0.973IH07 1.326 1.395 1.089 0.873IH08 1.193 1.060 1.164 0.966IH09 1.215 1.219 1.044 0.955IH10 1.037 1.008 1.081 0.952IH11 1.244 1.000 1.010 1.232IH12 0.753 1.000 1.000 0.753IH13 0.990 0.930 1.072 0.993IH14 1.003 1.000 1.000 1.003IH15 1.071 0.983 1.065 1.024IH16 1.029 1.000 1.000 1.029IH17 0.962 0.938 1.054 0.973IH18 1.504 1.454 1.018 1.015IH19 1.174 1.000 1.000 1.174IH20 1.024 1.000 1.000 1.024IH21 1.457 1.231 1.123 1.053IH22 1.133 1.095 1.048 0.987IH23 0.954 1.000 0.982 0.971

Average 1.089 1.058 1.036 0.994

3434


The source of productivity change

Hotels with efficiency increase, technology progress, and technical leadership progress.

Hotels with efficiency increase, technology progress, and technical leadership regress.

Hotels with efficiency increase, technology regress, and technical leadership progress.

Hotels with efficiency decrease, technology progress, and technical leadership progress.

Hotels with efficiency increase, technology regress, and technical leadership regress.

Hotels with efficiency decrease, technology progress, and technical leadership regress

3535


Hotels with efficiency decrease, technology regress, and technical leadership progress.

Hotels with efficiency decrease, technology regress, and technical leadership regress.

3636

Exhibit 8: Cumulated Productivity Growth for Individual Hotels, 2008-2011.


CH01 0.863 0.941 0.917 1.000CH02 0.971 1.056 0.895 1.027CH03 1.086 1.000 1.009 1.075CH04 1.191 1.000 1.188 1.003CH05 1.120 1.000 1.120 1.000CH06 0.598 0.604 0.932 1.062CH07 0.996 0.994 1.002 1.000CH08 1.209 1.029 1.175 1.000CH09 1.529 1.379 1.109 1.000CH10 1.000 1.000 1.000 1.000CH11 0.712 0.761 0.956 0.978CH12 1.000 1.000 1.000 1.000CH13 0.857 0.695 1.226 1.005CH14 0.991 1.106 0.925 0.969CH15 1.045 0.908 1.167 0.987CH16 0.873 0.882 0.986 1.004CH17 1.024 1.209 0.865 0.979CH18 1.050 1.168 0.894 1.006CH19 0.813 0.819 0.911 1.090CH20 0.932 1.000 0.932 1.000CH21 1.074 1.000 1.082 0.993CH22 1.000 1.000 1.000 1.000CH23 1.000 1.000 1.000 1.000CH24 1.052 1.000 1.000 1.052CH25 1.049 0.993 1.026 1.030CH26 1.004 0.999 1.005 1.000CH27 1.153 1.191 0.968 1.000

CH28 0.861 0.986 0.854 1.023CH29 1.257 1.438 0.874 1.000CH30 0.897 1.047 0.850 1.008CH31 1.056 1.000 1.053 1.003

Average 0.995 0.993 0.993 1.009Independent hotels

IH01 1.000 1.000 1.000 1.000IH02 0.892 0.974 0.939 0.976IH03 1.222 1.190 1.085 0.947IH04 0.926 0.923 1.047 0.959IH05 1.119 1.000 1.000 1.119IH06 1.124 1.111 1.040 0.973IH07 1.326 1.395 1.089 0.873IH08 1.193 1.060 1.164 0.966IH09 1.215 1.219 1.044 0.955IH10 1.037 1.008 1.081 0.952IH11 1.244 1.000 1.010 1.232IH12 0.753 1.000 1.000 0.753IH13 0.990 0.930 1.072 0.993IH14 1.003 1.000 1.000 1.003IH15 1.071 0.983 1.065 1.024IH16 1.029 1.000 1.000 1.029IH17 0.962 0.938 1.054 0.973IH18 1.504 1.454 1.018 1.015IH19 1.174 1.000 1.000 1.174IH20 1.024 1.000 1.000 1.024IH21 1.457 1.231 1.123 1.053IH22 1.133 1.095 1.048 0.987IH23 0.954 1.000 0.982 0.971

Average 1.089 1.058 1.036 0.994

3737

Outline

Introduction

Methodology


Discussion

Conclusions

3838

Discussion

Chain hotels suffered a slight drop in productivity, while independent hotels had growth in productivity.

With the shock of the financial tsunami, hotels should have adjusted their operational strategies to mitigate the effects of this event.

Exhibit 3: Productivity Growth between Chain and Independent Hotels. MPI EC BPC TGC

Chain hotels2008-2009 0.951 0.960 0.978 1.0132009-2010 1.013 1.026 0.988 1.0002010-2011 1.032 1.008 1.028 0.9962008-2011 0.995 0.993 0.993 1.009


3939

Discussion

However, since chain hotels’ activities are restricted, they could not immediately adopt new strategies or technology to resist the deterioration in productivity and improve it.

Such characteristics of chain hotels might explain why they had greater productivity deterioration in 2009 and lower productivity growth in 2010 and 2011 than independent hotels did.


Chain hotels2008-2009 0.951 0.960 0.978 1.0132009-2010 1.013 1.026 0.988 1.0002010-2011 1.032 1.008 1.028 0.9962008-2011 0.995 0.993 0.993 1.009


4040

Discussion

The rate of technical leadership change for chain hotels on average is higher than that for independent hotels.

If a hotel has more advanced technology than other hotels, it is the technology leader in the ITH industry.


Chain hotels2008-2009 0.951 0.960 0.978 1.0132009-2010 1.013 1.026 0.988 1.0002010-2011 1.032 1.008 1.028 0.9962008-2011 0.995 0.993 0.993 1.009


4141

Discussion

However, a technology leader does not mean that it would promote the improvement of technology or enhance the technology more than followers do over the period under consideration.

Although leaders’ intertemporal technology frontier is closer to a global one than the followers’, those leaders’ contemporaneous frontiers might still shift inward due to a decrease in demand.


Chain hotels2008-2009 0.951 0.960 0.978 1.0132009-2010 1.013 1.026 0.988 1.0002010-2011 1.032 1.008 1.028 0.9962008-2011 0.995 0.993 0.993 1.009


4242

Discussion

Chain hotels have the more advanced technology and adjust their product mix to enhance the production level to move toward the global production level.• The members of chain hotels have advantages, such as

innovative reservation systems sourced from the management affiliation (Mandelbaum 1997), as well as sharing of the knowledge and technology, their inherent technologies are superior to independent hotels’.

• In contrast, because independent hotels cannot benefit from the knowledge spillover and technology transfer, they should spend more time and resources through trial-and-error experiences (Mitsuhashi and Yamaga 2006).

4343

Discussion

Independent hotels are followers in inventing new technologies, resulting in greater distance between their intertemporal technology frontier and the global technology frontier. • Because more chain hotels adopt advanced technology, they

are good benchmarks in the ITH industry.

• Chain hotels with poor performance may more easily imitate chain hotels that stay in the global frontier to adjust their product mix.

• Independent hotels may not learn from the best-practice hotels in the ITH industry.

That may be why the rate of technical leadership change for chain hotels is better than that for independent hotels.

4444

Discussion

The main managerial implications of this finding

Because the performance of ITHs is influenced by environmental factors, they need to carefully face and handle the problems of changes in the operational environment.

Although independent hotels can more quickly react to changes in the operational environment by improving efficiency and adopting new technology or innovation, they still need to make more effort to obtain the lead in inventing new technologies.

Although chain hotels take the lead in inventing new technologies, they still need to increase their operational flexibility to quickly adjust the usage of inputs and technology.

4545

Outline

Introduction

Methodology


Discussion

Conclusions

4646

Conclusions

The major aim of this study is to provide an alternative framework for the evaluation of productivity in the Taiwanese ITH industry.

The metafrontier MPI is applied to measure the productivity indexes, and to overcome the shortcomings of the conventional MPI.

The empirical results of productivity change in the ITH industry offer several insights.

The use of different technologies by hotels will affect productivity change.

Both within-group EC and TC are the main factors of productivity change for chain and independent hotels.

4747

Conclusions

Chain hotels are technology leaders, and independent hotels are followers.

Direction for future research

Cover the whole hotel industry and compare the difference between STHs and ITHs.

Incorporate nondiscretionary inputs into the metafrontier MPI.

The issue of the direction of bias.

Identify the causes of within-group EC, within-group TC, and technical leadership change.

4848

Thank you for your attention!

productivity growth of taiwanese international tourist hotels in a metafrontier framework li-hsueh...

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