Determinants for productivity improvement in hotel business the case of danang, vietnam

VIETNAM NATIONAL UNIVERSITY, HANOI
VIETNAM JAPAN UNIVERSITY

TRAN TRONG VU LONG

DETERMINANTS FOR PRODUCTIVITY
IMPROVEMENT IN HOTEL BUSINESS:
THE CASE OF DANANG, VIETNAM

MASTER’S THESIS


VIETNAM NATIONAL UNIVERSITY, HANOI
VIETNAM JAPAN UNIVERSITY

TRAN TRONG VU LONG

DETERMINANTS FOR PRODUCTIVITY
IMPROVEMENT IN HOTEL BUSINESS:
THE CASE OF DANANG, VIETNAM

MAJOR: BUSINESS ADMINISTRATION
CODE: 8340101.01

RESEARCH SUPERVISORS:
Associate Professor. Phan Chi Anh
Associate Professor. Kodo Yokozawa

Hanoi – May, 2021

ACKNOWLEDGEMENT
First and foremost, I would like to express my sincere thanks to my parents, my
sister Tran Phuong Ly who always support me in any situation regardless of
successful ones or difficult ones.
Moreover, the successful completion of this thesis might never be possible in
time without the help of some persons whose inspiration and suggestion made it
happen. I want to thank my supervisor, Assoc. Prof. Phan Chi Anh and Assoc.
Prof. Kodo Yokozawa, the supervision, support, and advice that they gave truly
help the progression and smoothness of the program.
Thirdly, I would also like to give my gratefulness to faculty members and
faculty staff of the Program of Business Administration in particular and the
Vietnam Japan University and Yokohama National University in general.
Without these sources of support and encouragement, I would never be able to
fully complete my study as a whole and this thesis specifically.
Last but not least, my genuine appreciation goes to all of my dear friends who
give me enormous support and references. Their unprecedented, countless, and
undoubtedly helpful contributions have been a solid stepping-stone to all of my
accomplishments.
Sincerely,
Tran Trong Vu Long


ABSTRACT
Hotel industry in Vietnam has been explored and dramatically developed before
the COVID-19 pandemic. However, the hotel industry in Vietnam still has been
existed obstacles and problems. As a result, the hotel industry in Vietnam has
lower productivity compared with other countries in South East Asia. The
current situation leads to the necessity of improving productivity in the hotel
industry. This research focuses on the determinants that influence productivity
improvement in the hotel business in Danang, Vietnam, a famous tourist

destination in Vietnam. The data for this study was gathered using a pencil –
paper – survey with the responses of 120 hotel managers or manager's
representatives in Danang city. Based on previous researches that are related to
productivity improvement, a model is adapted to test the direct and indirect
impact of waste reduction, process management, innovation, technology
application, customer focus, employee satisfaction, customer satisfaction on
productivity improvement. Data were analyzed using linear regression and path
analysis with the support of statistical software (free trial version of SPSS 16
and AMOS 24). The findings suggest that only Waste Reduction, Process
Management, Innovation, and Employee Satisfaction have an impact on the
dependent

variable

–

Productivity

Improvement.

Regarding

practical

implications, this study proposes several recommendations to improve
productivity which helps to improve hotel competition and advantages.
Keywords: Hotel industry, productivity, productivity improvement.


TABLE OF CONTENT

LIST OF TABLE ......................................................................................................... i
LIST OF FIGURE .......................................................................................................ii
LIST OF ABBREVIATION ..................................................................................... iii
CHAPTER 1: INTRODUCTION ............................................................................... 1
1.1 Background and necessity of the research ............................................................. 1
1.1.1 Why improving productivity is important in Vietnam context? ..................... 1
1.1.2 Why productivity improvement in hotel industry of Vietnam is necessary? .. 2
1.1.3 Research about productivity improvement in hotel business. ......................... 3
1.2 Aims of research .................................................................................................... 4
1.2.1 Common purposes ........................................................................................... 4
1.2.2 Specific purposes ............................................................................................. 4
1.3 Research questions ................................................................................................. 5
1.4 Research scope ....................................................................................................... 5
1.5 Process and methodology ...................................................................................... 5
1.5.1 The research process ........................................................................................ 5
1.5.2 Methodology .................................................................................................... 5
CHAPTER 2: LITERATURE REVIEW .................................................................... 7
2.1 Concepts of productivity ........................................................................................ 7
2.1.1 Productivity concepts and definitions ............................................................. 7
2.1.2 Productivity measurement ............................................................................... 8
2.1.3 Productivity and determinants in manufacturing .......................................... 10
2.2 The difference between productivity in manufacturing sector and service sector
.................................................................................................................................... 12
2.3 Productivity in hotel sector .................................................................................. 13
2.3.1 Productivity concept in the hotel sector ........................................................ 13
2.3.2 Productivity measures in the hotel sector ...................................................... 14
2.3.3 Determinants for productivity in the hotel sector .......................................... 15
2.4 Productivity improvement ................................................................................... 16
2.4.1 Productivity improvement in hotel sector ..................................................... 16
2.4.2 Determinant for productivity improvement in hotel sector ........................... 17

2.5 Research Gap and Research Questions ................................................................ 19


2.6 Hypothesis development ...................................................................................... 25
2.6.1 Waste reduction and productivity improvement ........................................... 27
2.6.2 Process management and productivity improvement .................................... 28
2.6.3 Innovation and productivity improvement .................................................... 29
2.6.4 Technology application and productivity improvement ............................... 30
2.6.5 Customer focus and productivity improvement ............................................ 30
2.6.6 Employee satisfaction and productivity improvement .................................. 31
2.6.7 Customer satisfaction and productivity improvement ................................... 31
2.7 Final proposed research model ............................................................................ 33
CHAPTER 3: RESEARCH METHODOLOGY ...................................................... 34
3.1 Sampling and data collection ............................................................................... 34
3.1.1 Sample of research......................................................................................... 34
3.1.2 Questionnaire design ..................................................................................... 34
3.1.3 Data collection ............................................................................................... 35
3.2 Analyzing data plan ............................................................................................. 39
3.2.1 Scale evaluation ............................................................................................. 39
3.2.2 Factor analysis ............................................................................................... 40
3.2.3 Correlation analysis ....................................................................................... 40
3.2.4 Regression analysis........................................................................................ 40
3.2.5 Path analysis .................................................................................................. 41
CHAPTER 4: DATA ANALYSIS ........................................................................... 42
4.1 Data description ................................................................................................... 42
4.2 Measurement test ................................................................................................. 42
4.2.1 Reliability test ................................................................................................ 42
4.2.2 Validity Test .................................................................................................. 43
4.3 Hypothesis testing ................................................................................................ 45
4.3.1 Correlation analysis ....................................................................................... 46

4.3.2 Regression analysis........................................................................................ 47
4.3.3 Path Analysis ................................................................................................. 49
CHAPTER 5: RESULT DISCUSSION.................................................................... 52
5.1 Result discussion and implications ...................................................................... 52
5.1.1 Result discussions .......................................................................................... 52


5.1.2 Research implications .................................................................................... 55
5.2. Limitations and future research .......................................................................... 56
Reference .................................................................................................................. 58


LIST OF TABLE
Table 2.1: Summary of empirical study about determinants for
productivity improvement in service sector……………………………
Table 3.1: Measuring items for survey…………………………………
Table 4.1: Characteristics of the research sample……………………...
Table 4.2: Reliability test………………………………………………
Table 4.3: Factor analytical results: eigenvalue value (% variance)…...
Table 4.4: Pearson's Correlation Coefficient…………………………...
Table 4.5: Regression analysis results………………………………….
Table 4.6: Decompositions of Path Analysis…………………………..
Table 4.7: Model Fit Summary………………………………………...
Table 4.8: Hypothesis tested results……………………………………

19
36
42
43
44

46
48
50
50
51

i


LIST OF FIGURE
Figure 1.1: Productivity of Vietnam and some other countries
In 2018………………………………………………………………… 2
Figure 2.1: Proposed research model………………………………….. 33
Figure 4.1: Model Summary………………………………………….. 49

ii


LIST OF ABBREVIATION
APO: Asian Productivity Organization
GDP: Gross domestic product
OECD: Organization for Economic Co-operation and Development
WR: Waste Reduction
PM: Process Management
In: Innovation
TA: Technology Application
CF: Customer Focus
ES: Employee Satisfaction
CS: Customer Satisfaction
PI: Productivity Improvement

iii


CHAPTER 1: INTRODUCTION
1.1 Background and necessity of the research
1.1.1 Why improving productivity is important in Vietnam context?
Productivity is one of the most significant contributing aspects to the competitiveness
of any firm and each country in the context of rising international integration. Thanks
to increasing productivity, the number of physical products and services of society
increases. Increasing social productivity is the decisive factor to improve national
competitiveness, contributing to expanding international relations and cooperation,
promoting integration, etc (Te & Dong, 2013). Productivity enhancement is important
to all developing countries, including Vietnam. Because it means rapid and sustainable
development, getting out of middle income, and catching up with other countries in the
region.
Furthermore, Vietnam Government Office (2019), illustrated that Vietnam's labor
productivity growth rate reached 6% in 2018, and increase 5.77% from 2016 to 2018.
Additionally, the labor productivity of Vietnam in 2018 equals 4.521 USD/labor.
Moreover, in the report of APO (2019), Vietnam's per-worker labor productivity level,
calculated by GDP per worker, is equal to 9.300 USD/worker (GDP at constant basic
prices per worker in 2017, using 2011 PPP, the reference year 2017). However, to
compare with other countries in South East Asia, Vietnam’s productivity in USD is
still lower than others (See in Figure 1.1).

1


Productivity of Vietnam and some other
countries in 2018 (calculated in USD by PPP

2011)
Vietnam

11.142
19.918
24.849
29.499
30.115

Indonesia
Thailand
Singapore
0

20

40

58.687
60

80

152.418
100

120

140

160

180

Figure 1.1: Productivity of Vietnam and some other countries in 2018 (Source: Vietnam
Government Office, 2019)

1.1.2 Why productivity improvement in hotel industry of Vietnam is necessary?
The hotel business plays an essential role in the country's long-term development
goals, contributing to the aforementioned outcomes. However, the productivity of
Vietnam is at a very low level compared to Southeast Asia in particular and Asia in
general. Vietnam's tourist productivity, in particular, is significantly lower than that of
other Southeast Asian countries (only 40% of Thailand and 45% of Malaysia). The
labor productivity/worker in the tourism industry in 2017 only reached 77 million
VND (about 3,400 USD) (Hoang et al., 2019).
Besides, in Vietnam Tourism Annual Report 2019, the Vietnam National
Administration of Tourism calculated that the In 2019, the average room occupancy
was 52 percent, which was somewhat lower than the previous year (54 percent ). The
decline might be due to a bigger rise in supply relative to rising demand, as well as a
shorter duration of stay. Localities where tourist accommodations have grown rapidly,
like as Da Nang, have seen a drop in hotel occupancy, which has fallen below 50% in
certain cases.
Moreover, the COVID-19 pandemic caused a lot of upheaval in the Vietnamese hotel
market. Hotels, tour providers, and travel agencies were all significantly damaged
during this time, according to CBRE (2020). When break-even couldn't be achieved,
2


several hotels resorted to reduce staff working hours, lay off employees, and finally
close the hotel temporarily. According to Vietnam National Administration on

Tourism (VNAT) estimates, CBRE informed that Vietnam's tourism suffered a loss of
$5.9-$7.7 billion in the month of February – April 2020.
As a result, exploring and understanding what determinants of productivity
improvement in the hotel business are very important and imperative because an
increase in productivity can help hotels gain more advantage and competitive in the
market.
1.1.3 Research about productivity improvement in hotel business.
In the world, there has been a variety of research about factors' impact on productivity.
Some studies discovered the influence of scientific, technological development, human
capital, production management, and policies on labor productivity (Dong & Shi,
2019). Some studies also figured out that environmental management and labor
productivity have a negative relationship, meanwhile, quality management has a
favorable effect on labor productivity (Frondel et al., 2018; Ma et al., 2020). However,
the majority of the research focuses on the factors that influence productivity in the
manufacturing and construction sectors (Alaghbari et al., 2017; Munyai et al., 2017;
Chaturvedi et al., 2018; Wong et al., 2020) or the impact of leadership style on labor
productivity (Zehir & Narcikara, 2016; Yan, 2018; Olanrewaju et al., 2020).
Additionally, in the tourism sector, research about factors impact on productivity
improvement not as much as the manufacturing and construction sector. The majority
of the study is concerned with the influence of market segment, leadership style, and
management style (Joppe & Li, 2014; Witt et al., 2010). The other research considered
the impact of employee and employer relationship or workforce flexibility on labor
productivity (Mill, 2008; Simpao, 2018).
In Vietnam, meanwhile, recent research has concentrated on the influence of factors on
labor productivity or how to evaluate labor productivity in the construction industry
(Te & Dong, 2013; Huynh & Le, 2016). In the tourism and hospitality field, studies
focused on how to measure and calculated service productivity (Hoang et al., 2019;
Loan et al., 2009).
3

Thus, research on what factors influence productivity in the tourist sector is now
required for the development of the hospitality and tourist business. In order to be able
to pinpoint exactly what are the determinants of productivity improvement in the
hospitality sector, it is very important to select survey samples and survey subjects.
However, due to time and geographical constraints, the thesis could not survey hotels
in many cities. Therefore, the author has selected hotels in Da Nang city of Vietnam as
the research sample. The reason is that Da Nang city owns a series of titles: the most
livable city in Vietnam, the top 10 most attractive destinations in Asia, the top 10
emerging destinations of the world…. Therefore, Da Nang city becomes an attractive
destination, attracting millions of tourists every year. That means hotels in Da Nang
city are very diverse in terms of ownership type, star class, number of years of
operation, and so on. As a result, hotels in Da Nang city can guarantee the
representativeness of the sample.
Based on the research gap in Vietnam and in the world, as well as from the practical
needs of improving labor productivity in Vietnamese, the author chooses the topic:
“DETERMINANTS FOR PRODUCTIVITY IMPROVEMENT IN HOTEL
BUSINESS: THE CASE OF DANANG, VIETNAM” as thesis research.
1.2 Aims of research
1.2.1 Common purposes
With the title “DETERMINANTS FOR PRODUCTIVITY IMPROVEMENT IN
HOTEL BUSINESS: THE CASE OF DANANG, VIETNAM”, the purpose of this
research is to determine the influence of the variables: Waster reduction, Process
management, Innovation, Technology application, and Customer focus as well as the
mediating role of employee satisfaction; customer satisfaction on productivity
improvement in the hotel sector. Based on the findings of the analysis, author will
propose several solutions to improve productivity, which allow competitiveness
improvement.
1.2.2 Specific purposes
• To review the previous researches about productivity in the hotel sector.

4


• To examine the direct and indirect impact of factors (Waster reduction, Process
management, Innovation, Technology application, Customer focus, Employee
satisfaction; and Customer satisfaction) on productivity improvement in the
hotel sector.
• To propose solutions to improve the productivity of the hotel sector.
1.3 Research questions
• What factors related (both direct and indirect effect) to hotel productivity
improvement?
• How the factors have a direct and indirect impact on productivity improvement
in the case of Danang's hotels?
1.4 Research scope
The study was conducted for hotels in Danang city. Information was collected from
reports, handbooks, etc., and collected data through surveys between May 2020 and
September 2020.
1.5 Process and methodology
1.5.1 The research process
According to the review of some previous studies, this research has adopted those
research to build the research model. After that, primary data was collected from
Danang’s hotels. Then, these data are analyzed by SPSS 16 and AMOS 24 (free trial
version) software. The secondary data about labor productivity in the service sector of
Vietnam would be collected from the report and so on.
1.5.2 Methodology
1.5.2.1 Data collection method
The primary data, information will be gathered via a pencil-and-paper survey. This
survey's questions will all be graded on a 5-point Likert scale. The secondary data will
contribute to the formation of background information. Those data will be collected
from policies, reports, and so on.

5


1.5.2.2 Data analysis method
Data is coded, screened, and analyzed on the statistical software as following steps:
• Cronbach’s Alpha coefficient

• Correlation Analysis

• Factor Analysis

• Regression Analysis method
• Path Analysis

1.6 Thesis structure
Part 1: Introduction
Part 2: Content and results
Chap 1: Literature review

Chap 2: Research methodology

Chap 3: Analysis

Chap 4: Finding and conclusion

Part 3: Appendix and Reference

6

CHAPTER 2: LITERATURE REVIEW
2.1 Concepts of productivity
2.1.1 Productivity concepts and definitions
Productivity, according to Tangen (2005), can be characterized in a variety of ways.
Tangen’s research also emphasized that this is a wide phrase whose meaning is
dependent on its context. Furthermore, Alaghbari et al. (2017) conclude that
researchers should have different conceptions of productivity due to variations in
approach methods. It gives rise to a plethora of productivity concepts (Oglesby et al.,
2002; Lema, 1995). The research of Tangen (2005) and Alaghbari et al. (2017)
reviewed some of the definitions of productivity as below:
• Peles (1987) defined productivity as "operation performance," whereas Handa
and Adballa (1989) defined productivity as the ratio of outputs of commodities
and/or services to inputs of fundamental resources.
• Productivity is the most efficient use of resources; the act of creating more
items from the same resource boosts productivity. Alternatively, to create the
same amount of output using fewer resources (Bernolak, 1997).
• Furthermore, Arditi and Mochtar (2000) advocated calculating productivity as
total outputs in dollars divided by total inputs in dollars.
• Productivity is defined as the efficiency with which components of production,
labor, and capital create value (Bheda et al., 2003).
Productivity is also one of the most intriguing research and study subjects. As a result,
there have been several definitions of productivity. Productivity, according to Te and
Dong (2013), is a measure of the efficiency of a given application of labor in the
production process, characterized by a comparison of an output indicator (production
result) with the work required to create it. Some academics, on the other hand, feel that
productivity is one of the complexity factors. As a result, labor inputs and outputs
should be mentioned in productivity definitions. According to Quyen (2014)
productivity is split into two categories: individual productivity and societal
productivity. (1) Individual productivity is also described as an individual worker's

7


productivity as measured by the ratio of completed output to time spent working to
accomplish those goods. (2) The average GDP per employee working in the year is
used to determine social productivity, which is a criterion of the system of national
statistical indicators. Societal productivity is the degree of productivity of all resources
in a company or society as a whole. Thus, social productivity may be defined as the
working efficiency of a country's whole labor force.
Among the many definitions of productivity, the most widely used and popular
definition is the ratio of output and input. The ratio of output (goods and services)
divided by inputs (resources needed to produce output, such as labor or capital) is
commonly used to describe productivity (Heizer & Render, 2014). Productivity is
understood as the relationship between the outcome of the outputs with the used
inputs, denoted by the formula: Productivity = Output / Input (OECD, 2001; APO,
2019). APO (2019) also indicated that two major components must be included in the
inputs. There are labor and capital, such as buildings, plants, or machinery.
Furthermore, intermediary inputs like components, materials, or energy are referred to
as inputs in some particular cases.
Finally, a variety of meanings of productivity have come to the same conclusion or
identified productivity as a ratio of outputs to the combinations of inputs used to
produce those outputs (Gidwani & Dangayach, 2017).
2.1.2 Productivity measurement
Measuring company productivity is the capacity of an organization to completely
utilize its resources in order to achieve customer satisfaction. This is accomplished
through providing products and services that meet the expectations of customers in the
present market. Nonetheless, productivity is an important component in determining
an organization's business performance.
APO (2019) illustrated the following way to measure inputs and outputs of
productivity. Firstly, APO (2019) demonstrated two metrics of popularity outputs. (1)

Gross output measurement (based on the value of goods or services produced):
utilizing the prices of finished outputs. (2) Value-added metric (based on the value of
gross output generated minus all expenditure items): utilizing the value added by
8


producers to acquired products. Second, in terms of input measurement, there are three
main kinds of measurement mentioned: (1) Labor: the number of hours worked by all
people, directly and indirectly, involved in the production of the goods and services
being measured. (2) Capital: a term used to describe the flow of services from the
available capital pool. (3) Intermediates: the total worth of all intermediates utilized,
deflated to eliminate the impacts of price inflation.
These types of inputs and outputs lead to four available ways to measure productivity.
• Labor productivity = Outputs/(Labor inputs)
• Capital productivity = Outputs/(Capital inputs)
• Intermediate productivity = Outputs/(Intermediate Inputs)
• MFP = Outputs/(Combined labor, capital, intermediates)
APO (2019) also showed the other ways to measure productivity. They are (1) PerWorker Labor Productivity: This is a measure of labor productivity expressed as a
ratio of GDP per worker in US dollars. (2) Per-Hour Labor Productivity: This is the
amount of time worked per hour. (3) Total Factor Productivity: GDP per unit of
combined inputs.
On the other hand, Quyen (2014) proposed the main following ways to measure
productivity.
• Productivity calculated by-product: W = Q/T
W: labor productivity of one labor
Q: The total number of output calculated by product
T: The total number of worked labor.
• Productivity calculated by value: W = Q/T
W: Productivity
Q = value-added or revenue and T = a total number of employees or total

number of times (days, hours,…)
• Productivity calculated by worked time: t = T/Q
t: the number of labor resources used for product (in units of time)
T: worked time used
Q: the number of product
9


However, in terms of the service sector, especially the hospitality sector, the qualities
and characteristics of services have constrained productivity measurement. The
intangible nature of hospitality services, in particular, implies that objectively defining
and measuring the service outputs delivered is challenging. The assessment of
hospitality inputs and outputs is additionally complicated by the fact that hospitality
services are produced and consumed at the same time, as well as their perishability and
heterogeneity. The number of inputs and outputs, as well as their measurement units,
influence the complexity of the connection between them. In reality, there are several
methods for comparing inputs and outcomes. Ratio analysis is the most often utilized
in the hospitality industry (Sigala, 2004).
In terms of productivity metrics in the hotel sector, Mill (2008) stated that productivity
indicators often focus on labor effectiveness based on the ratio of outputs and inputs.
Mill proposes the following methods for measuring productivity in the hotel industry:
(1) Payroll ratio; (2) Sales per employee; (3) Sales per hour; and (4) Sales per
employee-hour. Hotel productivity was studied by Shaheen et al. (2018) as staff
productivity. According to Shaheen's study, employee productivity is defined as the
capacity to assist meet customer demand. Other financial measures, like revenue,
sales, and added value, might have intriguing elements of employee productivity.
2.1.3 Productivity and determinants in manufacturing
2.1.3.1 Productivity in manufacturing sector
When researching labor productivity in the Masonry Walls project, Santos et al. (2020)
defined productivity as the efficiency in changing inputs in outputs that combine with

the process's objective. On the other side, Dixit and Sharma (2020) proposed that
productivity in the construction project is ratio of work's performance or set of outputs
divided by inputs for produced outputs. Dixit and Sharma also noted, in the
construction industry, outputs are weight, volume or area, etc.; inputs are labor,
material, or machine.
Productivity is the rate where outputs (goods and services) are produced or operated
from the inputs used in the production process. In APO's definition of productivity,
inputs must include two main components. There are labor and capital, for example,
buildings, plants, or machinery (APO, 2019). Besides, in some special scenarios,
10


intermediate inputs such as components, materials, or energy are referred to as inputs.
On the other hand, in the report of OECD (2001), they also demonstrated that
productivity is often expressed as a ratio of a volume measure of output to a volume
measure of input used.
2.1.3.2 Determinants of productivity in manufacturing
Productivity is a complicated phenomenon that can be described and evaluated in a
variety of ways. As a result, conditions affecting labor production have been checked
and diversified. Other methods of determining these variables are likely to exist in
each industry (Ma et al., 2020). Several factors influence productivity in general,
including the pace of technological and scientific growth, the combination of human
resources, industrial structure, supply management, and policies (Dong & Shi, 2019).
Productivity, on the other hand, is influenced by a variety of influences in each
industry.
In terms of the manufacturing sector, Munyai et al. (2017) suggested three main
groups of factors that impact on productivity. They are (1) physical capital factors
(labor, material, machine, location, layout, and finance); (2) technological capital
factors (tangible asset; intangible asset); (3) management (planning, organizing,
leading, and control). Meanwhile, Fedulova et al. (2019) found out that factors of

changes in labor productivity are classified into five categories: (1) material and
technical factors (2) organizational factors; (3) regional economic factors; (4) social
factors; (5) structural factors.
Sanchez and Benito-Hernandez (2013) mentioned another specific factor, which
impacts on labor productivity of micro and small manufacturing companies in Spain. It
is effect of CSR policies on labor productivity. According to the findings of the study,
social responsibility leads to an improvement in labor productivity in the near run. The
increment is based on internal factors (process, production, promotion of innovation,
and employees care); however, the impact of CSR policies on labor productivity based
on external factors (relationship with stakeholder, environment) did not confirm.
In the construction sector, factors, which impact on labor productivity, focused on
diverse research and studies. In research of Alaghbari et al. (2017), factors that impact
11


on labor productivity categorized into 4 groups: (1) labor, (2) management, (3)
technical and technological, and (4) external. Among them, technical and
technological factors have the greatest influence on worker productivity.
Meanwhile, Nguyen and Nguyen (2018) discovered that the following sets of variables
influenced worker productivity on a construction site: (1) Labor, (2) Organization &
Management, (3) Motivation, (4) Working time, (5) Labor tools, (6) Working
conditions (7) Safety, (8) Project, (9) Natural environment, (10) Social-economic. The
result is supported by the research of Tam (2019).
2.2 The difference between productivity in manufacturing sector and service
sector
When divided by occupation, productivity is also perceived differently between
manufacturing and service industries. Manufacturing productivity is assessed more
easily than productivity in the services industry. Service sector productivity analysis is
relatively more difficult compared to manufacturing. It can be said that the
productivity analysis of the service industry is relatively more difficult than that of the

manufacturing industry because of the characteristics of the intangible output as well
as the many approaches to the problem.
First, there is a fundamental difference when comparing service productivity and
manufacturing productivity. In the study of Biege et al. (2013), services include such
characteristics as intangibility, heterogeneity, inseparability, and perishability; making
the application of the calculation method of manufacturing productivity in the service
lead to low productivity and inaccurate representation. The reason is that the product
or service includes the tangible part and the invisible. As for intangibility, the
customer's reception of the service and its consumption is simultaneous and disappears
immediately; Service experience is different from time to time, influenced by human
and environmental factors. On the other hand, Gallego et al. (2015) highlighted that
the lack of research about productivity in service can be explained by its nature. The
final product is ethereal and interactive. The absence of materiality of the service
offering is referred to as "intangibility". As a result, determining the service output and
distinguishing the output from the inputs for service production becomes complicated.
12


The second feature when calculating is that the service productivity approach is
diverse, multidimensional, and difficult to focus on as a whole. With physical
products, the estimation of output is usually not too complicated when the criterion is
the number of products that are easy to define and specific, and for services, it is
evaluated quite flexibly. As a result, the productivity measurement in the
manufacturing sector is quite different from productivity measurement in the services
sector.
According to Nguyen (2020), accurate measurement of productivity is crucial for the
management and monitoring of tourism activities, especially in Vietnam. However,
like other service industries, the calculation of productivity in tourism is also more
difficult than in the manufacturing industry in general because of the characteristics of
products and services as well as the way input costs are determined and outputs.

According to Mill (2008), service industry productivity growth has lagged behind that
of manufacturing industries. This is particularly true in the hotel business. This is due
to a variety of factors. Many of the successful operations management strategies used
in the manufacturing industry have not been embraced by hotels (Witt & Witt, 1989).
Therefore, in order to assess the current status and come up with solutions to improve
productivity for Vietnam's tourism industry, it is really necessary to research and
analyze to come up with an evaluation model.
2.3 Productivity in hotel sector
2.3.1 Productivity concept in the hotel sector
Productivity is a fascinating and complicated phenomenon in the economy as a whole.
As a result, increasing productivity is a difficult but necessary task for hotel and
hospitality management. According to De Jorge and Suarez (2013), in the hotel
industry, assumed productivity is a comparison of how successfully services process
transfer input to produce outputs versus the ideal potential for running it.
On the other hand, Hwang and Chang (2003) used the general term inputs/outputs to
define productivity in hotels in Taiwan. However, their inputs/outputs measures
included total guest room, number of floors for food and beverage (F & B), the
13


expense of operating, revenue from F & B, and other sources. Besides, Sigala (2004)
discovered productivity in both rooms hotel division and F & B. She found that
productivity in rooms division was determined by the inputs of the number of rooms,
payroll of front-office, expenses from administration, and general or demand
variability, come up with the outputs of room rate on average, number of room nights,
and non-rooms revenue. Shaheen et al. (2018) looked at hotel productivity as staff
productivity. Employee productivity is described in Shaheen's analysis as the ability to
help satisfy consumer demand. Other financial metrics such as revenue, sales, and
added value can have properties that are interesting aspects of employee productivity.
Previously, Houldsworth and Jirasinghe (2006) aimed at the ratio of managers’

physical and piece of work of one or more employees called productivity.
In conclusion, in the context of this thesis, the definition for productivity in the hotel
sector defined as “the ratio of an input (or inputs) to an output (or outputs)” (Mill,
2008, p.270). Inputs are the resources needed to produce and delivery services and
include the expenditure of direct raw material expenses (Sigala, 2004), number of
employees (Sigala, 2004); capital (Johnson & Ball, 2006). Meanwhile, outputs are the
outcome of the hotel business and include hotel sales and profits (Brown & Dev,
1999); market share (Barros, 2006); competitiveness in the market (De Jorge &
Suarez, 2013).
2.3.2 Productivity measures in the hotel sector
In a tourism productivity study, Blake (2006) shows three common measures of
tourism productivity. (1) output per worker, in this way single computations can be
made reducing the value that each worker brings to the company; (2) Second, the
output per hour of labor; the advantage of this approach is that it will not be affected
the number of hours worked overtime in a period and the results include both part-time
work and unused time paid to an employee. (3) Third, using Total Factor Productivity
(TFP), measure the output per input unit.
It can be said that the analysis of tourism service industry productivity is relatively
more difficult than that of manufacturing due to its intangible output characteristics
and multiple approaches to the problem (Hoang et al., 2019). Simpao's (2018) analysis
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backs up this theory. She showed that labor efficiency can be measured using a variety
of models and methods. However, because the hospitality business is qualitative in
nature, assessing outputs in the form of hotel facilities is difficult. Inchausti-Sintes et
al. (2020) showed that outputs per staff are the most important metric of efficiency in
the hospitality industry. However, the author confirmed that this metric can deceive
and misinterpret a region's efficiency (Coelli et al., 2005).
2.3.3 Determinants for productivity in the hotel sector

For many years, the hospitality industry recorded as the fastest development sector and
contributed lots of economic growth. So, as a result, there are number of research
about what factors impact on productivity, one main motivation dimensions of
improvement of hospitality sectors. According to Brown and Dev (1999), business
segment, leadership, and management style all influence productivity growth. Brown
and Dev's findings are backed up by Joppe and Li's (2014) study, as well as Witt's
(2010). Moreover, skills and human capital, physical capital, a competitive
environment, technology and innovation are highlighted as the key roles of
productivity (Blake, 2006). Finally, in De Jorge and Suarez (2013) study, these four
main determinants of that impact on the level of productivity of hotel are (1) Factor
outside the company (for example market competitors); (2) Company characteristic
(size, types, investment or localization); (3) Business dynamic; and (4) Public or
private property.
Mill (2008) proposed four determinants that enhance labor efficiency in the hotel
industry. Better workspace architecture, the implementation of improved job
procedures, more flexible staff scheduling, and organizational flexibility are all things
that can be changed. Some researchers explored the influence on labor productivity of
labor capabilities, the relationship between employers and employment or promotion
and incentives. (Simpao, 2018).
Park et al. (2016) used a different approach to show how internal and external
influences affect competitiveness (Sigala, 2004). Internal factors that have the most
impact on productivity are the number of workers (Hu & Cai, 2004), working hours,
labor flexibility (Kappa, Nitschke, & Schappert, 1997), human resource practices
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