[i]

MỤC LỤC SẢN PHẨM CÔNG BỐ

1. Factors affecting stock valuation multiples of listed construction companies in

Vietnam (2021). Conference Proceedings – 4th International Conference on
Contemporary Issues in Economics, Management and Business. Hanoi: National
Economics University Publishing House.

2. Nghiên cứu những yếu tố ảnh hưởng đến định giá cổ phiếu các công ty xây dựng
niêm yết tại Việt Nam (2021). Văn bản xác nhận ứng dụng đề tài – Công ty Cổ phần
Chứng khoán MB (MBS). Hà Nội.
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CONFERENCE PROCEEDINGS
4th International Conference on Contemporary Issues in

ECONOMICS, MANAGEMENT AND BUSINESS

November 11th – 12th, 2021, Hanoi - Vietnam

NATIONAL ECONOMICS UNIVERSITY PUBLISHING HOUSE

 [2]

CONFERENCE PROCEEDINGS
4th International Conference on Contemporary Issues in

ECONOMICS, MANAGEMENT AND BUSINESS

November 11th – 12th, 2021, Hanoi - Vietnam

NATIONAL ECONOMICS UNIVERSITY PUBLISHING HOUSE

 [3]

TABLE OF CONTENTS

SESSION 1: ACCOUNTING & FINANCE 1

ENTERPRISE FACTORS AFFECTING SECURITIES COMPANY'S
PROFITABILITY: EXPERIMENTAL RESEARCH IN VIETNAM....................... 1
Tran Van Hai
Hanoi University of Natural Resources and Environment
FACTORS AFFECTING STOCK VALUATION MULTIPLES OF LISTED
CONSTRUCTION COMPANIES IN VIETNAM ................................................. 20
Đã xóa Đã xóa Đã xóa Đã xóa Đã xóa Đã xóa
Đã xóa Đã xóa Đã xóa Đã xóa
Đã xóa Đã xóa Đã xóa

DETERMINANTS OF WORKING CAPITAL REQUIREMENTS:

THE CASE OF LISTED PLASTIC FIRMS IN VIETNAM................................... 39
Le Thi Kim Nhung, Tran Thi Thu Trang
Thuongmai University
GREEN CREDIT POLICIES IN VIETNAM BANKING SYSTEM
CASE STUDY AT BIDV ...................................................................................... 58
Tran Duc Anh
Monetary Policy Department, State Bank of Vietnam
Do Hoai Linh, Khuc The Anh
School of Banking and Finance, National Economics University
Lai Thi Thanh Loan
Joint Stock Commercial Bank for Investment and Development of Vietnam

SESSION 2: ACCOUNTING & FINANCE 2

EVALUATION OF THE EXPENSE RATIO ON NET REVENUE OF
MINERAL FIRMS LISTED ON THE HANOI STOCK EXCHANGE ................. 71
Do Duc Tai
University of Labor and Social Affairs
Vu Hung Phuong
National Economics University
 [4]

COST BEHAVIOR AROUND CORPORATE INCOME TAX RATE CUTS:

EVIDENCE FROM VIETNAMESE PUBLIC COMPANIES ............................... 85
Pham Thi Thuy, Le Ngoc Thang
National Economics University
SURVIVAL ANALYSIS OF CORPORATION FINANCIAL CRISIS:
A CASE STUDY OF VIET NAM ......................................................................... 98
Dinh Thi Ha
Thuongmai University, Vietnam
Phan Thuy Duong, Hoang Thi Thanh
University of Transport Technology, Vietnam
ESTIMATING LOCAL TAX EFFORT: THE CASE OF VIETNAM ................. 116
Nguyen Thi Kim Dung
National Economics University, Hanoi, Vietnam
Keshab Bhattarai
The Hull University Business School, Hull, United Kingdom

SESSION 3: ACCOUNTING & FINANCE 3

WORKING CAPITAL MANAGEMENT POLICIES, PROFITABILITY
AND RISK: CASE OF PLASTIC FIRMS IN VIETNAM ................................... 143
Tran Thi Thu Trang, Le Thanh Huyen
Thuongmai University
Bui Thi Thu
Hanoi University of Industry
THE RELATIONSHIP BETWEEN OWNERSHIP STRUTURE AND
FINANCIAL PERFORMANCE: EVIDENCE FROM VIETNAMESE
LISTED FIRMS .................................................................................................. 159
Luu Thi Thai Tam
An Giang University, Vietnam National University
DETERMINANTS OF CORPORATE DIVIDEND POLICY:
EVIDENCE FROM COMMERCIAL COMPANIES LISTED
ON VIETNAM STOCK MARKET .................................................................... 178
Le Thi Thai Ha
National Economics University
Truong Quang Minh
Thuongmai University
 [5]

FACTORS AFFECTING THE PROFITABILITY OF COMMERCIAL

BANKS IN VIETNAM: ADVANTAGES OF SIZE AND BAD DEBT
CONTROL ABILITY .................................................................................................. 196
Tran Thi Lan Anh, Do Thi Ngoc Lan
Hanoi University of Industry

SESSION 4: AGRICULTURAL ECONOMICS & ENVIRONMENT

APPLYING THE LIVELIHOOD VULNERABILITY INDEX (LVI)
TO ASSSES LIVELIHOOD VULNERABILITY TO CLIMATE CHANGE:
A CASE STUDY IN QUANG BINH PROVINCE .............................................. 213
Do Thi Ngoc Thuy
Hanoi University of Natural Resources and Environment
Vu Thi Hoai Thu
National Economics University
NATURAL DISASTERS AND HOUSEHOLD’S WELFARE: A CASE STUDY
OF RURAL VIETNAM ...................................................................................... 231
Kim M. Le
National Kaohsiung University of Science and Technology, Taiwan
Doan C. Le
National Yunlin University of Science and Technology, Taiwan
Quan. X. Tran
Quy Nhon University, Vietnam
AN ECONOMIC ANALYSIS FOR CLIMATE PROOFING MEASURES
IN CAI LON - CAI BE SLUICE GATE, KIEN GIANG PROVINCE ................. 245
Nguyen Dieu Hang, Nguyen Cong Thanh
Faculty of Environmental, Climate Change and Urban Studies,
National Economics University
Nguyen Hoang Nam
Institute of Strategy and Policy on Natural Resources and Environment
THE RELATIONSHIP BETWEEN CLIMATE CHANGE AND
MIGRATION IN THE NORTHERN VIETNAM: IS AGRICULTURAL
PRODUCTIVITY A MEDIATING CHANNEL? ................................................ 269
Nguyen Dang Khoa, Tran Thi Kim Thu
Faculty of Statistics, National Economics University, Vietnam
 [6]

FARM HOUSEHOLDS’ CREDIT ACCESS UNDER THE CONTEXT OF

URBANIZATION IN RURAL AREAS: A CASE STUDY OF FOUR
PROVINCES IN THE RED RIVER DELTA ...................................................... 291
Nguyen Thi Bich Hang
Nghe An College of Economics, Vietnam
Nguyen Viet Cuong
Financial Planning Department, Ministry of Labour,
War Invalids and Social affairs Vietnam

SESSION 5: BUSINESS ADMINISTRATION 1

DOMESTIC TOURISTS’ BEHAVIOUR AND COOPERATION IN
CORPORATE SOCIAL RESPONSIBILITY TOWARDS SUSTAINABLE
ECONOMIC DEVELOPMENT IN VIETNAM .................................................. 307
Nguyen Quynh Hoa
School of Economics and Management
Hanoi University of Science and Technology, Vietnam
EXPLORING FACTORS INFLUENCING VIETNAMESE HOUSEHOLDS’
INTENTION TO USE SMART HOME SOLUTIONS ....................................... 327
Pham Thi Thuy Linh
France Vietnamese Centre for Management Education
Nguyen Thi Hoang Yen
Posts and Telecommunications Institute of Technology
THE IMPACT OF PERCEIVED CSR OF E-COMMERCE WEBSITES ON
PURCHASE INTENTION: THE CASE OF THE HANOIAN CONSUMERS ............. 351
Le Thu Hang, Nguyen Thuy Linh
Foreign Trade University, Vietnam
Nguyen Thi Lien Huong
Thang Long University, Vietnam
LEAN APPLICATION IN THE AGRICULTURAL SUPPLY CHAIN
MANAGEMENT: A LITERATURE REVIEW .................................................. 378
Nguyen Thu Tram
Banking Academy of Vietnam
 [7]

SESSION 6: BUSINESS ADMINISTRATION 2

LOCAL RESIDENTS’ PERCEPTIONS OF CULTURAL TOURISM
DEVELOPMENT: CASE STUDY OF DAK LAK PROVINCE ......................... 399
Nghia Huu Le
School of Tourism, University of Economics, Ho Chi Minh City
Trinh Ngoc Phuong Nguyen
University of Social Sciences and Humanities, Ho Chi Minh City
FACTORS AFFECTING THE CLIMATE FOR INNOVATION IN
COMMERCIAL BANKS IN VIETNAM ............................................................ 419
Le Thi My Linh
Faculty of Business School, National Economics University, Vietnam
Nguyen Minh Phuong
Bachelor of Business Administration Program in English,
National Economics University, Vietnam
Nguyen Thien My
Bachelor of International Business and Trade, Ming Chuan University, Taiwan
Nguyen Minh Anh, Tran Ngoc Bao Tran
Bachelor of Business Administration Program in English,
National Economics University, Vietnam
IMPACT OF CULTURAL INTELLIGENCE ON STUDENTS'
INTENTION TO STUDY ABROAD: THE ROLE OF PERCEPTION
OF PERCEIVED VALUE ................................................................................... 444
Khuc The Anh, Bui Kien Trung
National Economics University
Pham Bich Lien
Saigon - Hanoi Commercial Joint Stock Bank
ORGANIZATIONAL JUSTICE AND ORGANIZATIONAL CITIZENSHIP
BEHAVIORS: AN EMPIRICAL STUDY IN VIETNAM ................................... 459
Pham Thi Bich Ngoc, Vu Dieu Linh
National Economics University

SESSION 7: ECONOMIC DEVELOPMENT & SOCIAL ISSUES 1

COMPLETING THE EXEMPTION POLICY FOR RESEARCH AND
DEVELOPMENT AGREEMENTS .................................................................... 471
Tran Thi Nguyet
National Economics University
 [8]

IMPACTS OF EXPORTS ON POVERTY REDUCTION IN KHANH HOA

PROVINCE ........................................................................................................ 481
Bui Quang Binh
Da Nang Economics University
Nguyen Thi Hai Anh
Nha Trang University
IMPLEMENTING UNIVERSAL SOCIAL INSURANCE IN VIETNAM
TOWARDS HUMAN ECONOMY .................................................................... 493
Nguyen Van Trang
Saigon University, Vietnam
DETERMINANTS OF PROPENSITY OF COOPERATION AMONG VIETNAM
LOCAL GOVERNMENTS IN FDI PROMOTION ............................................ 511
Kieu Quoc Hoan
Department of Human Resource Management, University of Commerce

SESSION 8: ECONOMIC DEVELOPMENT & SOCIAL ISSUES 2

COMBINING CIRCULAR ECONOMY WITH URBAN SUSTAINABILITY:
DIGITAL APPROACH TO MANAGE THE MUNICIPAL SOLID WASTE
IN HANOI .......................................................................................................... 541
Nguyen Cong Thanh, Vu Trong Nghia, Tran Quang Yen
Vi Thanh Ha, Truong Dinh Duc, Duong Duc Tam
National Economics University
SITUATION AND SOLUTIONS TO GUARANTEE ORGANIZATION
OF AGRICULTURAL LAND IN PHU THO PROVINCE TO IMPROVE
EFFICIENCY ..................................................................................................... 555
Nguyen Thi Minh Lan
Hung Vuong University
THE IMPACT OF PUBLIC SPENDING ON ECONOMIC GROWTH
IN THE RED RIVER DELTA REGION OF VIETNAM .................................... 575
Bui Duc Tho, Nguyen Thi Thanh Huyen, Pham Xuan Nam
National Economics University
Nguyen Tai Duc
Senior Finance Officer at CEO Group
 [9]

DETERMINANTS OF TECHNICAL EFFICIENCY OF DOMESTIC

SUPPORTING INDUSTRY FIRMS IN VIETBNAM ......................................... 600
Nguyen Quynh Trang
Vietnam Institute for Development Strategies,
Ministry of Planning and Investment
To Trung Thanh
National Economics University

SESSION 9: MACROECONOMICS
PARTICIPATION OF STUDENTS IN THE INFORMAL ECONOMY:
A CASE STUDY IN VIETNAM ......................................................................... 617
Tran Tho Dat, Ngo Mai Huong, Nguyen Hong Nhung
National Economics University
Le Ngoc Mai
Erasmus University Rotterdam
BANK COMPETITION, OWNERSHIP AND STABILITY
INTERRELATIONSHIP IN TRANSITION ECONOMIES: A CASE STUDY
OF VIETNAM ................................................................................................... 639
Le Thanh Phuong
Department of Economics and Management, Thuyloi University, Vietnam
IMPACT OF EXCHANGE RATE ON BALANCE OF PAYMENTS:
EVIDENCE FROM VIETNAM .......................................................................... 660
Nguyen Thi Dieu Chi, Nguyen Thi Thuy Trang, Luong Thi Thu Hang
National Economics University, Vietnam
WHAT DRIVES ECONOMIC GROWTH IN EMERGING COUNTRIES?
THE IMPACT OF FINANCIAL DEVELOPMENT, INSTITUTIONAL QUALITY
AND ICT PENETRATION ................................................................................. 671
Nguyen Thanh Phuc, Dinh Thi Thu Hong
University of Economics Ho Chi Minh City
THE GROWTH EFFECT IN THE VIETNAMESE STOCK MARKET:
A MISPRICING EXPLANATION ...................................................................... 704
Le Quy Duong
National Economics University
 [10]

SESSION 10: MARKETING & TOURISM 1

THE IMPACT OF SELF-CONGRUITY ON BEHAVIOR INTENTION:
THE CASE OF VIETNAMESE DOMESTIC TOURISTS.................................. 723
Pham Long Chau, Nguyen Duy Thanh
Thang Long University
THE IMPACT OF MORAL SENSITIVITY ON CARING BEHAVIORS OF
NURSING STAFF IN VIETNAM ...................................................................... 738
Tran Thi Mai Phuong
National Economics University
MARKETING ACTIVITIES FOR MUSEUMS THE CASE OF BAT TRANG
MUSEUM OF CERAMIC ART IN HANOI, VIETNAM ................................... 750
Do Khac Huong, Vu Tri Dung
National Economics University
Do Thi Phi Hoai
Vinh University
THE DETERMINANTS AFFECT THE COMPETITIVE CAPABILITY OF
RETAIL BANKING SERVICE: A CASE OF VIETINBANK ............................ 770
Hoang Ngoc Phuong
VietinBank
Le Huyen Trang, Nguyen Thi Phuong
Thang Long University
PURCHASE INTENTION TOWARDS CHINESE PRODUCTS OF
VIETNAMESE CONSUMERS: THE ROLE OF ETHNOCENTRISM,
COUNTRY IMAGE AND PRODUCT IMAGE ................................................. 796
Duong Thanh Thuy
QA global, JSC
Nguyen Ngoc Ha, Dao Trung Kien, Nguyen Van Ky
Dao Thi Lanh, Nguyen Tuan Thanh
Phenikaa University
 [11]

SESSION 11: MARKETING & TOURISM 2

FACTORS AFFECTING THE ADVERTISING AVOIDANCE BEHAVIOR ON
SOCIAL NETWORKS: A RESEARCH IN THE PAWNBROKING INDUSTRY ...813
Pham Van Tuan, Hoang Tuan Dung
National Economics University
Le Thi Diep Anh
University of Lincoln

THE TOTAL IMPACT MODEL SUPPORTS TOURISM DEVELOPMENT ..... 824

Nguyen Nam Thang
Ho Chi Minh City University of Food Industry

FACTORS AFFECTING BUSINESS CUSTOMER LOYALTY TO DELIVERY

SERVICE PROVIDER IN VIET NAM ............................................................... 843
Do Thi Lan Anh
Business Administration Department, Posts and Telecommunications Institute of Technology

FACTORS INFLUENCING CUSTOMER PARTICIPATION IN SERVICE

PRODUCTION AND DELIVERY: THE CASE OF ADVERTISING SERVICES.... 851
Le Pham Khanh Hoa, Nguyen Viet Lam, Nguyen Ngoc Quang
National Economics University
A MARKET STUDY OF E-LEARNING SYSTEM FOR LANGUAGE CENTERS
- CASE OF AI VIET NAM ................................................................................. 872
Vu Huy Thong, To Vu Luat
National Economics University

SESSION 12: MICROECONOMICS & SMEs

INVESTIGATING THE INFORMATION EFFICIENCY OF
CRYPTOCURRENCY MARKETS: A SHANNON ENTROPY APPROACH .. 895
Tran Thi Tuan Anh
University of Economics Ho Chi Minh City, Vietnam
ARE DIGITAL BUSINESS AND DIGITAL PUBLIC SERVICES A
DRIVER FOR BETTER ENERGY SECURITY? EVIDENCE FROM
EUROPEAN SAMPLE ....................................................................................... 908
Le Thanh Ha
National Economics University
 [12]

FACTORS INFLUENCING CHOICE OF HEALTH FACILITIES: A CASE

STUDY OF VIETNAM ...................................................................................... 940
Nguyen Thi Tuyet
Thang Long University
INTERNET OF THINGS - FROM PHILOSOPHY TO PRACTICE: A CASE
STUDY AT NATIONAL ECONOMICS UNIVERSITY .................................... 960
Nguyen Trung Tuan, Pham Minh Hoan, Nguyen Trung Kien
National Economics University
Luong Ngoc Tuan
Viet System Joint Stock Company
DETERMINANTS OF SELF-PROTECTION INTENTION ON SOCIAL
NETWORKS OF YOUTH IN VIETNAM .......................................................... 977
Tran Lan Huong, Nguyen Thi Ngoc Anh, Nguyen Thuy Linh
Pham Hong Anh, Mai Dai Hiep, Le Tri Nhan
National Economics University

SESSION 13: INTERNATIONAL ECONOMICS 1

THE IMPACT OF FOREIGN DIRECT INVESTMENT TO THE ECONOMIC
RESTRUCTURING OF HUNG YEN PROVINCE ............................................ 999
Nguyen Xuan Hung, Nguyen Thi Lan
School of Trade and International Economics,
National Economics University, Vietnam
ASEAN AND CHALLENGES OF CENTRAL ROLE IN RCEP ...................... 1019
Nguyen Quang Trung
Faculty of Logistics and International Trade,
Hoa Sen University, Vietnam
Q-INSIDE - A PROFITABLE FOREX TRADING ALGORITHM USING INSIDE
BAR PATTERN AND MACHINE LEARNING .............................................. 1027
Dang Minh Quan
National Economics University, Vietnam
IS DIGITALIZATION A DRIVER TO ENHANCE ENVIRONMENTAL
PERFORMACE? AN EMPIRICAL INVESTIGATION OF EUROPEAN
COUNTRIES IN PRE AND DURING COVID-19 ........................................... 1039
Le Thanh Ha, Tran Thi Lan Huong
National Economics University
 [13]

DETERMINANTS OF VIETNAM’S EXPORT PERFORMANCE, 2011-2020 .... 1069

Nguyen Van Cong
Faculty of Economics, National Economics University

SESSION 14: INTERNATIONAL ECONOMICS 2

IMPACT OF FOREIGN DIRECT INVESTMENT ON EXPORTS OF BAC NINH .... 1081
Xuan Hung Nguyen, Thi Phuong Thuy Nguyen, Thi Lan Nguyen
Minh Hang Tang, Thi Nhung Nguyen, Manh Dung Tran
National Economics University, Vietnam
RECENT TRENDS OF THE GLOBAL FDI: RISKS AND POLICY
IMPLICATIONS FOR VIETNAM ................................................................... 1110
Tran Thi Thu Hoai
Risk management Division, Military joint stock commercial bank
Phung Thanh Quang
School of Banking and Finance, National Economics University
Pham Quang Long
Development Strategy Institute, Ministry of Planning and Investment
FOREIGN DIRECT INVESTMENT SITUATION AND TREND OF SOME ASIA
COUNTRIES: OPPORTUNITIES FOR VIETNAM ......................................... 1120
Nguyen Dinh Toan, Truong Dinh Chien
Faculty of Marketing, National Economics University
PRODUCTIVITY AND EXPORT PERFORMANCE: EMPIRICAL EVIDENCE
FROM VIETNAM ............................................................................................ 1136
Nguyen Nguyet Minh, Dinh Viet Hoang
National Economics University
THE IMPACT OF FOREIGN DIRECT INVESTMENT ON PRODUCTION
TECHNOLOGY IN QUANG NAM PROVINCE ............................................. 1157
Nguyen Tan Van
The University of Danang

SESSION 15: HUMAN RESOURCES

EVALUATION OF BLENDED LEARNING MODEL QUALITY – AN
EMPIRICAL STUDY IN UNIVERSITES OF HANOI ..................................... 1173
Trinh Hoai Son, Le Quynh Trang, Pham Duc Toan
Le Hoa Chi, Vu Thu Phuong, Ngo Thuy Linh
National Economics University
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HUMAN RESOURCE MANAGEMENT AND INTRAPRENEURIAL

BEHAVIORS IN VIETNAMESE SUBSIDIARIES OF JAPANESE
MULTINATIONAL COMPANIES: DO WE NEED INNOVATIVE HUMAN
RESOURCE MANAGEMENT? ....................................................................... 1189
Tran Huy Phuong
National Economics University
THE INFLUENCE OF TALENT DEVELOPMENT PRACTICES ON TEACHER
PERFORMANCE IN GENERAL SCHOOLS IN HANOI ................................ 1209
Nguyen Thuy Van Anh
Faculty of Human Resource Management and Economics,
National Economics University
Pham Tung Anh
International School of Management and Economics,
National Economics University
THE FACTORS AFFECTING DEVELOPMENT OF HIGH QUALITY HUMAN
RESOURCE IN HIGH-TECH AGRICULTURAL ENTERPRISES IN VIETNAM.....1233
Le Thi Hien
Thuongmai University
THE DIRECT AND INDIRECT EFFECTS OF GREEN HUMAN RESOURCE
MANAGEMENT ON EMPLOYEES’ ORGANISATIONAL COMMITMENT......1252
Nguyen Ngoc Phu, Nguyen Ngoc Thang
Hanoi School of Business and Management, Vietnam National University
Tran Thi Van Hoa
National Economics University
Nguyen Thi Thu Huong
Ghent University

SESSION 16: TECHNOLOGY & INNOVATION

OPEN INNOVATION AND INTERNAL R&D EXPENDITURES: THE
MEDIATING ROLE OF ABSORPTIVE CAPACITY ...................................... 1267
Tran Lan Huong, Le Tri Nhan
Nguyen Thi Ngoc Anh, Nguyen Thuy Linh
Faculty of Management Science, National Economics University
THE IMPACT OF INFORMATION TECHNOLOGY ON IMPROVING
BANKING PERFORMANCE: EVIDENCE FROM VIETNAM ...................... 1287
Vu Thi Huyen Trang
Thuy Loi University
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DEVELOPING THE MECHANICAL INDUSTRY IN HANOI IN THE

CONTEXT OF INTERNATIONAL INTEGRATION AND DIGITAL
TRANSFORMATION ...................................................................................... 1302
Vu Tuan Anh, Tran Thị Mai Huong
National Economics University
IS E-GOVERNMENT A DRIVER TO ENHANCE ENTREPRENEURSHIP? AN
EMPIRICAL INVESTIGATION OF EUROPEAN COUNTRIES ................... 1318
Le Thanh Ha, Hoang Dang Khanh, Hoang Van Hop
Nguyen Thi Thu Hang, Le Lan Phuong, Pham Thi Ngoc Hanh
National Economics University
 [16]

FACTORS AFFECTING STOCK VALUATION MULTIPLES

OF LISTED CONSTRUCTION COMPANIES IN VIETNAM

Đã xóa Đã xóa Đã xóa Đã xóa Đã xóa Đã xóa Đã

xóa Đã xóa Đã xóa Đã xóa Đã xóa
Đã xóa Đã xóa Đã xóa

Abstract:
Stock valuation, using P/E and EV/EBITDA ratios, is favored by many analysts, but
has not seen much research in Vietnam. This study focuses on analyzing the factors
affecting stock valuation multiples of listed construction companies in Vietnam in the
period 2016 - 2020 because of the great development prospects forecasted in this
industry in the future. After performing panel data regression, the research results
show that there are 6 statistically significant factors affecting the P/E ratio, and 4
statistically significant factors influencing the EV/EBITDA ratio. Among them, beside
government bond interest rates, the only macro factor, micro factors such as dividend
payout ratio, debt-to-equity ratio, return on equity ratio, total amount of assets, total
asset turnover ratio, and revenue growth rate all have certain impacts on stock valuation
multiples. Therefore, the authors suggest that investors should clearly understand the
influence of these factors to make informed investment decisions; while construction
companies should carry out drastic measures and required changes such as
deleveraging, sustaining dividend payout rate and improving profitability rate in order
to keep listed stocks valuable to investors.
Keywords: Construction Industry, EV/EBITDA, P/E, Stock Valuation, Vietnam.

1. Introduction
Stock valuation is an issue that has attracted great attention from scholars in
recent years. There are two main approaches: absolute valuation method and relative
valuation method. This study focuses on the relative valuation method with two
representative ratios, the Price to Earnings (P/E) ratio and the Enterprise Value to
Earnings before Interest, Taxes, Depreciation and Amortization (EV/EBITDA) ratio.
While the P/E ratio indicates how much investors are willing to pay for a dollar of
profit and reflects the quality of the company's earnings and growth potential in the
future, the EV/EBITDA ratio shows how many years it will take the investor to
recover his capital with a constant EBITDA. It can be said that both P/E multiple and
EV/EBITDA multiple are very useful in valuing a company’s stock.
Vietnam is a country having a dynamic economy, in which the construction
industry plays a strategic role in the overall structure of the nation economy. In the
 [17]

period of 2016 - 2020, the construction industry group experienced strong

development with an impressive growth rate. Although the year 2020 witnessed the
lowest growth rate in the period, estimated at 6.76% (GSO, 2021), it is still considered
as a major progress in the context of the complicated situation caused by COVID-19
epidemic. Moreover, in recent years, especially in 2020, the construction industry has
benefited from the Government's public investment disbursement policies with a series
of key national infrastructure projects and social housing projects for low-income
workers. With great prospects in the future, the authors believe that construction stocks
will be more popular and valuable. Thus, it is very important to understand the factors
affecting the P/E and EV/EBITDA ratios of construction companies in order to make
the right investment decision. In Vietnam, there have been some studies on the topic of
P/E and EV/EBITDA ratios, but not many, especially for the construction industry.
Therefore, the study of the factors affecting the stock valuation of construction
companies listed in Vietnam in the period 2016 - 2020 was selected.
2. Literature review
Multiples of valuation, of which P/E ratio and EV/EBITDA ratio are typical,
have been widely applied in stock valuation, since this method is easy to comprehend,
and computations are also based on readily accessible sources of data. Along with the
development of stock markets around the world, studies about factors affecting the
relative valuation multiples of stock have been conducted in the last two decades.
On the international scale, numerous studies have been carried out to discover
the factors affecting the valuation multiples of stocks. Ramcharran (2002) stressed
the importance of economic growth when it comes to determining the market value
of stocks by studying the factors affecting the P/E ratio in 21 developing financial
markets. Another study concentrated on the effect of investor sentiment on the P/E
ratio of G7 nations was carried out by Rahman & Shamsuddin (2019). According to
their resecarch results, the dividend payout ratio has a significantly positive effect on
the quarterly P/E ratio in these markets. In contrast, short-term interest rates and
market volatility have a negative effect on P/E ratio. In general, there have been
abundant studies about this topic on an international scale, as opposed to the scarcity
of studies in Vietnam. However, the results obtained have also been largely different
from each other, despite the fundamental similarity in the data collection and research
methods. This can be attributed to the differences in the research subjects. Each study
derives its subjects from different stock exchanges in different nations. Therefore, the
level of development of the markets and the risk premium are also different.
Apart from the studies that provide an insight into the factors affecting a
particular relative valuation multiple, other studies have looked into the factors
 [18]

influencing a combination of various valuation multiples. The P/E ratio and

EV/EBITDA ratio have remained prevalent and are frequently used together by analysts
in the field of valuation. In fact, most assumptions in relative valuation tend to be implicit
rather than explicit, as opposed to discounted cash flow valuation where important
assumptions are often expressed in detail (Damodaran, 2016). Therefore, in some
situations, a single method of relative valuation may appear to be highly subjective and
biased. As a result, analysts usually use a combination of various valuation multiples
when building financial models in order to construct an appropriate price range, where
P/E and EV/EBITDA are popular valuation metrics. In addition, the P/E and
EV/EBITDA ratios are used jointly in investment strategies, as depicted by Persson and
Ståhlberg (2007) in an attempt to analyze the validity of the efficient market hypothesis.
Since the combination of many relative valuation multiples remains popular
in the field of valuation, some researchers have attempted to study the effect of some
fundamental factors on several multiples at once, instead of only one particular
valuation multiple. According to Drăgoi et al. (2016), the factor of market
capitalization displays a positive correlation with both the P/E and EV/EBITDA
ratios of 5 financial investment companies listed in Romania during the 10-year
period between 2004 and 2014, while some other fundamental factors such as return
on asset (ROA), return on equity (ROE) and reinvestment rate are negatively
correlated with the P/E and EV/EBITDA ratios of these companies. In addition, the
P/E and EV/EBITDA ratios of 1,500 industrial companies in the US (after
winsorization) have also been found to demonstrate high correlation of 0.79
(Mauboussin, 2018). These studies demonstrate a theoretical relationship between the
P/E and EV/EBITDA multiples, and the fact that some fundamental factors display
the same sign of correlation for both multiples. This serves as the basis for our
hypotheses, with the expected impact of the independent variables on both dependent
variables of P/E and EV/EBITDA being similar in our regression model.
In Vietnam, there have been a small number of studies about factors affecting
the valuation multiples of stocks. According to Hua (2013), dividend payout ratio and
financial leverage both have positive effects on the P/E ratios of listed companies on
the Ho Chi Minh Stock Exchange (HOSE) in the period between 2008 and 2012. In
contrast, the dividend payout ratio has a negative effect on the valuation multiples of
mining companies listed on HOSE (Phan and Nguyen, 2017). The results of the
aforementioned studies substantially deviate from each other due to the differences
in firm sizes, financial situations, and profits of the surveyed firms. Besides, factors
related to the uniqueness of each sector and the timing of the studies also contributed
to the differences in the results, since the data used for computation and comparison
of the stocks greatly depend on these factors.
 [19]

In summary, although the market value of stocks is an important factor in relative

valuation, the number of studies concerning this topic remains small, especially in
Vietnam. In addition, existing studies mostly focus on the P/E multiple while not paying
much attention to other valuation ratios, such as EV/EBITDA, and often take account of
the unique factors pertaining to each specific company. The contribution of our study lies
in the analysis of the impact of macroeconomic factors and the risk-related factors on the
valuation multiples of a construction stock in Vietnam, as well as concentrating on the
EV/EBITDA multiple along with the more widely studied P/E multiple.
3. Data and methodology
3.1. Research scope
This study focuses on evaluation of the factors affecting the multiples of stock
valuation, which herein are represented by the P/E ratio and the EV/EBITDA ratio,
of listed companies in the construction sector in Vietnam.
There are 54 companies within the construction sector that are listed on Ho
Chi Minh Stock Exchange (HOSE) and Hanoi Stock Exchange (HNX) chosen to
survey. The data on these companies are collected within the period between 2016
and 2020 to ensure that they are up to date. Since the time frame of the research scope
is 5 years, a total of 270 samples is analyzed.
3.2. Data collection
Data used in the research were collected from audited financial statements,
including the balance sheets, income statements, and cash flow statements of 54
construction companies listed in Vietnam in the period 2016 - 2020. In which, 24
companies are listed on HOSE and 30 companies are listed on HNX. Subsequently, the
authors calculated the necessary indicators that the financial statements did not show based
on the formula learned on the theoretical basis. In addition, data was also collected from
articles, documents and research works related to the topic both at home and abroad.
3.3. Research models and hypothesis
In this research, the authors used descriptive statistics, Pearson correlation
coefficient and carried out three regression models: pooled ordinary least squares
(OLS), fixed effect model (FEM) and random effect model (REM). Afterwards, the
authors used the F-test and the Hausman test to evaluate if the statistical model
correspond to the data, then used three methods to test the defects of the regression
model, including: multicollinearity test using the VIF coefficient, autocorrelation test
using the Wooldridge test, and heteroscedasticity test using LM - Breusch and Pagan
Lagrangian Multiplier. Lastly, the authors used the feasible generalized least squares
(FGLS) model to rectify the defects of the regression model.
 [20]

To understand how P/E ratio and EV/EBITDA ratio are being impacted,
eleven factors are chosen to examine the relations between these factors and stock
valuation multiples.
Table 1: Independent variables and expected impact on dependent variables
Impact on
dependent
Variable Meaning Unit Referred studies
variables
hypothesis
Gross domestic Percentage - Shamsuddin and Hillier
GDP +
product growth Decimal (2004)
Percentage - Peavy III and Goodman
Inf Inflation rate -
Decimal (1985); White (2000)
Treasury note rate Percentage -
T-note - Jitmaneeroj (2017)
(5-year term) Decimal
Vu and Nguyen (2010);
Beta Systematic risk Decimal -
Gupta (2018)
Fraction
D/E Debt to Equity ratio - Kulling and Lundberg (2007)
- Decimal
Dividend payout Fraction
DR + Constand et al. (1991)
ratio - Decimal
Return on Equity Fraction
ROE + Tahu and Susilo (2017)
ratio - Decimal
Common logarithm
Size Decimal + Doğan (2013)
of Total assets
Fraction Nia et al. (2012); Bhatia and
CR Current ratio +
- Decimal Srivastava (2016)
Total asset turnover Fraction
TAT + Patin et al. (2020)
ratio - Decimal
Percentage
Egrowth Revenue growth + Arslan et al. (2017)
- Decimal
Two multivariate regression models were designed to satisfy the demand of
the study:
P/Eit = β1GDPt + β2Inft + β3T-notet + β4Betait + β5D/Eit + β6DRit + β7ROEit +
β8Sizeit + β9CRit + β10TATit + β11Egrowthit + εi. (1)
EV/EBITDAit = βAGDPt + βBInft + βCT-notet + βDBetait + βED/Eit + βFDRit +
βGROEit + βHSizeit + βICRit + βJTATit + βKEgrowthit + εi. (2)
In which:
i stands for a firm, t stands for a year.
P/E is the Price to Earnings ratio, calculated by dividing the market share price
to net income after tax.
 [21]

EV/EBITDA is the Enterprise Value to Earnings before Interest, Taxes,

Depreciation and Amortization ratio, calculated by dividing the enterprise value (Market
capitalization + Total debt - Cash and cash equivalents) to earnings before interest, taxes,
depreciation, and amortization.
The meanings of independent variables are illustrated in Table 1.
4. Research results and discussion
4.1. Descriptive statistics of variables
Table 2: Descriptive statistics of variables
Variable Mean Std. dev. Min Max
P/E 9.371662 8.977966 0.56697 57.55556
EV/EBITDA 14.01104 8.93225 0.838016 67.6079
Size 12.03682 0.615012 10.41805 13.65578
D/E 2.790339 2.012776 0.044886 13.43604
DR 0.814369 1.002857 0 4.183444
ROE 0.110421 0.094188 0.000955 0.646668
CR 1.503968 0.852465 0.264648 7.876451
Beta 0.334609 0.597724 -2.66656 2.046891
TAT 0.764073 0.460562 0.031349 2.522202
T-note 0.04874 0.012792 0.0288 0.0669
GDP 0.06006 0.015812 0.0291 0.0708
Inf 0.01808 0.003351 0.0141 0.0231
Egrowth 0.086116 0.501605 -0.84487 4.671537

According to Table 2, the average values for the dependent variables of P/E
ratio and EV/EBITDA ratio between 2016 and 2020 are 9.37 and 14.01,
respectively. The standard error values for P/E multiple and EV/EBITDA multiple
both reached roughly 9, meaning that there are considerable differences between
different construction firms in the value of stock valuation ratios. The large gap
between the minimum value and the maximum value for both P/E and EV/EBITDA
shows how these multiples could greatly vary. It is also proved that firm policies
concerning the use of leverage and dividend payment also substantially differ
among listed construction companies, considering the number for the D/E and DR
variables.
 [22]

Figure 1: Changes in average values of P/E and EV/EBITDA of listed

construction companies in Vietnam by years
35
16.7434
30

14.3596
25 13.3453
12.5188
13.0881
20

14.2792
15
9.8893
8.9541
10 7.5577
6.178

0
2016 2017 2018 2019 2020

P/E EV/EBITDA

Figure 1 illustrates changes in the average value of P/E ratio and EV/EBITDA
ratio of listed construction companies in Vietnam from 2016 to 2020. The average
P/E value increased consistently (on average around 10-20%/year) throughout the
period, especially in 2020 when the number surged by 44% compared to that in 2019.
Meanwhile, there was a slight decrease in the index for EV/EBITDA ratio between
2016 and 2017, before the figures increased steadily by 6-8%/year from 2017 to 2019
and rose substantially by 16.6% in 2020. The increasing trend in the figures is
evidence that the construction industry has witnessed major development and
growing investment in its stocks in recent years. The COVID-19 pandemic is
considered as the main factor contributing to the considerable rise in both P/E and
EV/EBITDA values as more than half of the listed construction firms in the scope of
this research experienced negative growth in net income after taxes. In contrast, there
was a massive boost in the price of stocks in the securities market in 2020, as shown
in Table 3.
Table 3: Index of HOSE and HNX by years
2016 2017 2018 2019 2020
HOSE* 664.87 984.24 892.54 960.99 1103.87
HNX* 80.12 116.86 102.23 102.51 203.12
Note: * Closing price at the final trading day of the year.
Source: HOSE, 2020; HNX, 2020
 [23]

4.2. Pearson correlation coefficient

Table 4: Pearson correlation coefficient
P/E EV/EBITDA Size D/E DR ROE CR
P/E 1.0000
EV/EBITDA 0.3778 1.0000
Size 0.0812 -0.0016 1.0000
D/E -0.0088 0.4240 0.1929 1.0000
DR 0.4120 0.2543 0.0092 0.1438 1.0000
ROE 0.4443 -0.4450 0.1086 0.0040 -0.2296 1.0000
CR -0.0805 -0.2428 -0.2505 -0.4475 -0.0870 0.1176 1.0000
Beta -0.0010 -0.0429 0.1967 -0.0724 -0.1077 0.1179 0.1186
TAT -0.1513 -0.0725 -0.2967 0.1909 -0.0289 0.2065 -0.1065
T-note -0.2978 -0.1436 -0.0658 0.0302 -0.2060 0.1716 -0.0047
GDP -0.2436 -0.1451 -0.0299 0.0157 -0.2919 0.1160 0.0043
Inf 0.2240 0.1498 0.0416 -0.0172 0.2131 -0.1560 0.0100
Egrowth -0.1732 0.0570 0.0912 0.0645 -0.0346 0.1806 -0.0122

Beta TAT T-note GDP Inf Egrowth

Beta 1.0000
TAT 0.0030 1.0000
T-note 0.0018 0.1496 1.0000
GDP -0.1407 0.1341 0.6481 1.0000
Inf 0.1018 -0.1278 -0.5672 -0.7643 1.0000
Egrowth 0.1249 0.1593 0.0386 0.0410 -0.0545 1.0000

Considering the relative movements of variables in the P/E equation and

EV/EBITDA equation shown in table 4, the correlation coefficients all differ to zero,
implicating that all variables have relations with each other. Specifically, apart from
the numbers related to macroeconomic variables (GDP, Inf and T-note), most
correlation coefficients are lower than 0.5, with the highest figure being -0.4475 for
relation between CR and D/E. However, the multicollinearity phenomenon is still
likely to happen due to high correlation coefficients (higher than 0.5) between
macroeconomic variables, meaning a multicollinearity test using VIF values is
required. It is also hinted that the equations used in this research would likely not
have high significance levels due to the correlation values being relatively small.
Among the independent variables, ROE is the variable having the strongest
correlation with both P/E and EV/EBITDA (0.4443 and -0.4450, respectively).
 [24]

4.3. Pooled ordinary least square - OLS regression and Multicollinearity

Table 5: Pooled OLS regression
P/E EV/EBITDA
Variables
Coef. Coef.
GDP 10.42497 -7.945256
Inf 8.324411 103.5272
T-note -121.381** -25.12161
Beta 0.9753498 0.7486114
D/E -0.3183652 1.942681***
DR 2.798737*** 0.7648332*
ROE -32.84083*** -37.00874***
Size 1.667078* -1.688308**
TAT 0.2924566 -2.332411**
CR -0.257895 -0.422105
Egrowth -1.980113** 2.303406***
cons -3.31114 34.17381***
Adj R-squared 0.3309 0.3891
Note: ***, ** and * are 1%, 5%, and 10% significance level, respectively
Table 5 reports the regression estimates by using the pooled ordinary least squares
(OLS) method. In equation (1), considering variables with statistical significance, T-
note, ROE and Egrowth have negative impacts on P/E, while the effect by DR and Size
is the opposite. In equation (2), negative effects on EV/EBITDA are reported by ROE,
Size and TAT, whereas positive effects are made by D/E, DR and Egrowth. The adjusted
R-squared numbers suggest that under the OLS method, 11 independent variables
account for 33.09% and 38.91% of changes in P/E and EV/EBITDA, respectively.
Table 6: VIF coefficient
Variable VIF 1/VIF
GDP 3.11 0.321399
Inf 2.49 0.401879
T-note 1.83 0.545509
Size 1.42 0.702188
CR 1.39 0.717635
TAT 1.36 0.737046
D/E 1.35 0.741952
ROE 1.24 0.808839
DR 1.19 0.837415
Beta 1.17 0.85313
Egrowth 1.08 0.928127
Mean VIF 1.6
 [25]

The variance inflation factor (VIF) values for every independent variable are
relatively small (< 5) with the average VIF of 1.6, meaning there is no
multicollinearity phenomenon between these variables.
4.4. Verification of conformity of the model
The F-test and the Hausman test are conducted in order to figure out the best
suited model for this research.
At first, the F-test is conducted to verify whether the pooled OLS model or the
FEM model is more appropriate for the research:
Hypothesis: H0: The pooled ordinary least squares model (OLS) is suitable
H1: The fixed effect model (FEM) is suitable.
Table 7: F-test
F (11,258) Prob > F
P/E 13.10 0.0000
EV/EBITDA 16.58 0.0000

Results from Table 7 showed the equation for P/E ratio and that for
EV/EBITDA ratio both have (Prob > F) < 0.01. Therefore, with a 99% significance
level, we can reject hypothesis H0, accept hypothesis H1, and conclude that the FEM
model is more appropriately fit to the sample size than the pooled OLS model.
After which, the Hausman test is carried out to figure out which model among
the FEM model and the REM model be chosen for the research:
Regression: H0: Random effect model (REM) is suitable.
H1: Fixed effect model (FEM) is suitable.
Table 8: Hausman test
Chi2(11) Prob > chi2
P/E 9.96 0.5337
EV/EBITDA 17.34 0.0983

With 95% significance level, since both equations each have Prob > chi2
equals to 0.5337 and 0.0983 which are higher than 0.05, we do not reject hypothesis
H0 and conclude that the REM model should be chosen over the FEM model.
 [26]

4.5. REM model regression

Table 9: REM regression
P/E EV/EBITDA
Variables
Coef. Coef.
GDP 7.487826 -8.491676
Inf 1.754124 112.1922
T-note -115.0907*** -22.2986
Beta 0.5018728 0.4020822
D/E -0.3105095 2.242038***
DR 2.875685*** 0.5650186
ROE -33.77782*** -31.63185***
Size 1.502599 -1.52413
TAT -0.2228172 -4.42496***
CR 0.0082737 -1.225067**
Egrowth -2.077335** 1.662464**
cons -1.163649 33.64753**
Adj R-squared 0.3556 0.3932
Note: ***, ** and * are 1%, 5%, and 10% significance level, respectively
In model (1), consider statistically significant variables: T-note, D/E, ROE and
Egrowth have negative effects on P/E, while the effect of DR is positive. As for the
variables that are statistically significant in model (2), those that have negative
impacts on EV/EBITDA include ROE, CR and TAT, while the variables having
positive effects include D/E and Egrowth. According to the adjusted R-squared value,
11 independent variables in the REM model explain 35.56% and 39.32%,
respectively, for the two dependent variables P/E and EV/EBITDA, which are
slightly higher than the OLS model.
4.6. Defect testing of the REM model
Firstly, the autocorrelation test was conducted by applying the Wooldridge test:
Hypothesis: H0: There is no autocorrelation in the estimated model.
H1: There is autocorrelation in the estimated model.
Table 10: Wooldridge test
F (1,53) Prob > F
P/E 2.343 0.1318
EV/EBITDA 0.882 0.3518
 [27]

Applying Wooldridge test method, with 95% confidence, the results show that 2
models have (Prob > F) higher than 0.05, respectively. Thus, we cannot reject the hypothesis
H0, the REM model of both P/E and EV/EBITDA has no autocorrelation phenomenon.
Secondly, the LM test - Breusch and Pagan Multiplier was carried out to test
for Heteroskedasticity phenomenon:
Hypothesis: H0: The variance is constant
H1: The variance is not constant
Table 11: LM test - Breusch and Pagan Lagrangian Multiplier
Chibar2(01) Prob > chibar2
P/E 20.39 0.0000
EV/EBITDA 151.94 0.0000
Applying the given test, with 99% confidence, the results show that tow models
have (Prob > chibar2) less than 0.01, so we reject the hypothesis H0, accept H1, and confirm
that the REM model of both dependent variables has variable variance.
Thus, both models do not suffer from autocorrelation but have variable
variance. Therefore, to overcome this defect, the correction method with the feasible
generalized least squares (FGLS) model is used.
4.7. Adjustable model FGLS
Table 12 shows that in both research models, the macro variables are not
statistically significant, except the T-note variable in model (1) when it is significant
at the 1% statistical level and negatively impacts the P/E ratio.
Table 12: FGLS regression
P/E EV/EBITDA
Variables
Coef. Coef.
GDP 17.27341 -15.32625
Inf 91.18722 23.48159
T-note -91.08158*** -27.14791
Beta 0.414576 -0.1921864
D/E -0.269679*** 2.281952***
DR 2.909269*** 0.440532
ROE -28.42786*** -35.89962***
Size 2.060366*** -0.5691228
TAT 0.5588927 -2.514726***
CR -0.1966943 0.0304577
Egrowth -1.024281* 1.53152**
cons -13.29285** 21.21841***
Note: ***, ** and * are 1%, 5%, and 10% significance level, respectively
 [28]

On the other hand, the variables D/E, ROE and Egrowth are statistically
significant in both models. Specifically, all three variables have a negative impact on
the P/E ratio; meanwhile, with the model of EV/EBITDA ratio, only the variable ROE
has a negative effect, whereas the variables D/E and Egrowth have positive effects.
In addition to the variables mentioned above, the DR and Size variables also
have high statistical significance (1%) in model (1), and both have a positive impact
on the P/E ratio, while the variable TAT is only statistically significant in model (2)
with a negative effect on the EV/EBITDA ratio.
Variables CR and Beta are not statistically significant in both models.
Based on the estimation results of three regression models (the Pooled OLS
model, the REM model and the FGLS model), thanks to the ability to overcome defects,
the FGLS model was selected as the most appropriate and effective model in the study.
Overall, the EV/EBITDA multiple of listed construction firms are affected by
financial leverage (D/E), profitability (ROE), total assets turnover (TAT) and revenue
growth (Egrowth). The statistically significant variables affecting the P/E multiple of
listed construction companies include the risk-free rate (T-note), profitability (ROE),
financial leverage (D/E), dividend payout rate (DR), total amount of assets (Size) and
revenue growth (Egrowth). Our findings of the factors affecting the P/E ratio display
similarities and differences compared to the previous studies. However, since there
has not been much research into the EV/EBITDA ratio, it is difficult to compare our
results with previous studies.
The risk-free rate has a negative impact on the P/E ratio, which coincides with
the results attained by Jitmaneeroj (2017). A healthily high P/E multiple, which
indicates a decent financial performance and low risk, is usually associated with a
lower required rate of return and thus, a lower risk-free rate.
Profitability has a negative impact on EV/EBITDA multiple. A consistently
high ROE normally belongs to a market leader or a mature company, which is usually
associated with a lower EV/EBITDA. ROE also has a negative impact on the P/E
ratio, which differs from the results of Tahu and Susilo (2017). Normally, a firm with
a consistently high P/E ratio is usually a market leader that has reached a level of
maturity. Therefore, its ROE tends to stay stable instead of aggressively increasing.
Besides, since the denominators of both valuation ratios are figures related to firm’s
income, an increase in profitability would logically lead to decline in the number for
P/E multiple and EV/EBITDA multiple. Another reason is high ROE usually applies
for firms which use financial leverage at a major scale, which may be unpopular to
investors with risk aversion.
 [29]

Dividend payout ratio has a positive impact on P/E multiple, similar to the results
attained by Constand et al. (1991), since investors are more likely to favor companies
paying consistently high dividends, which increases the P/E ratio. Besides, a company
with a higher dividend payout ratio tends to attract investors, which increases its market
capitalization, leading to a higher EV/EBITDA ratio. This also accounts for the positive
impact of the dividend payout ratio on the EV/EBITDA ratio.
Financial leverage has a positive impact on the EV/EBITDA ratio. A high
financial leverage multiple indicates a high level of debt, which leads to a higher
enterprise value and thus a higher EV/EBITDA multiple. However, D/E has a
negative impact on the P/E ratio, which is the same as the results obtained by Kulling
and Lundberg (2007), since investors tend to be more conservative and reluctant to
invest in a firm with increasing debts, which leads to a lower P/E multiple.
Total amount of assets has a positive impact on the P/E ratio, same as the
results of Doğan (2013), implying that investors are more likely to favor companies
with larger sizes, which increases the P/E ratio.
Total asset turnover has a negative impact on the EV/EBITDA ratio. A high
total asset turnover is associated with the ability to generate revenue effectively from
assets, which indicates that the company is not overvalued and consequently lowers
the EV/EBITDA multiple.
Revenue growth has a positive impact on EV/EBITDA multiple. A
consistently high year-on-year revenue growth usually indicates a healthy financial
performance, leading to a higher enterprise value and thus, a higher EV/EBITDA
multiple. However, the factor has a negative impact on the P/E ratio, which is in
contrast with the results of Arslan et al. (2017).
It is clear from the result that beside the similarities, there are some differences
in our result surrounding the P/E multiple, compared to previous studies. Profitability
and revenue growth are factors showing correlations that are different from the ones
proposed in our hypotheses. The differences of our results, compared to previous
studies, can be attributed to a number of following reasons:
Firstly, the previous studies, as shown in our literature review, derived their
data from many different financial markets in different countries. These financial
markets vary in the level of development, risk-related factors such as market interest
rate, and risk premium. Therefore, each of them is subject to the peculiarity of the
different stock exchanges and our study is obviously not an exception.
Secondly, most of the previous studies focused on a selected sample of stocks
from a particular industry. The valuation of a stock from a specific industry depends
 [30]

on many different factors such as sales drivers, capital structure, or barriers to entry
and these are all unique factors in terms of valuation in every industry. This accounts
for the deviation of our findings from the results shown in the previous studies. Since
the construction sector has not been thoroughly studied on an international scale, the
fact that our study is partially different from previous studies is foreseeable.
Another information worth mentioning is how financial leverage and revenue
growth influence contrastingly towards P/E multiple and EV/EBITDA multiple. The
main reason is believed to be the increasing use of debt by a company would result
in greater enterprise value, but also culminate in decreasing stock price since
investors become wary of potential risk that accompanies with a high level of
financial leverage. Substantial increase in revenue usually applies to small-size firms
but has great potential for future growth, meaning that the incentive to borrow for
investment capital is often high among these companies, making them less attractive
with risk averse investors.
5. Conclusion and recommendations
5.1. Conclusion
This research focuses on finding and analyzing the factors affecting the stock
valuation of construction companies listed in Vietnam in the period between 2016
and 2020. The results show that only government bond interest rates within the group
of macroeconomic factors have a significant impact on stock valuation, specifically
the negative impact on the P/E ratio. Meanwhile, within the group of endogenous
factors of the companies, considering the statistically significant factors affecting the
P/E multiple, factors such as debt to equity ratio, return on equity and revenue growth
rate have negative effect, while dividend payout ratio and total amount of assets have
a positive impact. As for the EV/EBITDA multiple, return on equity and total asset
turnover ratio have a negative effect, whereas debt to equity ratio and revenue growth
rate have a positive influence.
5.2. Recommendations
Based on the study results, several recommendations to listed construction
companies and investors revolving stock valuation multiples are suggested:
Firstly, in terms of dividend, listed construction companies are asked to
develop a long-term dividend policy with the intention to maintain a constant
dividend rate in order to attract investors, especially for large-cap corporations not
having any more potential for growth. Meanwhile, it is recommended for investors to
buy stocks of companies which consistently pay dividends since these are usually
high value ones. It is also a sign that the company’s business is performing well and
is able to finance sustainable development.
 [31]

Secondly, in the aspect of a company’s growth, listed construction companies

with high profitability rate and major growth in revenue often have small-cap stocks
with unappealing valuation ratios. Therefore, these firms should prioritize business
expansion, enhancing competitive advantages and maintaining strong yearly growth
to invite investors. With this group of companies, investors are suggested to carry out
comprehensive research into them, and only buy stocks with the potential of
becoming large market capitalization ones in the future.
Thirdly, regarding financial leverage and capital efficiency, it is needed for
listed companies to evaluate the current use of debt policy, and to come up with
solutions to improve capital efficiency while strengthening financial autonomy to
lower the amount of debt. On the other hand, investors are advised to invest in firms
with large financial resources and be cautious with those having large debt. Leverage-
used companies often have poor stock valuation ratios due to being highly risky for
individuals to invest if they lose the ability to meet debt obligations. Also, investors
should take note of a company’s asset turnover to evaluate its use of capital.
Finally, in terms of risk-free rate, despite being the factor causing negative
effect on stock valuation ratios, the recent 5-year data have shown a decline in
government bond interest rates, and this is expected to continue its trend in the long
run. However, the short-term period may witness an increase in the risk-free rate as
the government introduces fiscal policies to boost the economy after being devastated
due to the COVID-19 pandemic. Therefore, listed construction companies should
have preferential treatments for investors to keep the stock price high and maintain
healthy valuation ratios. For investors, they are suggested to keep track of government
policies and the risk-free rate to build a reasonable portfolio.
Apart from the suggestions above, the researchers propose other
recommendations for investors regarding the process of valuing construction firms
listed in Vietnam. P/E ratio and EV/EBITDA ratio are both important metrics that
investors need to estimate in order to determine the market value of firms in the future,
which facilitates appropriate decision-making. Therefore, an insight into the factors
affecting these metrics will help investors generate objective, relevant and appropriate
estimations. This is not only the fundamentals for the decision-making process but also
the basis of determining the firms’ market value. In addition, investors may propose
comparisons between the multiples of valuation of construction firms in Vietnam and
those of other exchanges in other nations. Hence, they can gain a panorama of the
construction sector and evaluate the potential for further development.
5.3. Research limitation and future research directions
Aside from the obtained results, the study still has some limitations. Firstly,
the research was limited in terms of time and sample selection. Based on variable
 [32]

requirements, the authors did not consider firms with negative profits in the fiscal
year, therefore, this study only used information of 54 construction companies listed
on the Vietnamese market, and the time scope was also limited to the period 2016 -
2020. Secondly, the data source was mainly taken from the financial statements of
each company. Thus, the statistics might not be reliable. Thirdly, the research topic
only focused on relative valuation methods, specifically the P/E ratio and the
EV/EBITDA ratio. Finally, the authors only put our minds to evaluate
macroeconomics and endogenous factors of enterprises. After looking through other
articles and studies, the team found that there were still other independent factors that
had not been taken into account, such as variables related to investors’ psychology.
Although the research has limitations, these are also gaps and opportunities
for the topic to be improved in the future. Other research groups can conduct similar
studies with different sample size and time scales to make the research more objective
and comprehensive. Subsequent studies are suggested to study more deeply about
other factors affecting stock valuation multiples which are not examined in this
research, such as investor psychology, risk appetite, stock market trends, etc.
Furthermore, expanding the research to other stock valuation methods also helps the
topic to further develop.

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Corresponding author can be contacted at: Đã xóa Đã xóa Đã xóa

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