Luận văn factors affecting the young vietnamese customer's willingness to participate in fashion

electronic- word of mouth -WOM credibility and influencer marketing on subjective norm Design/Methodology/Approach: The research uses survey as a quantitative method, he questionnaire i

VIETNAM NATIONAL UNIVERSITY, HANOL

INTERNATIONAL SCHOOL

GRADUATION PROJECT

KACTORS AFFECTING THE YOUNG VIETNAMESE

CUSTOMERS’ WILLINGNESS TO PARTICIPATE IN

FASHION RENTALS

Nguyen Thi Thoa

Hanoi, Year 2020

VIETNAM NATIONAL UNIVERSITY, IIANOI

INTERNATIONAL SCHOOL

GRADUATION PROJECT

FACTORS AFFECTING THE YOUNG VIETNAMESE

CUSTOMERS’ WILLINGNESS TO PARTICIPATE IN

FASHION RENTALS

SUPERVISOR: MBA Pham Huong Trang STUDENT: Nguyen Thi Thoa

STUDENT MD: 16071115 COHORT: TR20164

MAJOR; International Business

Hanoi, Year 2020

in this project arc clearly cited according to regulations

I take full responsibility for the fidelity of the number and data and other contents of

ACKNOWLEDGEMEXT

First of all, T would tke to express my deep thankfulness 10 my supervisor, MBA Pham Huong Trang who inspired me to do this study, guided me how to make it done properly, and spent time on helping me to correct it during last time Without her cnthusiasm, great passion and useful comments, T might not, complete this paper within a limited time frame

J also would like to express the sincerest gratitude to all the lecturers and professors

of International School- Vietnam National University, who gave me the necessary knowledge about international business and other majors during four years T studied here That helped me a lot when | conducted this research

Besides, I would like to say thank you to all the participants whe helped me answering the questionnaire so that I can get data to do the study I really appreviated those who sport, time on kelping me completing the survey

Also, T would like lo send my sincere gratituste la my families and friends for their unconditional love, perseverance, encouragement and emotional support Without

them, I might not feel strong enough to finish the research

Finally, I wish all the best will come to my supervisor and all the lecturers and professors of International Schoo!- Vietnam National University Wish everyone

will have more happiness in life and more sucvess in career

Thanik you all very mmueb!

Student, Nguyên Thị Thoa

CHAPTER 2: LITERATURE REVIEW

2.1 The sharing cconomy and the online fashion renfal serviee 11 LLL The basic knowledge related to shharÌng ©C0HGEJ eo 1] 31.2 The online [ishiow renfdÌ serV€€ co "— 2.2 The characferistics of generation Z (gen Z/ ¬

Roam

3.5.1 Reliability analysis by Cronbach's alpha 36

4.2.1 Reliability of perceived usefuiness- PU scale - - 45 4.2.2 Reliability of perceived ease of use- PEU scale - 45 42.3 Reliability of Interpersonal influence- II scale - - 46 4.2.4 Reliability gƒ E-WOM credibiliiy —

0ƒ Perceived beliavioral control- PRC sedle 4T

429 Reliability of Behavioral intention- BI scale 4 4.3 Exploratory Factor AnalysÌs, ch ersereeeeo,.4Ể 4.4, Confirmatory Factor Analysis (CFA) ¬"

4.6 Sfructural cquation modeling (SÉM), "—

4.6 Bootstrapping and Hypotheses tcstcd resulfs

CHAPTER 5; DISCUSSIONS, CONCLUSIONS AND LIMITATIONS

APPENDIX 2: QUESTLONNAIRE (Vietnamese version)

APPENDIX 3: TLE PRIOR STUDIES 1

APPENDIX 4: TILE PRIOR STUDIES 2

TABLE OF NOTATIONS AND ABBREVIATIONS

In the research, these letters are abbreviated to easy follow The below table would

‘be described in detail,

LIST OF TABLE

‘Table 1: ‘The definition of variables

Table 2: Demographic information of respondents

Table 3: Five-point Likert scale

‘Table 4: Measuring items for questionnaire

Table 5: The rule of alpha value

Table 6; The using of factor loadings

‘Table 7: ‘The acceptance level of Model fit

Table 8: The cistribulion of respondents’ character:

Table 9: Descriptive statistics of 375 observations

‘Table 10; Reliability Analysis

Table 11: KMO and Bartlett’s Test

‘Table 12: The Pattern Matix

Table 13: Model fit summary

Table 14: Standardized Regression Weights

‘Table 15: the value of CR and AVE

Table 16: The value of AVE and MSV

Table 17: Regression Weights

Table 18: Standardized Rogrcssion Wcighis

Table 19: The order of factor's effect on variables

Table 20: Boolstrapping wilh sample size N 1000

‘Table 21: Hypotheses Tested Results

LIST OF FIGURE

Eigure 1: Proposed Research Model

Figure 2: Roscarch pEOCGdUEE, is nen ree Figure 3: The measurernent model

Figure 4: The structural maded

electronic- word of mouth (-WOM) credibility and influencer marketing on

subjective norm

Design/Methodology/Approach: The research uses survey as a quantitative

method, he questionnaire including, demographic questions, behavioral intention, attitude toward behavior, subjective norm, perceived behavioral control, perceived usefulness, perceived ease of use, interpersonal influence, E-WOM credibility and influencer marketing was developed and delivered online to 375 people After that,

the SPSS26 and AMOS20 were used to analyze the collected data

Findings: This study contributes to the extant literature concerning factars

impacting the willmgness of cuslomer lo parlicipale in fashion rental Firstly, the xosults show that attitude toward behavior, subjective norm and porccived

behavioral control have positive and significant relationships with behavioral

intention of people TL emphasizes that behavioral intention can be mosL strongly influenced by each individual’s ability in relation to resources, such as: time, money Secondly, the positive relationships between attitude and two other factors perceived usclulness and perecived case of usc are also highlighted Iu which,

perceived ease of use has higher influence on attitude compared with perceived

usefulness Lastly, all three clements: interpersonal influence, E-WOM credibility,

and influencer marketing have positive impacts on subjective norm Influencer

marketing has the highest level of effec compared with the twa remaining variables

Implications: ‘The research findings help to understand factors that might influence

customers’ intention to rent the clothes online in Vietnam From there, it is useful

for managers, or marketers to catch the key predictors of customers’ behavioral intention Besides, this provides basic knowledge related to sharing economy,

online fashion rental, generation Z with empirical evidence that can be taken into

considerations in the busmess stralegies

Originalily/value: This study focuses on gen 7, which is the most polenlial group

of customers Besides, the study expands the TPB model by exploring the impacts

of other dimensions of subjective norm namely E-WOM credibility and influencer marketing,

Key words: (ashion rental/ online reviting clothes, generation 7, slaring economy,

‘TPB model, ‘TAM model, behavioral intention, attitude toward behavior, subjective

norm, perceived behavioral control, perceived usefulness, perceived ease of use, interpersonal influence, F-WOM credibility, and influencer markeling

kở

1.1

CHAPTER 1: INTRODUCTION

In the Vietnam context, fashion rental service has appeared for a long time, but it

is imited to some types of costumes such as wedding or dancing dress and in the

form of store shopping Lence, the online renting clothes is still quite new to

Vietnamese customers Besides, by 2025, Generation Z , who were born after

1995, will account for about 25% of the national workforce, and are equivalent to about 15 million potential consumers (Nielsen, 2018) The report of Nielsen alsa

shows that this group of people likes to experience new services or new trends, and they have a higher awareness of online services as well ay social issues

Therefore, this research not only shows the potential of a special type of fashion -

clothing rental service in Vietnam, but also emphasizes the key factors that influence the Vietnamese younger customer’s decision to experience online

hiring

This chapter consists of five sections Initially, the chapter elaborates background

for (he study (section 1.1) before the prior studies and research gaps are presenled (section 1.2) Subsequently, the research objectives and research questions are emphasized (section 1.3) After that, a brief description of the research methods is provided (seetion 1.4), which is follawed by a presentation of rescarch findings (section 1.5) ‘Ihe chapter closes with a presentation of the thesis structure (section

1.6)

Background of the study

In recent years, sharing economy is a popular topic among companies and academic researchers It is defined that people share their intangible assets and underutilized tangible assets for money or for free with the help of the Internet and online platforms (Garog, 2018) A decade ago in a world where Airbnb had not changed the tourism indusiry, sleeping in strangers’ houses rather than in a well-known hotel

would have considered a little dangerous Before Uber, or Grab dominated the

transportalion, getting into a stranger's car mieht haye unpreecdented lí can be seen

that, the sharing economy is gradually replacing the ownership economy, becoming

4 polsnlially profitable business model in all [elds (Tu and Hu, 2018), Sharing economy is also known as collaborative consumption, which is expected to diminish social problems, such as poverty, excessive consumption of resources, and environmental pollution, Therefore, some authors arc trying lo rescarch and expec! positive effects of sharing economy on the fashion industry - one of the most polluting industries in the world (Armstrong et ai., 2016; Yoon and Kim, 2017; Tran, 2018, Tang and Joyner Armstrong, 2018, Tu and Hu, 2018; Lee and Chow, 2030)

Although fashion rental is not a new phenomenon, an increase in environmental

concems has made hiring clothes more popular than ever, leading to a global trend

According to a reporl of damaging parliamentary commitlec, the textile industry discharges 1.2bn tons of CO2 per year, and is responsible for the consumption of

huge quantities of water, while 35% of the microplastics in the ocean come from the

synthetic fibres in abandoned clothing (PerfeciSouremg, 2019) Therefore, [asl

fashion is assessed as the second dirtiest industry, only coming in behind the oil

industry in terms of pollution (AlterNet, 2015) Although the perception of people

about nogative impacts of fast fashion is increasing by education, or propaganda, the actual demand for shopping shows no sign of slowing down ‘Ihe research of Hubbub Foundation suggests that one in six young people say they do not feel able

to wear an outfit again once it has appeared on social networking sites (Cart-

Morley, 2017) And, nearly half of young women participants feel like wearing different clothes every time they go out As the dark side of fast fashion is quickly being exposed fo the world and the demand is constantly mercasing, the awareness

of sharing “wardrobes” makes important sense for the planet's sake, especially environmental protection (AllerNe!, 2015) Based on the principle of sharing economy, renting clothes would be an cffcctive solution that brmgs many benefits

in terms of sustainability fashion, such as maximizing usage and reducing, the

impact of goods that were disvarded after limited use (Rachel Botsman and Rogers, 2010) Moreover, It is not only an eco-friendly option, but also brings economic

denelils fo customers as sharing the cost of products and reducing the burden of

ownership (Rachel Botsman and Rogers, 2010; Lang and Joyner Armstrong, 2018,

Lang, Li and Zhao, 2019)

This study classifies clothing rental inte two categories based on Ihe lypes of

sharing economy, brand-to-consumer and peer-to-peer Firstly, for brands-to-

consumer model, the fashion firms offer list of service packages with a fixed

tmonhly price, and customers who parlieipale in this service package will have

unlimited rights to hire clothing products in corresponding catalogs Such as: ‘The United States is currently the leader of fashion rental industry, specifically Rent the

Runway company, which bogan operating in 2009, provides one month's

subscription cost of 160$ A United Kingdom company has also started this service

with a monthly cost of 100$ Other brands like Mang Walk, My Wardcoat HQ and

Front Row, H&M provide rental services for their premium designs and Inxury

products on a monthly subscription cost plus rental fee per item, typically ranging

from 10% to 15% of the selling price Secondly, for peer-lo-peer model, each

individual can jom in both the provision and use of the service, making own

agreements on costs or transport or example: Merri Smith and Violet Gross

Jawmched thew slartup- Tuleric, wioch ts the wardrobe rental platform business

They look for women interested in both borrowing and lending, resulting that roughly 80 percent of platform's members are active on both sides of rental equation

(Biins, 2019) Therefore, Tulerie not only helps members rent and eam money on

their wardrobes but it gives them a way to offload items that no longer have any place in their closets

Tn addition to the transformation in faskrion trends, the customers! shopping habils

are also gradually shifting from store shopping to online shopping Advances in e- commerce technology have made online fashion renting more convenient and

accessible, crealing favorable conditions for development of this scrvice

(Carl-Morley, 2017) In fact, the online fashion rental market has recently been expanding

exponentially in many countries, for examples: Girl Meets Dress in the U.K., Rent

the Runway inthe U.S., Meilizu in China, Lend My Trend, and HUMM (Gullsiand

Kdbring, Lebner and Mont, 2016, Lai ef af, 2018), According to a report of

Technavio organization in 2019, the potential development of this service is

cuormous, when il only accounted for 1% of the fashion market but the growth rate

reached 9.98% (Yechnavic, 2019) Allied Market Research also found that the

global clothing rental market was valued at approximately $1015 million in 2017 and is estimated to reach $1,856 million by 2023 (Iqbal, 2017)

‘The focal point of this study is generation Z which is the group of people who were bom after 1995 with the high level of education, information technology, and

innovation (Priporas, Stylos and Fotiadis, 2017) There are some reasons why the

study chooses gen Z to analyze Firstly, It is the youngest and largest consumer

group across all generations from 2017 to 2030 (Priporas, Stylos and Kamenidou, 2019) Gen 7 is considered as the main potential consumer group of companies in

many fields, especially technology, entertainment activities or fashion industry

(Bassiouni and Hackley, 2014) A report conducted by Barclays bank in 2018

identified that gen Z plays a key role in the fuhwe cconomic development, because

they can represent 40% of consumers in the United States, lurope and BRIC

(Brazil, Russia, Tia and China) by 2020 Secondly, gen 7 is the first group of

people who were born into a digital world, they live online and are heavy users of technology (Gemstein, 2015) Therefore, they have a high awareness of online

trading and easily take advantage af online resources to evaluate products before

shopping, Lastly, A research identified that Gen % is characterized as economically conservative and social activists (Barclay, 2015) These people not only think about

personal salisfaclion, but also are more sensilive to social impacts (Abdullah,

Mahadee Ismail and Albani, 2018) ‘Therefore, this research will focus on surveyed

participants — gen Z to shed light on the factors that influence this group's behavior rogarding fashion rental trends

1.2 ‘The prinr studies and Research gap

‘The studies on human behavior have resulted m a multitude of theories and

assumptions wilh many arguments from psychologists and researchers (Martin

Luenendonk, 2017) Not all people react in the same way, or behave in the same

manner, even under the exact same situation There are various factors which

impact behavior of people Those are what psychologists and thinkers have been

trying to study and make sense of in the past few decades (Martin Luenendonk,

2017) In terms of human behavior, behavioral intention also becomes an interesting

topic Tt refers lo the tendency for which a person wants to lake a specific action

‘Theory of planned behavior is the most popular model that is used to analyze factors affecting behavioral intention It is adopted in many fields and previous

yesearches: edusalion (Knander and Koschmieder, 2019; Rana ø/ 2È, 2019), heaHh (Lee et ai, 2016; Gabriel, Iĩoch and Cramer, 2019), transportation (Cristea and

Giheorghin, 2016, Potard et al., 2018) In this study, related to fashion field, factars

affecting the behavioral inlontion to engage in rentiry, clothes will be explored and

identified

Although the trend of hirmg clothes is getting more atisntion in the world, the umber of studics on this topic is still low and limited compared to other topics

xegarding behavioral intention research In which, most studies foeused ơn

exploiting factors thal affect customers’ behavior, based on the maim TPB

theoretical model and incorporating a number of other theoretical foundations, such

as IDT, VBN, EVA or TRA (iran, 2018; Tu and Ilu, 2018; Lee and Chow, 2020)

The results of these studies show that attitude and subjective norms are the main

factors to predict customers” intention to engage in fashion rental, especially online service Following this motive, the paper continues to build a research model, based

on the TPB and TAM theory, to deeply measure the influence and relaionship

among variables that shape customers’ behavior

Besides, there are two gaps in previous studies that will be improved in this article Firslly, in prior rescarches, the authors often focused on analyzing variables relalcd

to attitudes such as compatibility, relative advantage, personal imovation, ecological importance, or psychological ownership (Becker-Leifhold, 2017; tu and

Hu, 2018; Lee and Chow, 2020) Meanwhile, only inlerpersimal er sooval influence

of subjective norms that are associated with relative's opinion, friend's suggestion or worth of mouth review has been highlighted into relationship with customers!

intention (Becker-Leifhold, 2017; Tu and Hu, 2018) Hence, in this study, the

influence of factors, in term of subjective norms, will be explored further to provide deep understanding about young customers’ intention Secondly, another limitation of previous researches is relative lo the surveyed parlicipanis, lacking of

concentration (Annstrong ef al., 2016; Becker-Leifhold, 2017; Iu and Llu, 2018;

Lee and Chow, 2020) The Vietnamese younger- gen Z is the main targeted group in

this sludy This is a group of potential customers with outstanding characteristics

related to technology application, personal awareness and social responsibility

(Abdullah, Mahadee Ismail and Albani, 2018) For those living in the world of

sovial neiworking, besides effecting from friends or relatives source, customers may

be governed by large sources of information on the internet or marketing channels Therefore, subjective norm is determined in the relalion and impact of interpersonal influcnee, clectronic- word of mouth and inthiencer marketing

1.3 Research objectives and Research questions

This study contributes to the extant knowledge concerning factors impacting customers’ willingness to participate in fashion rental through the following research objectives

- To clarify the relationship and impact of attitude, subjective norms, and perceived behavioral control on the behavioral orientation of young customers following the TPB and TAM theory

- To expand and provide more knowledge related to fashion rental trends and characteristics of gen Z, helping business companies have more information to

analyze and apply in real aclivitics

~ Tơ đemonstrato the influence of E-WOM and inilueneer marketing on generation

Z engagement in hiring clothes

Tu order to achicve these objectives, lwo research questions are addressed as follows:

1 Why does the fashion rental in terms of sharing economy become a potential business model?

2, What are the main factors affecting the Vietnamese younger customers’

willingness ta engage in fashion rental service?

14 Research method

A questionnaire survey is employed to investigate the impacts of factors based on

TPR theoretically model SPSS and AMOS — SEM are adopied lo analyze the

quantitative data obtained from 375 young participants in Vietnam ‘These

applications enable the data to be sequentially analyzed via the measurement model

and structural model The former enables reliability and validity of constructs”

measures are assessed while the later is used for testing hypotheses of the study

Applying TPB model, the study confirms the effects of three factors: attitude toward behavior, subjective norm, and perceived behavioral control an the behavioral intention of young customers to participate in renting fashion In which, the strongest influence comes from the perceived behavioral control, regarding, ability

to hire clothes after assessing the personal resources Moreover, tlie highlight of this study is to focus on the Vietnamese young customers- generation Z who are affected by using technology and social networks Therefore, combining the TAM

model, the results show the positive relationships between perceived uselulness,

perceived case of use and attitude toward behavior Besides, in terms of subjective norm, all three factors interpersonal influence, 1!-WOM credibility, and influencer rnarketing have significant relationship with subjective norm Especially, influencer marketing plays an important role that makes stronger impacts on subjective norm than the remaining two variables

1.6 Structure of the study

The research project is organized in 5 chapters Chapter 1, present chapter provides the background for the study, prior siudies and research gaps, research objeclives and research questions, research methods, research finding and the structure of the study Chapter 2 reviews Hterature on necessary knowledge about fashion rental service in sharing economy tend, the information related lo potential group of customers- gen Z, and factors shaping customers’ engagement Chapter 3 states the selected research method of study, which describe a comprehensive research procedure of the survey design Clapler 4 presents technique of data analysis and research findings, ‘The study closes with chapter 5 where the research findings are discussed and the research conclusion is drawn Also, the limitations of the study

are addressed and suggestions for the future research are provided.

CHAPTER 2: LITERATURE REVIEW

‘This chapter aims to understand the sharing economy, online fashion rental service and generation Z (section 2.1 and 2.2) before providing, theoretical perspective on factors unpacting customers’ behavieral intention (section 2.3 and 2.4) ‘Then, the conceptual framework and the proposed hypotheses are shown in section 2.5

2.1, The sharing economy and the online fashion rental service

2.1L The basic knowledge related to sharing economy

‘The sharing economy has increasingly concerued and received significant attention from scholars, and policymakers,

cormomy, platform economy, and cornmurty-based economy (Belk, 2014)

Sharing economy is originated from the collaborative consumption idea praposed

by Felson and Spaeth (1978) through peer-to-peer platforms or markets Jt is considered as a consumption behavior mode using exchanges, sharing, bartering, transaction, and leasing (Mohlmann, 2015) Sharing may be not new concept, but sharing economy driven by the Internet and other supporting tools or features is a recent phenomenon (Belk, 2014) Heinrichs (2013) suggested that the drivers of the sharing economy include social media and information technology that allow the online interaction, Hence, the dominant platform of the sharing economy has beon online websites A number of online-service companies pioneering the sharing economy include e-Bay, Craiglisi, Napster, Wikipedia, YouTube, and Ask.com Heonomic, societal and technological drivers (Owyang, 2014) promote the innovative forms of collaborative consumption, leading the appearance of more and tore applivations in the public, private, non-profit and profit seotor (Toni, Renzi and Mattia, 2017)

In addition, the collaborative economy which is a new potential business model has

exclusive features that differentiate itself from existing models The process of

11

transaction and product oxchange are the main differences of sharing cconomy compared with other business models Some authors argue that sharing economy consists of three key vores: access economy, platform economy, and community based economy (/Acquier, Daudigeo and Pinkse, 2017) It is not only considered in business-to-consumer rental , but also allowed to expand into the consumer-to-

consumer environmen (Rim Chai ef ad., 1998)

The main characteristic of sharing economy is the possibility of nsing goods and

services by paying for the temporary experience , with no transfer of ownership taking place (Bardhi and Eckhardt, 2012) Many economic, spatial and temporal advantages derive from usmg rather than owring goods Moreover, il also brings positive impacts on the sustainable development activities, such as reducing

negative impact on environment, saving energy and reducing oarbon, allowing

people to have products they carmol alford In order to promote sustainability, consumers need to decrease their level of consumption (Pogutz and Micale, 2011)

The adoption of collaborative economy models on a large scale and vary fields by

companies as well as in (he consumption activities of individuals is considered a very promising way of making production and consumption more sustainable

(Liedtke ef af, 2015) Chiu (2014) emphasized that there are many reasons for

development of sharing cconomy, such as cconomic downturn, nse of environmental awareness, and popularity of social media and other factors In

combination with this trend, companies can create online rental services and take

enviioumental protection or resource utilization as main factors to communicate

with customers

The sharing economy can be classified into three categories: product-service systems, redistribution markets, and collaborative lifestyles by Rachel, Botsman and Rogers (2010) Firslly, producl-service sysloms mean thal owners of cerlain products or services share their products or services with others by way of a fee-

based rental Instead of purchasing, consumers can experience services or enjoy the

Denofits of products by leasing Some multiple emerging platforms have invested in

12

this sharing services, such as Zipear, Lyft and other car sharing, Airbnb rent sharing services Secondly, in terms of redistribution markets, families often have a large number of rarely used and idlle assels thal could only be placed in slorage rooms or discarded in the past Nowadays, by using internet, these second-hand products are redistributed on online platforms rapidly to those people in need The appearance

of SwapTree cBay Freceycle and other sccond-hand exchanges, sales, or reveling platforms allow people to save resowces and protect environment ‘Thirdly, related

to collaborative lifestyles, it means that various interests and common needs of

consumer may galher on social platforms io share or exchange relatively recessive assets J’rom there, it helps idle resources create greater utility, for examples time, money, experience, and space, through peer-to-peer lending platform, Zopa,

Lending Club or rental services such as Airbni

Based on the great benelils, al present, the sharing economy is growing continuously in all fields and countries Kor examples: one report in 2018 of China forecasted an annual growth rate of 30 percent or more over the next three years for sharing economy, “tlanks to Uke publie’s active participation, government policy support and mature business mode” Besides, the number of consumers taking part

in China’s sharing economy increased by 7.1 percent compared with 2017 (SMEBIZ, 2019) In this country, bicycles were among the top sharing products, with 91 percent of those open to collaborative consumption trend saying they had rented or bought second-hand bicycles For cars, it was 61 percent Books and consumer electronics were far behind transportation when it came to a willingness

to take part in the sharing economy, at about 25 percent for both product categories (PYMNTS, 2019) According to a survey conducted by PWC in 2017, it was estimated (hat the sharing cconomy in Europe would experience exponential growth from the current € 28 billion to € 570 billion (Bolassa, 2017) In other words, all

sectors may increas

identified that Vietnam is positioned to take advantasc oŸ the growing opportunitics presented by the sharing economy Rebecoa Bryant, Australian Umbassy Charge D’ Allaire, said that “ with a well-educated and young population and almost 70 percent of people owning a smart-phone”, Vietnam’s economy stood to benefit significantly from these developing technologies (VietNamNews, 2018) By this business trend, consumers can take advantages because the market would become more competitive with diversified services In addition, it would also bring more investment opportunities, creating jobs and raising incomes

2.1.2 The online fashion rental service

The increase in renting services, which can give many things a second life, has also contributed to the sharing economy Network-based rental service which can be the center of continuous development make save resources by sharing and protecting

environment (Tu and Hu, 2018) In foreign countries, many online websites for

clothing rental has been creating and developing

Rent the Runway (US), an online service that provides designer dresses and accessory rentals, was established since 2009 and has been operaling for elevert years The company currently focuses on renting formal wear service for events such as banquets and weddings It offers clothes and accessories from the biggest names in fashion, such as Prabal Gurung, Self-Portrait, Brock Collection, Celine, Stella McCartney and Tory Burch, in addition to affordable lines like Reformation, Nike and Splendid The payment that is required for customers is around 10% of the original price of the clothing to rent formal wear And a monthly rental service was

launched In 2017

A competitor to similar companies like Rent the Runway, which focuses on high- end fashion, the plus-sized service Gwynnie Bee, and others, Le Tote (US) allows

users lo borrow and wear unlimited items for $69 per month Tt was established int

2012 and has becn operating for 8 years Current brands inelude Free People, BCB

Generation, Sam Edelman, House of Harlow French Comneetion, Vinee Camuto, and nearly 80 others ‘Ihe customers can keep their items as long as they wont,

yolumn producia and receive a new shipment, or pura

ø them for 20 lo $0 perecnt

off retail prices, given their secondhand nature

Dubbed the “Airbnb of Australian fashion”, [he Volte is an Australian online

marketplace that enables members to borrow and lend high-end designer clothing

Tt works similarly to community closet sharing sites although it focusses specifically

on high-end designer dresses, outerwear, handbags, and accessories with a recommended retail price of $100 Borrowers will find many exquisite garments

from popular Australian brands such as Alice McCall, Alex Perry, Thurley, Nicola

Finetti and Zimmerman from as little as $49 per item The general lend period is 4

days and dry cleaning’s included in customer fee

Aircloset is one Japanese company renting out everyday clothes for women at a spevifie fee by ¥9.800 a month AirCloscl began in February 2015 when the company realized what the fashion industry lacked a sustainable, reoycling-based business model Its focus is on the Japanese boutique clothing market, and it sends three sels of clothing to subscribers every month (including tops, pants and skirts) for a fee Another project of AirCloset named ShareCloset that aimed at reducing apparel waste The company works with specific clothing brands to gather used garments from customers It subsequently uses AirClosct’s oxpericnce and techniques to add these garments to the sharing service or recycle them as materials One ‘Taiwan renting clothes company is AMAZIi which was operated since 2016

The company currently offers more than 1200 styles and more than 5000 pieces of

clothing Tt provides a varicly price of online service oplions including NT$999,

NT$1999, and NT$3999 Users can rent clothes today and receive them two days

later Shipping is offered (ree of charge to provide Ihe most converient service lo consumers If customers like a picce of clothing after renting, they can also buy it at

cost.

One of China’s largest fashion rental platform is Ycloset which has 15 million registered users It was established in 2015 and has been operating for five years This company focuses on fashion sharing for women and it is engaged in the business of “inonthly dressing” Customers pay a monthly subscription rather than per item fee and are able to buy the clothing after they have rented it In 2019, H&M, the world’s sccond-biggest fashion group, had teamed up wilh Chinese subscription rental platform Yoloset for its brand COS to ty renting out clothes in the country as environmentally conscious consumers rein in purchases

The establishment and development of these online platforms are based on the

denefils that fashion rental service brings For the textile industry, hirmg clothes service has many significant cconomic benefits The fashion rental mode) cars

revenue from rental fees and can be an altemative source of revenue for retailers in

the industry (Rachel Bolstnan and Rogers, 2010; Porlacia, Dur] and Sachi, 2017)

For fashion rental companies, the main sources of costs stem from labor and website maintenance (Perlacia, Dum and Saebi, 2017) In the long run, they will be

able lo gencrate revenue by allowing the clothmg items to be used and renled muliple times by different consumers with the frequent tumaround cycle

Moreover, some fashion-rental and e-commerce companies charge for shipping and

laundry services Benjaafar et al.(2019) have identificd that the rental platfonn is

most profitable when the owners and renters are balanced

Customers also get benefits from fashion rental services According to study of Benjaafar et al (2019), the rental service improves consumer welfare and reduces sovietal cosls Without laking complele ownership, consumers can experience products for a chosen period by sharing in a small portion of the original price (Rachel Botsman and Rogers, 2010) Fashion is closely related to individuals! personalitics und their extenual symbols such as status, uniqueness, or beauly Using fashion products is one of the ways to show off status and wealth (Yuan and Shen, 2019) Tn order to be considered fashionable, people must follow the fashion Irends

that constantly changes (Yurchisin and Johnson, 2010, Armstrong ef al, 2015)

16

Instead of purchasing lueuwious produets, people can acocss a tàte of thosc products through renting services Lliring clothes facilitates conditions for consumers lo always have new, diversified and fashionable apparel products that suit thei needs (Balck and Cracau, 2015) without ever having a cluttered wardrobe Moreover, through renting, consumers avoid buying something that is only used

justa Lew lites,

Despite the potential of the online fashion rental market, the knowledge regarding consumers’ perceptions and factors affecting consumers’ intentions to rent fashion items online is less Most existing studies on collaborative economy focus on house renting and car renting, with only a few that notice clothes hiring or sharing clothes Therefore, this research will discuss in more detail the issues related to factors affooting customer behavior in participating in online fashion rental service, while providing additional Inowledge of this potential business model,

2.2 The characteristics of generation Z (gen Z)

In the recent years, gen Z is becoming an interesting topic that is concerned by many anthors (Okan and Solmay, 2015; Abdullah, Mahadee Tsruail and Albani, 2018b; Chicca and Shellenbarger, 2018; Schenarts, 2020) There are some discussions on the exact dates defining this generation, however in general, Gen Z includes those born afier 1998 This period coincidentally aligns with the approximate time when the World Wide Web appeared and became popular (Chicca and Shellenbarger, 2018) There are various names of this group currently used in the studies, including Goneralion 7, iGen, digilal malives, nel Generation, iGeneration, Gen Next, 1 Gen, Gen Lech, Post Gen, and Plurals (Tumer, 2015; Seemiller and Grace, 2016; Jean M Twenge, 2017)

Gen Z has many outstanding and different characteristics compared to other groups that emphasized in the prior research (Ige! and Urquhart, 2012;

2017; Loveland, 2017, Schenarts, 2020) Firslly, this group's members are

jean M ‘Iwenge,

considered as true digital natives and the only generation raised exchssively with a technology influence They are avid consumers of technology and wallow in the

digital world with highly interactive Their daily lives are completely saturated with the digital environment Shatto and Lirwin(2017) reported that the frequency of

using mobile phone of gon 7 is an average of 9 hours per day Secondly, Generation

Z desires convenience aud immediacy ‘They are quite pragmatic Having grown up

in the context of social, political, and economic uncertainty, this group is cautious

and concerned with emotional, physieal, and financial safely Tn addition, Jean M

‘Twenge (2017) suggested that the common events and contextual factors experienced by gen Z have led to more practical, cautious, and skeptical youths

When young people abandon TV and olhter traditional media, they replace il, by using social media at very high frequency Uence, understanding how teenagers use social media throughout their shopping process is key to engaging them on the right

platforms with the righ message (Marianne Wilson, 2017) According to resulis of

Bluecore survey, there are clear differences in the choices different generations

make when using social media to learn about new products (Marketing Charts, 3016) 85% of Gen 7% uses social media to leam about new products and 69% will

visit a store based on the retailer's social media post In addition, figures show that

45% of young people use Taslagram lo find new products, followed by Facebook

with 40% of uscrs, YouTube is also the platfonn of preference when it comes to

shopping recommendations (Dara lontein, 2019), Gen Z consumers are more likely

than other groups to purchase an ilem due to: what their family or (riends think;

recommendations from YouTube; and comments on social media In addition, when

shopping online, their interactions are higher, such as: chat with an online sales

assistant; check in store for more information, ask friends’ or relatives’ opinions via

social media, message or phone ‘The findings of Morning Consult’s Influencer Report show that 52% of Gen Z trusts influencers! advice about products or brands,

while 82% of them trust ther fiends and family over any other source (Tracy

Jrancis and ernanda Lloefel, 2019)

2.3 Theory of planned behavior (TPB)

‘TPB has been adopted broadly in many studies that cover different research areas in

specific contexts It is a causal model to explain behavior and is considered as an

extended model of ‘TRA (Ajzen, 1991) According to TPB, a person’s actual

behavior is direolly influenced by behavioral intention which is determined by

altitude, subjective norm and perceived behavioral control toward performing the behavior (Wu and Chen, 2005), In other words, human behavior is shaped by three

considerations: bekefs about the likely consoquences and experienees associated

with the behavior (behavioral beliefs), beliefs about the normative expectations and

behaviors of significant others (normative beliefs), and beliefs about the presence of

factors that may facilitate or impede performance of the behavior (control beliefs)

In their respective aggregates, behavioral beliefs produce a favorable or unfavorable

attitude toward the behavior; normative beliefs result in perceived social pressure or

subjective norm; and auntrol beliefs give rise to pereeived behavioral control or

self-efficacy (Ajzen, 2010)

Attitude expresses the feeling of a person's favorable or unfavorable assessment yogarding the behavior Furthermore, a favorable or unfavorable altitude is « direc!

influence on the strength of behavioral beliefs about the likely consequences or the

past experience (Solm and Kwon, 2020)

Subjective norm shows the perecived organizational or social pressure of a person

regarding perform the behavior intention, In another way, subjective norm is

relative (o normative belicls about the cxpeelatious of other persons Tn many

articles’ suggestion, the dimension of normative belief should be decomposed into

reference groups Taylor and P Todd (1995) decompose of the subjective norm into

peer influence and superior influence seems justified in an organizational setting in

which one’s peers may be opposed towards specific behavior, whereas, at the same time, one’s superior may be encouraging towards the behavior Bhattacherjee

(2000) separaled subjeclive norms io interpersonal ifluence and external

influence When the potential adopters try to do something, they will look for the experience of the previous adopters (interpersonal influence) or consult the experts

from the iass media in this Íield (exicrnal míluenoe), so as lo reduce the

uncertainty In this rescarch, following the external factors which have more impact

on gen Z, subjective norm can be determined through three main variables:

interpersonal mMucnec, clectrome word of moullh (EWOM) and iniTuencers

marketing

The restriction of TRA is to predict the behaviors of those with weak control

Dillerent from TRA, TPB includes perecived behavioral control thai is the

perception of the ease or difficulty of performing the behavior (Wu and Chen, 2005;

Ulker-Demirel and Ciftci, 2020) The effects of attitude toward the behavior and

subjective norm on inlenlion are moderated by perception of behavioral comrol As

a general rule, the more favorable the attitude and subjective norm, and the greater the perceived control, the stronger should be the person’s intention to perform the behavior im question (Ajzen, 2010)

2.4 Technology acceptance model (EAM)

‘Technology Acceptance Model (TAM) was introduced by Hed Davis in 1986

(Davis, Bagozzi and Warshaw, 1989) It is an adaptation of the theory of reasoned

action (TRA) and mainly designed for modelinys user acceptance of information

technology ‘I'his model hypothesizes that system use is directly determined by

behavioral intention to use, which is in tum influenced by user’s attitude toward

using the system And, altitude is affected by porecived usefulness and perecived ease of use According to the defining of Davis, perceived usefulness reflects the

users' belief that using a specific application system will enhance their job or life

performance Besides, perceive case of use can be defined as the degres to which the users expect the target system to be free of effort (Taylor and P A Yodd, 1995)

Both perceived ease of use and perceived usefulness which are the most important

determinants of actual system use can be mfluenced by external variables (Wu and Chen, 2005) The main extemal factors are social factors, cultural factors and

polilival [uclors Social factors include language, skills and facilitating conditions

Political factors are mainly the impact of using technology in politics and political

crisis.

TAM is one of the most popular theories that is used widely to explain Information System usage Llence, many researchers have suggested the changes in the originally propased model A new model called combined TAM-TPB model was

buill by Taylor and Todd (1995) Venkalesh ef a/.(2000) developed a new version

of ‘LAM called ‘AM 2 which added new variables to the existing model Besides,

TAM has been used to understand the acceptance of different types of information systems such as: clearing systems, online shopping plaiform, online banking

applications (Zhou, Dai and Zhang, 2007; Priyanka Surendran, 2012)

2.8 The framework and the research hypotheses

This study combines TPB and TAM to predict and analyze the factors that can

affect the customers’ willingness lo engage im fashion rentals as the model below

Attitude onward behavi

25.1 Perceived usefulness

Perceived usefulness is defined as ‘the degree to which a person believes that using

4 particular lechnology will enhance his or her job performance’ (Davis, Bagovvi and Warshaw, 1989), This means that the user has a perception of how useful the technology is performing in his/her job tasks On the other way, Davis, Bagozzi and Warshaw (1992) said that perceived usefulness refers to consumers’ perecplions regarding the outcome of an experience ‘This follows from the definition of the word useful: “capable of being used advantageously.”

As the results of some past TAM studies, perceived usefulness has a possible impact on enhancing user’s attitude towards usage The cffect of perceived usefulness on attitude has also been validated in many existing studies (Chen,

Gillenson and Sherrell, 2002) For examples: Fumei Weng et af (2018) found that

the attitude toward behavior was significantly affected by predicting usefulness in using multimedia teaching material for school teachers Teo (2010) conducted a study on pre-service teachers’ attitudes toward computer use The results indicated that porecived usefulness significantly influcnices on altitude Tn line wilh other research, perceived usefulness plays imporiant role in shaping attitude toward

online airline tickets purchasing (Remy, Suryo Guritno and Holniar Siringorinigo, 2013) Therefore, this study postulates following hypothesis:

Hla: Perceived usefulness has a positive relationship with attitude regarding online fashion rental services

25.2, Perceived ease of use

Davis described perovived case of use as “the degree to which # person believes thet using a particular system would be free of physical and mental effort” (Davis, Bagozzi and Warshaw 1989) Tt also means a user’s subjective perception of the cffortlessness of a computer system This follows trom the definition of the word

“ease”: “freedom from difficulty or great effort.”

TAM posits that perceived ease of usc has a direct positive offect on attitude toward using the system Complexity of one particular system will become the inhibitor that discourages the adoption ol an imovation (Rogers, 1993) Many studies were conducted to validate ‘AM by using perceived ease of use and perceived usefulness

as two independent variables and attitude towards behavior as the dependent

variable (Teo, 2010, Rermy, Suryo Guritno and Hoiniar Siringoringo, 2013; Juniwati, 2014, Fumer Weng ef af, 2018), ‘The results show that perceived

usefulness is significantly correlated with attitude As the same way, perceived ease

of use also has positive impacts on altitude Based on the above arguments, the

proposed hypothesis is:

Hib; Perceived ease of use has a positive relationship with attitude regarding

ontine fashion rental services

2.5.3 Interpersonal influence

As mention above, Tulerpersonal is onc of the chmersions thal bas inlousive impact

on subjective norms (Bhattacherjee, 2000) Interpersonal behavior is referred to the

change in one's behavior due to others! feelings or opinions This influence might

refleet the compliance and acceplamce wilh others’ expectation Before making a decision, Bhattacherjee (2000) argued that potential adopters solicit opinions from peers who already know about the characteristics and worthiness of a service Interpersonal sources create important influences, especially on decisions involving

uncertainty (Ienech and O'Cass, 2001) Besides, the strong influence of proximate

people was posiled and cmphasived (Iobnson, 2004), such as friends, family and co-

workers (Hsu ef a/., 2006, Hung, Chang and Yu, 2006) Regarding online fashion

rentals, Tu and Liu (2018) found that the positive relationship between interpersonal

influence and subjective norms was significant Hence, this study assumes Uual:

Ha: Interpersonal influence has a positive relationship with altitude regarding

online fashion rental services,

2.5.4 Electronic word of mouth (E-WOM) credihility

Based on previous studies, it shows that word of mouth (WOM) through social

media which means face-to- ornmunication among peuple plays an important role in influencing consumers’ decision making (Brown and Reingen, 1987;

Mazzarol, Sweeney and Soutar, 2007) It allows consumers to communicate in an

unbiased manner regarding products or services in a plalform believed to be non

related to an organization With the development of intemet, it had established a nore universal and less personal kind of WOM which is electronic word of mouth (E- WOM) Hennig-Thurau and Walsh (2003) defined E-WOM as comments either

positive or negative which are made by customers regarding product or service to an amount of people through thư InlerneL E-WOM is also considered lo be an important platform that allows consumers to communicate and transfer theit

thoughts to others (Godes and Mayzlin, 2004) In addition, E-WOM is also

considered to be more effective when compared to traditional word of mouth as it is

more convenient and it has the ability to achieve a higher reach

WOM which can be considered in terms of peers influence generaled by co- workers, relatives or friends has positive relationship with subjective norms (Blutlacherjee 2000; Teo, 2010) Numerous studies have validaled the significant influence of word of mouth on subjective norm (Bhattacherjee, 2000, Md Husin, Ismail and Ab Rahman, 2016) In addition, WOM is also said to generate the subjective norm construck wherever conmumer considers technology adoption (Palka, Pousttchi and Wiedemann, 2009) Hence, some authors also suggest the influence of I-WOM on subjective noms (Jalilvand and Samiei, 2012, Doma, Flare and Abo Elnaga, 2015, Goh, 2015) Besides, Chatterjee (2001) ard Fong and Burton (2008) discussed more details in terms of the differences between H-WOM and WOM They argued that E-WOM is more effective than WOM due to the ease

of usc and the width of range Adopting, these articles, the study suggests the hypothesis

H2b: E-WOM credibility has a positive relationship with subjective norms regarding online fashion rental services

2.5.5 Influencer marketing (KOLs)

Brown (2013) defines thal inluencer marketing is “Typically a noncustomer or

business mecentivised to recommend/create content about a business brand or

product” Another definition which Brown and Hayes (2008) gave is that the word

“Tnflucnce” can be broadly delimed as the power lo affect a person, thing or course

of events Influencer marketing can appear as an entirely new marketing, strategy

As previous studies, it may affeot the subjective norm of individuals (De Koning,

2018) Subjective norm which also is social influence means “the person’s

perception that most people who are important to him or her think he/she should or

should not perform the behavior in question”

In addition, influencer marketing can be seen as a virtual word of mouth but it works dilferently than word of mouth A company uses influencers to reach consumers instead of family or friends, by providing the agreed messages or activities between the company and influencer Consumers are much more likely to positively porcvive and reac! to a message thal comes frou a busted porsoual over a

sponsored post that comes from a company (Woods, 2016, Wroblewski, 2017) Fspecially, in fasion industry, influencers who ofen have a high number of followers on social networks can be useful for brands to attract consumers The research focuses on gen % who is significantly and directly affected by famous

people or influcnicers Hence, the following hypothesis is proposed:

H2c: Influencer marketing has a positive relationship with subjective norms reyarding online fashion rental services

256 Attitude toward behavior

Following the results of TRA or TPB research, attitude is one of the major determinants that shape behavioral intention (Ajzen, 1991), Attitude refers to a person’s assessment of human, objects and goods (I3lackwell R, Miniard P and

Bnge] J, 2006) This imvolves favorablc or tufavorable asscssimeni, emotional feelings, and behavioral propensity (De Koning, 2018) Furthermore, by ‘IPB model, atlilude loward behavior is explained as ihe dogree whereby an individual makes a positive or negative evaluation towards the bebavior in question (Ajzen, 1991), Tlence, it can be said that as attitudes are more favorable toward the behavior, a person’s inlention io exccule Ihe behavior will be sbronger A further

commonplace is that attitudes have cognitive components, affective components,

and behavioral components In which, the behavioral component is central to research's concern here, following the argument of Ajven (1991) : “The ability of attitudes to predict behavioral intentions or overt behavior continues to be @ major focus of theory and research”

The positive impacts of attitude on behavioral intention are explored and proved in rnany sludies in different elds (Fusilier, Harrison and Worley, 1996, Ajven, 2010; Jatilvand and Samiei, 2012; Juniwati, 2014, Chew and Abdul Adis, 2018) In particular: Fusilier, Harrison and Worley (1996) suggested that attitude is positively related lo the behavioral intention to provide ATDS care Another report showed that positive attitude leads high behavioral intention of waste management technology at students (Siahaan, 2018) Regarding to renting clothes, attitude also is one of the main determinants that positive influences on mntention to hire (Tu and

Lin, 2018; Lee and Chow, 2020) ‘This study suggests the hypothesis

H3: Attitude toward behavior has a positive relationship with behavioral intention regarding online fashion rental services

25.7 Subjective norms

Subjective nom is the second determination of intention in the TPB model Ajzen (1991) said that it is the perception of social pressures to undertake or not to undertake a given behavior Auother component lowards subject norms is normative belief, which defines the perceptions of an individual towards the views regarding his/her act generated by a person believed to be important to that individual The

TPB model shows that wherever the stronger the drive to adhere to social pressure, the role of social pressure is more important (Mathieson, 1991) lurthermore,

intention, Besides, Venkatesh et ai (2003) concluded that subjective norm originated through social influences is crucial to ascertain users’ intention towards

the acceplanee and usage al technology

Many other studies also indicate that subjective norm has impact on the intention For instant: ‘Ihe finding of a research showed that subjective norm was significantly and positively correlated with leamers' behavioral intention in using e-learning (Yau

and Ho, 2015) Shin and Hancer (2016) adopted the extended TPR model of Ajzen

in their study and indicated that subjective norm in the standard model was

supported Another article also analyzed the specific role of two types af subjective

norms in forming [he intention to purchase groon [ood (Ham, Jeger and Tvkovié, 2015) Hence, this study assumes that subjective norm has positive effects on the

behavioral intention of clothes renting

lI4 Subjective norm has a positive relationship with behavioral intention

regarding online fashion rental services

25.8 Perceived behavioral control

Ajzen introduced perceived behavioral control into his theory of planned behavior

asa determinant, behavioral intention (Ajven, 1991) Perceived behavioral control

means an individual’s perception regarding the ease or difficulty in undertaking the behavior In addition, it reflects on past experiences and also forecasts about impediments or consequences (Ajzen, 2002) Furthermore, perceived behavioral control is combined of bwo different factors namely control beliefs and perceived facilitation (De Koning, 2018) Control belief is an individual’s belief regarding to the self-availability of skills, resources and opporhmilies Perceived facilitation relates to the accessibility of time, money or other specific resources for certain behavior (Tu and Hu, 2018)

tỳ

TPB suggested that perceived behavioral control direetly affects the intention to perform a behavior and also the actual performance of that behavior as compared to

the extent of the actual behavioral control Lake Ajzen's theory of planned behavior,

most psychosocial theories of health behavior have incorporated perceived behavioral control as a major determinant of intention to engage in health behavior

(K Walston, 2001) This study also proves the influence of perecived bchavioral

control on behavioral intention by proposed hypothesis:

HS: Perceived behavioral control has positive relationship with behavieral intention regarding online fashion rental services

25.9, Behavioral intention

Behavioral intention reflects the tendency for which a person wants to take a specific action, and it can be measured by a person’s willingness to have an

experience or the effort of person makes to take an action According to TPB model

of Ajven, if is pointed oul that, behavioral intention is the best way to predict

individual behavior (Ajzen, 1991) In other words, when people have stronger intention to take some actions, then the probability of taking the action will be higher This study proposcs that three main Jactors: altitude, subjeclive norm, and perceived behavioral control have a significant positive correlation with behavioral intention of cuslomer Lo engage in online renting clothes service.

CHAPTER 3: RESEARCH METHODOLOGY

This chapter is divided into 5 sections from 3.1 to 3.5 The first section shows the research procedure which involves each step taken in the analysis ‘The using of

survey a8 a quanfitative method is identified in the nexL section Aller thal, scelion

3.3 shows the designing of questionnaire and pilot testing before practical swvey Then, information about sample size and how to collect data is presented in section 3.4, The last scction gives the basic knowledge about the data analysis mothods and its evaluation standards that are used in the study

3.1, Research procedure

This research aims to analyze the knowledge about online clothing rental industry

as well as its opportunities and discuss the factors affecting Gen Z’s behavioral intention to rent clothes According to the aforesaid literature review, the research procedure of this research is constructed as shown in figure below:

Figure 2: Research procedure

supervisors for Bical quest:ennaire and doing prlal Lest

3 Identify sample size

4 Collect data and clear it before analyeng:

3.2, Survey ax 4 quantitative research method

In this study, quantitative research method is used to quantify the problem by way

of generaling mamorical data

The survey refers lo via a set of questions designed to find oul and prove relationships between variables [he most noticeable characteristics of the survey is that data of multiple cases are collected at one point of time (De vaus, 2601;

Bryman and Bell, 2007) One of the most advantages of the survey is its reasonable

costs to collect data within a relatively short period of time However, if the questionnaire is not carefully designed, the misunderstanding of respondent can be a

major problom (Johnson and Tumer, 2007)

The survey consists of different stages The first phase is to state the problems that will be examined by the studies At this stage, main concepts of the study are

clarified before hypotheses are develaped and concepiual framework is built

Sceondly, a pilot tas! is advisable to cusure the quoslionnaire is in the best quality conceming its content, its length, and its understandability ta target respondents

Thirdly, this is followed by sample plan that allows the researcher to identify a

iminimum sample size for the study before the questionaire is ollicially delivered ona large scale According to [lair et al (2014) the minimum of sample size is to have at least five Limes as mary observations as the number of ilems in questionnaire to be analyze The next phase is to clcan the data before certain techniques or methods of data analysis are implemented, ‘Then, research findings are drawn Importantly, the credibility of rescarch findings is significantly influenced

by two vital aspects of survey design namely reliability and validity

3.3 Questionnaire design and pilot Lest