Research Proposal: Will Zara's Sales increase at TMAll

Executive Summary
As the online shopping gives more convenient shopping experience to online shoppers, there is no argument that it is slowly replacing the physical stores. But with the easiness of access to products and the ability to compare goods or services online without going to the physical shopping stores of these companies, companies face tight competition and need to handle the online shopping with care such as choosing the right platform, determining the shopping behavior of a group of people which can be divided by age, culture, nationality and the like. Zara is one of the fashion design retail stores which started to sell to Chinese online shoppers, online shopping platform owned by Alibaba. Our research is designed to find whether sales will increase and what are the key success factors to ensure it. To do the analysis we formulated research questions whose answers would provide us with the opportunity to find answers to these questions and to identify the current feelings of online shoppers in China. A questionnaire will be developed in English and translated to Chinese, and will be initially administered as a pre-test to small group of participants at Zhejiang Normal University. The actual study population will consisted of a total of 1000 individuals, located in Beijing, Shenzhen, Shanghai, Guangzhou, Wuhan, and Shandong. The questionnaire contained questions designed to collect information on demographics, Internet usage, brand knowledge and e-commerce activities (frequency of commerce and type of purchase, means used for purchase, transaction experience, and perceptions of e-commerce in China). The data will be analyzed first, demographic information is analyzed using descriptive analysis, second factor analysis is used for each variable and its indicators, third the general hypothesis is tested using independent sample t-test and at last, canonical analysis is applied in order to investigate the casual relationship between online ecommerce and sales. The research is intended to support Zara in securing profit and winning Chinese online shoppers.

Introduction

Zara is one of the world’s most successful fashion retailers, operating in 59 countries. Established in 1975, Zara is the flagship of Inditex (Industria del Disen˜o Textil, SA), a holding company located in Galicia (Northwest Spain). In a relatively short time frame Inditex has become the world’s second largest clothing retailer with 2,692 stores spread across 62 countries worldwide by the end of January 2006. In addition to Zara, which accounted for 66 percent of the group’s turnover in 2005, Inditex owns seven other clothing chains: (1) Kiddy’s Class (children’s fashion); (2) Pull and Bear (youth casual clothes); (3) Massimo Dutti (quality and conventional fashion); (4) Bershka (avant-garde clothing); (5) Stradivarius (trendy garments for young women); (6) Oysho (undergarment chain); and (7) Zara Home (household textiles).

As part of its expansion and internationalization strategy Zara entered China in 2006 and now operates in 146 stores. The fast-fashion brand began to sell online to Chinese shoppers on its own site, Zara.cn, in 2012. In 2014 Zara opened online store on Tmall, a Chinese website owned by Alibab Group Holding Ltd (BABA), where companies such as Nike Inc, Burberry Group Plc., and Gap Inc . sell their ware.

Zara is one of the strongest Western retailers in China, where Inditex has 456 stores. But its two-year old Zara.cn, which will continue to exist, isn’t even among the 10,000 most popular Web destinations in China, while Tmall is No. 7 (Alexa, 2013). Several Inditex competitors already have stores on Tmall that complement their bricks-and-mortar stores in China. They include U.S.-based Gap Inc., Forever 21 Inc., and Uniqlo Co. of Japan. Hence, the objective of this proposal is to study whether Zara’s sales will increase in Chinese market with Tmall. Information from this research will be important in determining the critical success factors for Zara at Tmall.

The research team has set a period of ten weeks for the completion of the project. Consequently, all the tasks in the research will be distributed evenly within this period. Allocations will be done depending on the weight of the task and how many parties will need to be involved in the process.

Background

Concerning the consumer buying behavior when it comes to buying clothes, it is changing very fast in modern China, particularly among young people. As more fashion related goods are entering into the Chinese market, status-conscious Chinese now have a better understanding of luxury and quality than they ever did before and it is no longer easy for foreign fashion companies to make money in China. For example, facing the challenges from H&M, Zara and other fast-growing domestic fashion brands, Bestseller Fashion Group China must have a thorough understanding of its target group’s buying behavior. Analyzing the Chinese fashion consumer’s buying behavior on a regular basis is a very effective way of keeping Bestseller Fashion Group’s leading position in China. Consumers in China have shown that they are sensitive to price but brand names are not relatively important among the respondents (Yang, 2011).

According to Yang, fashion buying is also at its all-time high in certain parts of China, yet it is difficult for foreign fashion companies to beat the popular brands. Comparing the older generation with the younger generation, the older generation focuses more on budgeting and the responsibility of this is usually given to the wife. As for the younger generation, they focus more on the fashion, the brand and the technology and aim more for the luxury and quality. Based on the research, this puts the personality of the younger generation in the category of ‘idea shopping’ and the older generation in the category of ’value shopping’ (Zhou & Amin, 2014).

Purpose of the Research study and research problem
Our Objective is to find answer to two primary questions:

(A) Will Zara’s sales increase with the opened online stores on Tmall?
(B) What are the key success factors for ensuring increase of sales?

The objective of the research:
(A) To ensure increase of Zara’s sales at Tmall
(B) To find the key success factors for winning online clothing and shoes shoppers in China

Since we wanted to narrow the focus of our research and focus primarily on knowing if Zara’s sales will increase and find the key success factors, we formulated research questions whose answers would provide us this opportunity to find answers to these questions and to identify the current feelings of online shoppers in China, a 25-question questionnaire was developed in English and translated to Chinese, and was initially administered as a pre-test to small group of participants at Zhejiang Normal University. The actual study population will consisted of a total of 1000 individuals, located in Beijing, Shenzhen, Shanghai, Guangzhou, Wuhan, and Shandong during the time of the study, residing and working in different regions in China, and with different educational levels, professions, and gender. They also worked for different types of organizations.

The questionnaire contained questions designed to collect information on demographics, Internet usage, brand knowledge and e-commerce activities (frequency of commerce and type of purchase, means used for purchase, transaction experience, and perceptions of e-commerce in China). Because of the types of questions and groupings we created (e.g. multi-year age grouping vs. specific age, verbal measures vs. numeric, etc.) and used in our questionnaire.
Study Population and Demographics

As can be illustrated in (Table 1), in our study, our study population of 1000 participants characteristics will be compared to the studies conducted by the China Internet Network Information Center (CCNIC), which uses Internet to collect data for the Chinese government. CCNIC conducts these studies semi-annually to identify the development and progress of Internet in China. We will use the demographics of their latest survey as comparative statistics to our study. Their study participants had a much broader sample of professions, including those who checked categories such as ‘military’, ‘peasants’, ‘agriculture, forestry, fishery’, real estate’, ‘wholesale and retail’, ‘culture and arts’, and ‘sports’, ‘unemployed men,’ etc. professions which may of course not covered by our survey. However, since CNNIC conducts their surveys using Internet and participants are self-selected, we are not sure how representative their study participants are of the general population demographics of China. Since theirs is the only large-scale study in China that presents reliable demographics, as well as technical data, we decided to use their findings to compare with our study results.

Table 1
Our study demographics vs. comparable study demographics

Gender Education Age E-commerce Participated

Male Female BS degree Graduate 25–40 years Over 40 years

Study % % % % % % %
CNNICa % % % % % % %

a China internet network information center, 2014

Table 2
Organizational affiliation of study participants

MNC Domestic enterprisesa Joint Venture Participants in sample # # % of participants % % %

MNC, Multi-National Corporation. a Includes private enterprises, state owned enterprises (SOE), and university.

Data Analysis

Data collected through survey will be presented and analyzed statistically. The statistical procedures that will be undertaken are as follows: First, demographic information is analyzed using descriptive analysis, second factor analysis is used for each variable and its indicators, third the general hypothesis is tested using independent sample t-test and at last, canonical analysis is applied in order to investigate the casual relationship between online ecommerce and sales.

Descriptive Analysis

Factor Analysis
Factor analysis attempts to identify underlying variables, or factors that explain the patterns of correlations within a set of observed variables. Factor analysis is often used in data reduction to identify a small number of factors that explain most of the variables observed in a large number of manifest examples.

Timing

This table bellow indicates our suggested timeframe for the project. The project duration is 19 weeks. This meets the deadlines set out the brief. When the project is underway, we will send weekly progress reports in the forms of emails at 12 noon every Friday. This allows us to summarize the week 's work and gives us the opportunity of the weekend to put into place any modification you might suggest. Please note that there are overlapping periods, these have been carefully studied to ensure that your deadline are respected. Timing is tight, so if we are to conduct the research to match the deadline you provided, we would require sign-off within the next two weeks. Should your own launch date change, our timetable can be applied to the new requirements. Detailed plan template that will be used for the project is attached at the appendices.

Week
Activity
1 to 4 desk research
4 to 6 qualitative fieldwork
7
qualitative/desk research report available
8
questionnaire development
10
Debriefing
11 to 12 quantitative stage (1000)
12 to 13
Coding and data preparation
14
Analyze
16
Presentation
19
final report available

Budget
The following information are quoted and suggested by research facility price in average. All fees are subject the assumption contained in this proposal and all rights of making adjustment Final costs may be within 10 percent to those listed in this proposal. Detailed budget plan template is attached at the appendices.

Activity
Description
Prices
Field work desk research, reports
¥20 000
Analysis
interview, analyze, 5 students
¥60 000
Report
Hours f junior and senior executives
¥50 000
Total

¥130 000

Research Design and Limitation
The research will provide a selective analysis of some big cities selected based on the largest number of online shoppers numbers based on the CCNIN. The critical success factors which will be identified may not be exhaustive.

We have made the decision to carry out of 1000 interviews of different age. This will give us a spread of responses and the opportunity to identify interesting differences. It will be directly with the person who is responsible to buy clothes.

buyer age male female total sample
20 to 23
125
125
250
24 to 27
125
125
250
28 to 31
125
125
250
32 to 35
125
125
250
total
500
500
1000

We propose four groups with the following profiles.

group 1 group 2 group 3 group 4
North
south east west

References

China Internet Network Information Center, 2013 annual Survey Report on the evelopment of China’s Internet (1997–2013etrieved 20th September 2003 from the World Wide Web http://www.cnnic.net.cn/ evelst/2003-1e/444.shtml.

Gihyung Kim, Seunghee Lee. 2014. Business Strategy of Fast Fashion -A Case Study of Zara-. Journal f the Korean Society of Clothing and Textiles 38, 175-190.

Liz Barnes, Gaynor Lea‐Greenwood, Maegan Zarley Watson, Ruoh‐Nan Yan. 2013. An exploratory tudy of the decision processes of fast versus slow fashion consumers. Journal of Fashion Marketing nd anagement: An International Journal 17:2, 141-159.

Gresi Sanje Dahan, Filiz Balta Peltekoglu. 2011. The Effects of Zara to the SMEs of an Emerging Market.Journal of Global Fashion Marketing 2:1, 1-10.

Zwass, V., 1996. Electronic commerce: structure and issues. International Journal of Electronic Commerce 1
(1), 3–23.

Travica, B., 2002. Diffusion of electronic commerce in developing countries: The case of Costa Rica. Journal of
Global Information Technology Management 5 (1), 4–24.

BDA, 2000. Consumer E-Commerce in China (2000), BDA (China) Limited, Retrieved 16th September 2002 from World Wide Web http://www.bdaconnect.com.

References: China Internet Network Information Center, 2013 annual Survey Report on the evelopment of China’s Internet (1997–2013etrieved 20th September 2003 from the World Wide Web http://www.cnnic.net.cn/ evelst/2003-1e/444.shtml. Gihyung Kim, Seunghee Lee. 2014. Business Strategy of Fast Fashion -A Case Study of Zara-. Journal f the Korean Society of Clothing and Textiles 38, 175-190. Liz Barnes, Gaynor Lea‐Greenwood, Maegan Zarley Watson, Ruoh‐Nan Yan. 2013. An exploratory tudy of the decision processes of fast versus slow fashion consumers. Journal of Fashion Marketing nd anagement: An International Journal 17:2, 141-159. Gresi Sanje Dahan, Filiz Balta Peltekoglu. 2011. The Effects of Zara to the SMEs of an Emerging Market.Journal of Global Fashion Marketing 2:1, 1-10. Zwass, V., 1996. Electronic commerce: structure and issues. International Journal of Electronic Commerce 1 (1), 3–23. Travica, B., 2002. Diffusion of electronic commerce in developing countries: The case of Costa Rica. Journal of Global Information Technology Management 5 (1), 4–24. BDA, 2000. Consumer E-Commerce in China (2000), BDA (China) Limited, Retrieved 16th September 2002 from World Wide Web http://www.bdaconnect.com.