China Power of Retailing 2015

China Power of Retailing 2015 1 Foreword 2015 has witnessed the recovery of a global economy and the gradual stabilization of a real economy in China. While the Eurozone economy continues to improve, the differentiation among its economies remains noticeable. “Abeconomics” throws Japan into deep recession. The United States of America, as the only exception, enters the trajectory of a strong recovery and the US dollar has appreciated sharply against other major world currencies. Its well-anticipated rise in interest rate in the fourth quarter forebodes an accelerated devaluation of currencies in most emerging economies. As a result, the pressure on devaluating RMB is mounting. With a slowed growth rate, the Chinese economy has arrived at the stage of new normal. The YoY growth for the first half of the year lingers around 7%, hindered by the deceleration of the three engines that used to propel GDP growth – a sluggish export, a slow growth in investment and a domestic consumption that continues to fall behind expectation. Although the growth rate of the total retail of consumer goods has dropped, it has far outpaced the domestic industrial growth. With the consumer confidence seeing constant improvement that will further free up consumption potential, consumption is expected to continue pulling the economy in the future. A continued fall in oil prices has offset the inflationary pressure, curbing the inflation at a lower level to make room for executing a lax monetary policy. To further boost investment and consumption, and reduce enterprise financing costs, the government has gradually redirected its macro economy from “stabilize growth and adjust structure” to “ensure growth,” making the lowering of interest rate and reserve ratio possible in the second half of the year. A rising cost and narrowed profit still threaten the retail industry. Constantly climbing house rents and labor expenses have pushed up enterprise operational costs and further eaten in their profits. Meanwhile, physical retailers face the challenges from e-commerce, forcing the traditional retail industry to go through the pain of transformation, while the competition among retailers is becoming more brutal. On the other hand, technological innovations, change in consumer behaviors and individualized needs in consumption have combined to drive enterprises to beef up efforts in online business, switch to O2O all-channel operation and speed up mobile e-commerce and cross-border e-commerce deployment. Our major findings about the situation in the present and trend in the future in China’s retail industry include: · A slowing economic growth, consumption upgrade, emerging industries and the emergence of online and mobile shopping have grabbed a significant share of offline retailers and resulted in the slowdown in the growth rate of the latter. At the same time, constantly rising house rents and labor expenses have put tremendous pressure on the costs of running businesses. In 2014, growth in sales slipped to 5.1% among top 100 chain retailers and net profit dropped to 2.08%, a 0.03 percentage points below last year’s figure.

China Power of Retailing 2015 2 · The slump environment has further differentiated the operating results across retail enterprises. It has come to our attention that enterprises with a national operation have outperformed their regional counterparts thanks to the economy of scale and their mature operational and managerial mechanism. In terms of the type of operation, shopping malls and convenience stores have maintained in a growth trajectory due to their stronger capability of defending themselves from e-commerce and the upgrade and transformation they have done to adapt to changing consumer needs. Although businesses have made the attempt to fend against risks by diversifying their types of operation, the operational data collected this time prove otherwise: Businesses with only one type of operation have delivered better results than those with multi-types of operation, suggesting that businesses should take a cautious approach toward transformation. · Integration in the retail industry has picked up in speed where businesses seek to break through by mergers and acquisitions. Foreign companies begin to feel increasingly fierce competition from local rivals. More M&A deals are concluded among Chinese enterprises that are more inclined in M&A across different types of operation. · The rapid development in internet technology and logistics has fueled the continuous growth in the size and share of e-commerce market. · Physical retail industry is undergoing an accelerated transformation and restructuring. More stores will be closed to further optimize commercial structure and more emerging technologies will be adopted to differentiate operations. · The entire retail industry is switching to O2O all-channel operations where the last- kilometer distribution remains a critical factor in consumer experience. · Cross-border e-commerce emerges to be a new growth engine, steadily bringing up shares in import. B2C and B2B will grow hand in hand. While internet giants have intensified their efforts in making cross-border deployment, physical retailers are wasting no time in testing the water of cross-border e-commerce. · Mobile shopping has grown to account for nearly half of the market of online shopping and is showing the tendency of dominance. The increasing infiltration of mobile payment technology has further boosted the transactions on the mobile platforms. China Power of Retailing 2015 is published jointly by Deloitte China and China Chain Store and Franchise Association (CCFA). Produced on the basis of analyses of sample data collected from 206 enterprises that responded to the questionnaire we sent out to a total of 208 enterprises, and in-depth interviews we conducted with top retailers, the report offers insights into the trend of the retail industry in China and provides preliminary advice on the transformation of retail businesses.

China Power of Retailing 2015 3 Contents

I Macro environment ...... 5

II Retail industry – overview and trend ...... 14

III Operating conditions of hypermarkets and supermarkets ...... 37

IV Operating conditions of convenience stores ...... Error! Bookmark not defined.

V Operating conditions of department stores and shopping malls ...... Error! Bookmark not defined.

VI Operating conditions of specialty stores ...... Error! Bookmark not defined.

Appendix: 2014 Top 100 Chain Store Enterprises in China ...... 75

China Power of Retailing 2015 4 I Macro environment

1.1 International macro environment Global trend Declining oil prices Global oil price has declined more than 50% from its level in the first half of 2014, mainly triggered by the increase in the value of the US dollar, expected increase of oil supply in the global market and a decrease of intensity of oil consumption by global economy. The decline in oil prices has a widespread impact on the global economy. It has alleviated the inflationary pressure off all the countries, especially the developed markets such as US, Europe and Japan, and has lifted the purchasing power of oil consumption states such as Japan, India, US and Europe. In the meantime, the decline of oil prices is more likely to add fuel to the economic growth than does an increasing oil price. For oil exporting countries like Russia, Iran, Venezuela and Nigeria, however, a slump oil market has clearly deteriorated their international balance of payment and frustrated their economic growth.

Oil prices may continue to fall in the short term. Considerable new oil production capacity is in the pipeline in the US and is expected to go into operation in 2015, causing crude oil inventory to pile up continuously. In the long term, a depressing oil price may suppress the investment on fracking. As a matter of fact, we have noticed a cut in the number of drilling licenses issued and the amount of capital expenditure in oil companies. As a result, the reduction in oil production by the US may come at the time when global demands start to pick up, which, if materialized, will certainly cause oil prices to rebound. Such a speculation may become reality in as short as a couple of years. A rising oil price will translate into inflation and add pressure on debt repayment in oil consumption nations, leaving them with no choice but to adopt a tightening monetary policy. This is at least true in the US. An oil price hike will, on the other hand, benefit oil exporting countries such as Russia, Iran, Venezuela, and Mexico, in particular.

A stronger US dollar A remarkable trend for the period from 2014 to early 2015 is the sharp rise in the value of US dollars against most of other major currencies. Many factors have contributed to the trend: a weak oil price, a stronger economic growth and expected rise of interest rate in the US as well as the more active monetary policies introduced by Europe, China and Japan while experiencing sluggish growth. The impacts of a stronger US dollar are multifold. Domestically, a stronger US dollar will make imported goods cheaper and thus have the effect of keeping inflation in check, allowing more time before the Fed has to raise the short-term interest rate. Internationally, a rising US dollar will trigger inflation in all other countries, which although benefits countries with unreasonably lower inflation

China Power of Retailing 2015 5 rates such as Europe and Japan, may not sound pleasing to many emerging economies. In fact, some emerging markets have adjusted the short-term interest rate up as a way of stabilizing home currency and battling inflation, only to see their economic growth to slow down. Moreover, to the US dollar debt-ridden companies from emerging economies, a stronger dollar means a heightened burden in debt repayment and thus a higher debt risk. Such a debt has quadrupled in the past seven years. Looking forward, although it is impossible to accurately forecast foreign exchange rate, it is highly likely that the US dollar will continue the trend of appreciation.

Important markets overview US The US economy is picking up speed and will witness the fastest growth in 2015 since 2005. Despite a robust economy in general, the first quarter of 2015 slumped, partly due to the unsatisfactory economic conditions in many places in the US, or simply reflecting the impacts by the sluggish economy in other countries and by a stronger US dollar. However, the most encouraging data came from a surprisingly robust job market. Encouraging signs are also visible in the area of business investment that suggests a possible come-back. The real estate industry has been underperforming in the US economy. Although data from real estate have been fluctuating in the past year as a result of high mortgage rate and housing price, coupled with student loans that often hinder first-time buyers, the industry has a promising medium-term prospect as housing prices stabilize, mortgage rates go down and more jobs are added to the market, creating vast potential needs.

In addition, factors such as drastically falling crude oil price have kept the US domestic inflation rate far below the Fed target of 2.0%, making it possible for the Fed to raise interest rate before the end of this year. Furthermore, lower inflation rate and energy price have played a role in boosting consumer’s purchasing power. Unlike the situation in the past few years, fiscal and budgetary control has not been tightened in the US. A sharp decline in budget deficit, thanks to a strong economy, has almost lifted the political pressure to deal with budget deficit off the US government.

In the long run, the United States will have to face the conflict in its population structure. The gap between the increase in retired population and a lagging working population will drag down economic growth, begin worsening budget deficit around 2025 and make it more difficult to fund the pension accounts. Demographically, possible solutions include increasing the number of immigrants, pushing forward the average age of retirement, collecting more taxes that are used to fund the government’s pension programs, and encouraging people to save more for the retirement.

China Power of Retailing 2015 6 Europe The economy in Eurozone has shown some signs of improvement. Despite a weaker- than-expected economic growth, some positive indicators seem to suggest that the situation is getting better. These include a strong job market, rising retail sales, improvement in manufacturing industry performance, and a partially improved credit market condition. Needless to say, they are far from enough. The major issue comes from a sluggish credit market that has curtailed the number of jobs available on the market to a lower level and kept the unemployment rate high. A sluggish credit market is due to many reasons. For example, shaky banks try to restructure their assets by selling off risky assets and restraining from adding new risks. Worries about sovereign risks and panics over a possible deflation have worsened the risk situation and are haunting the peripheral countries in Europe. Although a moderately easy monetary policy has increased the broad money supply, banking credit available to private sectors continues to fall.

To deal with the problems in the credit market, European Central Bank has introduced a more radical monetary policy recently, including setting an extremely low interest rate, granting low-interest-rate loans directly to banks (on the condition that these loans be extended to private sectors), and most importantly, purchasing government bonds, namely the measure more well-known as “QE”. While preliminary signs are positive, QE alone is unlikely to bring back a strong economic growth. Other measures needed by Europe include a more slack fiscal policy, a deeper economic restructuring and financial integration among major countries in Eurozone.

Japan The large tax hike has failed its purpose and has thrown Japan into recession since 2014, causing both the consumer expenditure and business investment to shrink. Right after he was sworn in about two years ago, Shinzo Abe immediately grabbed people’s attention by putting forth a radical economic policy represented by “three arrows”, the so-called “Abeconomics” – fiscal stimulation, loose monetary policy and structural reform (in essence, to lift control and free trade), among which only the arrow of monetary policy was shot out. According to this policy, Japanese banks implemented unrestrained QE measures aimed at an eventual 2.0% inflation rate, which would suppress the Japanese Yen, uplift securities’ prices, increase the level of inflation and keep real interest rates at a lower level. Initially this policy went well as planned but soon derailed. The salary level has not shown the promised change but the real consumer purchasing power has diminished that has negatively impacted the consumer expenditure. Sluggish demands from other countries that have not shown the willingness to cooperate have sunk the Japanese export. The most severe problem, however, is caused by the massive tax hike implemented in April 2014. The policy was ready for execution as early as the time when Abe took office. Its impact has been catastrophic and has led to the current economic recession.

China Power of Retailing 2015 7 In November 2014, Shinzo Abe announced to postpone the second round of tax hike that had been scheduled to kick off in October 2015 for 18 months. How he shoots his third arrow remains a problem. Will he deliver on his initial promise to push forward the reforms that will without any doubt meet with all kinds of political resistance, such as labor market liberalization, removal of controls on product market, free trade, change of corporate governance and encouraging females to enter the labor market? Abe has taken some actions on the last two reforms, but supporters of Abeconomics are now hoping that Abe can solve all these problems, which, if realized, may have a positive impact on enterprise productivity and may boost enterprise confidence and thus rejuvenate investment.

Compared to the US, Japanese banks are adopting an extremely easy monetary policy. It is estimated that, if walking down the current path, the relative weight of the assets of the Central Bank over GDP will increase significantly, but whether it will bring the inflation rate to the level that the government needs remains unclear. Japan has a very strong deflation mentality and is hard to let go. For the time being, the policy has produced a greater impact on the price of assets than it has on inflation, and may remain this way in the future.

1.2. Domestic macro environment The Chinese government’s efforts to turn the slowed economy around have not stopped it from deteriorating. The 7.4% economic growth rate in 2014 has been the slowest since 1990. The government expects to see a growth rate of 7.0% this year. What has caused the slowdown? First of all, major export markets like Europe have been weak. Even the US market is not what it used to be. The constantly rising salary level and exchange rate in China have weakened China’s export competitiveness, and have caused the capacity to migrate from China to lower-cost regions such as Vietnam and Indonesia.

Secondly, the Chinese government has been trying to restrain the shadow banking from growing out of control. The previously rapid inflation of shadow banking has been blamed as causing over-investment in real estate, infrastructure and heavy industry, therefore creating more NPA and threatening the stability of the financial system. However, restriction on this type of investment has the side effect of slowing down the economy. The government is stuck in a dilemma: control the financial risk but not to halt the growth. It has taken measures to keep the size of shadow banking loans from growing out of control and, in the meantime, try to vitalize more kinds of traditional credit through a loose monetary policy. Indeed, both the interest rate and bank deposit reserve ratio have been lowered. However, given the sizable over-capacity in real estate and manufacturing industry, whether the loose monetary policy will lead to more lending on the market or the increased lending will bring desired benefits remain to be seen. The worst case scenario is that it may end up in more losses in economy as more loans aggravate the problems of over-capacity and rising wholesale prices.

China Power of Retailing 2015 8 Domestic consumption has grown to be a new driving force Figure 1-1: Nominal growth in industry value-added and total retail sales of consumer goods (%)

13.0

12.0

11.0

10.0

9.0

8.0

7.0

6.0

5.0

Nominal growth in total retail sales of consumer goods Growth in industry value-added

Data source: Wind

The above chart shows that while VAI continues to dip, growth in total retail sales of consumer goods, although decelerating, has been much faster than that of domestic industry value-added. Data from the second quarter of this year indicate that overall consumer market is stabilized and is showing signs of growing. Under the new normal economic circumstances in the future, the consumer market is expected to bring hope to the Chinese economy. In the meantime, a weakening oil price that has alleviated domestic inflationary pressure and a stabilizing CPI will give more leeway to the government in the selection of monetary policies and will play a positive role in encouraging business investment and individual consumption. Another force that is significantly driving consumption comes from the emerging consumer market including education, tourism, cultural and entertainment activities, which has been booming due to the accelerated urbanization process and a growing per capita income.

China Power of Retailing 2015 9 Figure 1-2: Urban and rural resident consumption expenditure (%)

Urban and rural resident consumption expenditure Urban and rural resident consumption expenditure 100.0%

80.0%

60.0%

40.0%

20.0%

0.0% 1995199619971998199920002001200220032004200520062007200820092010201120122013

Traditional consumption Emerging consumption

To further develop China’s consumer market, the monopoly by the state-owned enterprises in the market must be reduced or lifted. Currently, state-owned enterprises are holding 50% shares in industries such as education, sports, culture and art, preventing these markets from growing at an unprecedented speed. Changes are taking place, to our delight, to bring down the shares of state-owned enterprises. More national policies are introduced to encourage unrestrained competition, which will make the market more dynamic.

Figure 1-3

120.00%

100.00%

80.00%

60.00%

40.00%

20.00%

0.00%

of investment by state-owned enterprises over total investment in 2011 of investment by state-owned

China Power of Retailing 2015 10 “Internet +” reshapes the real economy and drives consumer industry through innovation

Internet+ has become a nationwide hot topic. The Chinese internet industry, although a late starter, has demonstrated evident late-mover advantages. Compared to developed countries in Europe and US, China’s internet industry has been growing explosively at a much faster rate than the other countries. It also has a much higher penetration rate. Online shopping accounts for more than 10% of total consumption in China, while in the US it is a mere 5%. In 2014, the total retail sales of physical goods in China were about 80% of those in the US but its online sales were 150% of those in the US. In the future, e- commerce will be a backbone industry in China’s national economy.

1.3 Recent policies Concerted measures introduced by multiple government departments send cross- border e-commerce into the fast lane Opinions on the Implementation of Policies in Support of Cross-border E- commerce Retail Export

Ministry of Commerce announced on its official website on August 29, 2013 that General Office of the State Council relayed the Opinions on the Implementation of Policies in Support of Cross-border E-commerce Retail Export jointly issued by Ministry of Commerce and other government departments, which introduced six specific measures about cross-border e-commerce in the areas of customs, inspection and quarantine, tax and collection and payment of foreign exchanges. These measures will be taken as a coordinated effort among nine ministries and commissions including general administration of customs, ministry of finance, and ministry of commerce. This is the first time for the Ministry of Commerce to officially announce a policy in favor of cross-border e-commerce.

Since its announcement, the new policy has gone into trial implementation in the five cities of Shanghai, Chongqing, Hangzhou, Ningbo and Zhengzhou that had been pilots in the customs clearance service for cross-border e-commerce trade. Since October 1, 2013, it has become effective in all the other eligible places across the country.

Circular of General Administration of Customs #12, 2014

In February 2014, in order to promote retail import and export business in cross-border e- commerce, facilitate customs clearance by commercial entities, standardize customs administration and allow for the compilation of customs statistics, the General Administration of Customs (GAC) has introduced a new customs supervision code: 1, The new code "9610" relates to " Cross-border Trade by E-commerce", or " E-commerce" for short. This new code is applicable to cross-border trade initiated by individuals or e-

China Power of Retailing 2015 11 commerce enterprises via those e-commerce platforms recognized by China Customs. It applies to all inbound and outbound retail goods subject to cross-border e-commerce that have been processed through the mode of “clear by commodity lists and declare in total” (with the exception of any import or export retail goods traded via e-commerce platforms among special customs supervision zones or bonded customs supervision premises). 2, E-commerce enterprises carrying out cross-border e-commerce import-export trade under customs supervision code "9610" or e-commerce enterprises, payment enterprises and logistics enterprises that are involved in cross-border e-commerce should file a record with China Customs in line with the relevant regulations. They should also submit their real-time data relating to transactions, payments, warehousing and logistics through the e-commerce platform.

The State Council Printed and Distributed on March 12 the Official Reply to Approve the Establishment of China (Hangzhou) Cross-border E-commerce Comprehensive Pilot Zone

In March 2015, the State Council gave permission to Hangzhou to set up China Cross- border E-commerce Comprehensive Pilot Zone, symbolizing the beginning of cross- border e-commerce pilots in China. The progress made in the pilot zone will offer copiable and expandable mature experiences to boost the growth of e-commerce in China and provide fuels to the entire industry. In April 17, the State Council issued Some Opinions on Improving Operations in Ports of Entry to Support Foreign Trade Development, which put forth 22 measures in six areas including optimize services in ports of entry, drive a steady growth in foreign trade, intensify the construction of ports of entry, promote foreign trade transformation and upgrade, improve the environment for foreign trade development, further open up ports of entry and enhance the level of openness, reinforce the foundation in ports of entry, increase the ability to facilitate the economic and social development, and step up the organization and leadership function over the operation of ports of entry.

The State Council issued the Guiding Opinions on Driving a Healthy and Rapid Development in Cross-border E-commerce

On June 20, 2015, General Office of the State Council issued the Guiding Opinions on Driving a Healthy and Rapid Development in Cross-border E-commerce (Guobanfa [2015]46), the first of its kind that completely reflects the opinions of the State Council regarding cross-border e-commerce. It gives opinions in 12 areas including support domestic enterprises to conduct foreign trade business by e-commerce, encourage capable enterprises to grow bigger and stronger, optimize supporting measures in customs supervision, improve quarantine and supervision policies, plan on policies about import and export taxations, improve e-commerce payment and settlement management, provide favorable fiscal and financial support, build a comprehensive service system, standardize operational behaviors and intensify bi-lateral and multi-lateral international cooperation. As a keynote in the development of “internet + foreign trade”, it reassures

China Power of Retailing 2015 12 the policy supports by the government to cross-border e-commerce. If 2014 symbolizes the beginning in cross-border e-commerce in China, it soon turns bullish in 2015 when quite a few trade policies are introduced that voice support to cross-border e-commerce. From foreign trade to e-commerce, from “one road one belt” to “free trade pilot zone”, cross-border e-commerce has emerged to be an important area in international trade and cooperation.

The State Council issues guiding opinions on commercial development and encourages internet enterprises to go public in domestic stock market.

On May 7, 2015, the State Council issued the Opinions on Driving the Rapid Development of E-commerce to Create New Economic Engines, encouraging qualified internet enterprises to list in domestic stock markets. It requires that all relevant government departments intensify support in financial services within respective functions, establish and improve diversified and multi-channel investment and financing mechanisms that adapt to the development of e-commerce, support commercial banks, guarantee inventory management organizations and e-commerce enterprises in providing various form of intangible assets or movable assets-pledged financing services. It encourages commercial banks, commercial factoring organizations, and e-commerce businesses to carry out supply chain financing, commercial factoring business to further extend e-commerce businesses’ financing channels, guides and drives venture investment funds to intensify support to e-commerce start-ups. In addition, it clarifies three principles: Firstly, proactively drive the development and solve various conflicts and problems in the development of e-commerce. Secondly, gradual standardization. Streamline administration and institute decentralization, loose control but in the meantime tighten supervision. Businesses may do what laws do not explicitly prohibit and the governmental should not step in the territory they are not authorized to do by the laws, keeping the administrative interference in the e-commerce market to the minimum. Thirdly, offer more guidance to help businesses understand can capitalize on the trends.

China Power of Retailing 2015 13 II Retail industry – overview and trends

2.1 Overview Growth in brick-and-mortar retail continues to slow down with mounting cost pressure

The slowdown in macro economy and income of urban residents continue dragging the retail sales down. The total retail sales of consumer goods in 2014 reached RMB26,239.4 billion, representing a yoy nominal growth of 12% and a drop in growth for five years in a row. Conditions in top 100 retail chains were no exception: The growth in sales continued to fall from 21% in 2010 to 5.1% in 2014 and the market share over the total retail sales of consumer goods continued to dwindle from 11% in 2010 to 8% in 2014. The expansion by the top 100 retail chains slowed as well: the growth in the number of stores dropped from 9.8% in 2010 to 4.2% in 2014. 23% of these enterprises had a negative growth in the net number of stores while 7% of them remained at the same level as a year before.

Figure 2-1 Total retail sales of consumer goods and growth in China

300,000 20.0% 18.3% 17.1% 18.0% 250,000 16.0% 14.3% 13.1% 14.0% 200,000 12.0% 12.0%

150,000 10.0%

8.0% 100,000 6.0%

4.0% 50,000 2.0%

0 0.0% 2010 2011 2012 2013 2014 Total retail sales of consumer goods (RMB100million) Growth%

Data source: Wind, Deloitte Analytics

China Power of Retailing 2015 14 Operations in physical retail enterprises are under tremendous pressure. A sluggish economic growth, consumption upgrade, rapid emergence of new types of operations, online and mobile shopping combine to slow the revenue growth in these enterprises. Constantly rising operating costs further narrow the profit margin and therefore separate these enterprises apart by operating performance. Figure 2.3 reveals that the overall rents and labor expenses in the sample enterprises, growing by 7.0% and 7.7% respectively, remained at a higher level, while utility expenses dropped slightly by 2.7%1, showing how rising rents and salaries impacted the costs in these enterprises. The above difficulties forced the enterprises to focus more on improving operational efficiency. It is evident from the collected data that businesses tried to control costs by downsizing their workforce, resulting in a drop in the number of employees per store by 0.8% in 2013 and 1.2% in 2014 in average.

Figure 2-2 Ratio of retail revenue by top 100 retail chains over total retail revenue of consumer goods

25000 0.12 20,963.8 11.0% 20,451.7 0.1 20000 9.1% 18,927.6 17,269.8 16,736.6 9.0% 8.6% 0.08 15000 8.0% 0.06 10000 0.04

5000 0.02

0 0 2010 2011 2012 2013 2014

百强销售额（亿元）Retail revenue by top 100 占社会消费品零售总额Ratio over total retail revenu比例e of retail chains consumer goods

1 2013 samples growth of the rent, employee salary and utilities are respectively 1.9%, 10.2% and 0.9%.

China Power of Retailing 2015 15 Figure 2-3 Three expenses and growth rate in sample enterprises

45000.0 10.0% 38893.6 7.7% 40000.0 36356.6 8.0%

35000.0 32519.0 7.0% 30189.6 6.0% 30000.0

25000.0 4.0%

20000.0 2.0%

15000.0 0.0% 10000.0 8369.5 8139.8

-2.0% 5000.0 -2.7% 0.0 -4.0% Rents (10,000 Yuan) Employee salary (10,000 Yuan) Utility (10,000 Yuan) 2013 2014 2014 Growth % Figure 2-4 Average growth rates in the number of employees in the stores of top 100 retail chains

0.0% 2012 2013 2014 -0.2%

-0.4%

-0.6%

-0.8% -0.8% -0.8%

-1.0%

-1.2% -1.2%

-1.4%

Average growth rate in the number of employees in the stores of top 100 retail chains

Data source: wind, CCFA, Deloitte Analytics

Falling net rate of profit separates businesses in operating results A sluggish revenue growth, slowed expansion and constantly rising costs continue eating in enterprise profits. According to data from questionnaires for retail chains in 2014 administered by CCFA, although the average gross margin % of top 100 retail chains was 16.4% and slightly higher than a year before, the net profit margin % dropped by 0.03 percentage points to 2.08%. The falling revenue and profit in the entire industry further separated businesses in operating results. Among the 206 sample enterprises, 52, or

China Power of Retailing 2015 16 27%, reported a drop in revenue, while 31, or 16%, reported a revenue growth of over 20%. Out of the 144 responding enterprises that disclosed gross margin, 39 showed a drop compared to 31 that reported a growth of more than 20%. It indicates that even under the circumstances of a gloomy market, climbing costs and brutal competition from e-commerce, enterprises may have a better chance of staying in the lead through a well- planned strategy, articulated operation and outstanding marketing and promotional activities.

Figure 2-5 Distribution of revenue Figure 2-6 Distribution of gross growth in sample enterprises margin growth in sample enterprises

over over 20% negative 20% negative 22% growth 16% growth 27% 27% 10%-20 % 18% 10%-20% 19%

0%-10% 0%-10% 32% 39%

Data source: CCFA, Deloitte Analytics

Enterprises with national operations outperform their regional counterparts Among the sample enterprises in 2014, 104 (51%) restricted their operations within a province, 54 (26%) operated across (2-5) provinces and 48 (23%) had a nation-wide operation (in 6 or more provinces). The enterprises with national operations were more sizable and had an average annual operating income of RMB26.5 billion that almost doubled those with cross-provincial operations and was 8 times of those operating within a single province. Economy of scale and mature operating and managerial mechanism both contributed to the better operating results of businesses with national operations. Below figures tell that businesses that operated nationally outperformed those of a regional nature (including cross and intra-province) in both revenue growth and gross margin. To the contrary, businesses that operated across provinces had barely satisfactory operating results. Their revenue growth and gross margin, at 16.6% and 4.8% respectively, were lower than those that operated within a single province despite their larger size than the latter. It seems to suggest that businesses operating across a few provinces faced more challenges. They had to compete head-on with those that focused on and were more familiar with the environment in a single province, while at the same time kept alert not to be outflanked by the national giants. Whether the high-investment

China Power of Retailing 2015 17 and low-profit business expansion strategy will succeed is subject to the test by the market.

Figure 2-7 Comparison of key financial indicators among retail enterprises with national, cross-provincial and single-provincial operations

30.0 26.5 25.2 25.0

20.4 20.0 16.6 14.5 15.0

9.6 10.0

5.7 4.8 5.0 3.4

- Scale of operation (10 billion yuan) Operating income growth (%) Gross margin (%)

Single-provincial operation Cross-provincial operation Nation-wide operation

Data source: CCFA, Deloitte Analytics

Build multi-dimensional retail channels through multi-type operations Facing challenges by structural upgrade in consumption, differentiation in levels of consumption and emergence of mobile and online shopping, retail enterprises are trying to build multi-dimensional retail channels by diversifying the types of operation so that their operational advantages can be maximized. Better Life Commercial Chain Share Co. adopts a mode of multi-type operation that comprises “supermarket + department store + electrical appliance” to optimize and integrate its primary business; Tianhong (Rainbow) Department Store adds shopping malls and convenience stores to the traditional department stores and expands the previously single type of operation that solely relies on offline physical department stores to an all-channel multi-type mode that integrates offline and online channels. Metro and Carrefour both introduce convenience stores in China. In fact, 60% of the enterprises sampled in this 2014 survey carry out business operations in multi-types including supermarkets, department stores, shopping malls, convenience stores, and e-commerce etc.

The multi-type operation is both a forced choice in a harsh business environment and a natural result in the development of the businesses, and is adaptive to the change in consumer needs. Thanks to the elevation of income, consumers today are putting more emphasis on individualism, customer experience, efficiency and effectiveness, and thus,

China Power of Retailing 2015 18 are more diversified in needs. Both the dull “one-stop” shops and undistinguishable standardized commodities and services have gone out of fashion and are hard to appeal to consumers. Changes in consumer needs inevitably lead to the transformation of retail businesses that choose to devise new operating standards, commodity structures and marketing and promotional strategies accordingly, giving rise to the mode of a multi-type operation. The new mode becomes popular also because it increases the likelihood of achieving a synergy. Businesses may share customers among different types of operation under the same brand name and a larger scale gives them more bargaining power against upstream suppliers. Furthermore, multi-type operations help diversify risks and increase profits. Better Life Commercial Chain Share Co, as an example, has maintained a rapid growth mainly as a result of its multi-type operational strategy.

Despite all the benefits a multi-type operation may offer, over-optimism should be guarded against. After we classify the sampled enterprises into two groups by the standard of single-type operation (such as Gome and Suning ) or multi-type operation (such as China Resources Vanguard, Lianhua Supermarket) and compare the operating performances between the two groups, we’ve found out that enterprises with single-type operations outperform those with multi-type operations in both profitability and growth, reflecting, to a certain degree, the difficulty that businesses may encounter when expanding into multi-type operations. We think that although multi-type operations may benefit the businesses in optimizing resource allocation to meet the needs of different consumers by integrating strengths of each operational type, it is imperative for businesses undergoing a transformation to thoroughly understand their competitive strengths and weaknesses, continue building profound core competency in the primary business, and intensify concerted development and dynamic integration among different types of operation.

Figure 2-8 Comparison of key financial indicators between retail businesses with multi-type and single-type operations

30.0 26.1

25.0

20.0

14.7 15.0 13.0

10.0

4.0 5.0

- Operating income growth (%) Sales gross margin (%)

Single-type operation Multi-type operation

Data source: CCFA, Deloitte Analytics

China Power of Retailing 2015 19 Shopping malls and convenience stores demonstrate a trend of better growth As the slowdown of growth in overall retail industry has differentiated different types of operation in operating performances, shopping malls and convenience stores have demonstrated a better growth trend. Data from enterprises responding to the CCFA’s questionnaire indicate that sampled shopping malls and convenience stores recorded an average revenue growth for the two years of 2013 and 2014 by 6.7% and 3.6% respectively, while the growth of hypermarkets, supermarkets, department stores and specialty stores for the same period are 1.7%, 0.5%, -1.2% and -3.3%. Due to their huge size, inclusiveness, and focus on customer experience, shopping malls are viewed as a “safe harbor” in retail industry and have delivered a better growth result in recent years. We also notice that the fever in the construction of shopping malls spreading among many businesses makes the competition fiercer and the pressure on profit heavier. It is foreseeable that shopping malls will be built to reflect differentiation, brand names, and chain operations in the future. In comparison, convenience stores will continue growing rapidly to penetrate deeply in mature markets and fill the void markets in the years to come due to lower investment, shorter cycle to maturity as well as convenience in space, time and service and closeness to consumers.

Figure 2-9 Comparison between average revenue growth in sampled stores of different types of operation for the two years of 2013 and 2014

8.0% 6.7%

6.0%

4.0% 3.6%

2.0% 1.7%

0.5%

0.0% Shopping mall Convenience store Hypermarket Supermarket Department store Specialty store

-1.2% -2.0%

-4.0% -3.3%

Data source: CCFA, Deloitte Analytics

Integration in the retail sector picks up speed and the capital market remains vibrant The year 2014 witnessed a noticeably faster pace in mergers and acquisitions in the retail sector where companies were actively in hunt for M&A opportunities and targets. According to statistics from Merger Market, compared to 2013, the total scale of M&A

China Power of Retailing 2015 20 deals in the retail sector in China increased 4.5 folds, scale of M&A deals among domestic Chinese enterprises increased 4.73 folds, scale of M&A deals where foreign companies acquired Chinese enterprises increased 4.97 folds, while scale of M&A deals that involved Chinese companies acquiring foreign enterprises fell by 49.8%.

Mergers and acquisitions as a whole demonstrated some new characteristics in 2014:

Promising M&A prospect M&A deals offer both parties the benefit of making up for one’s shortages with the other’s advantages, sharing of resources, on/offline integration and O2O deployment to drive the two-way integration between physical commerce and e-commerce. In March 2014, Alibaba Group made a HK$ 5.37 billion strategic investment in Intime Retail (Group) Co. Ltd to form a joint venture that aimed at building an on/offline-integrated commercial infrastructure system for the future. Once the deal is concluded, Alibaba will hold 9.9% stake in Intime Retail (Group) Co. Ltd as well as HK$-denominated convertible bonds worth approximately 3.71 billion. It is stipulated in the contract that in the next three years, Alibaba Group is entitled to convert the convertible bonds to the common shares of Intime Retail (Group) Co. Ltd so that it will ultimately have no less than 25% stakes in the later provided that legal requirements are fulfilled.

Foreign companies encounter strong competition from local rivals The brutal competition in the retail business and uncertainty in the international economic landscape at present cause foreign retail companies to favor more prudent routes in terms of capital distribution and mode of profitability. On the other hand, having seen the potential of huge demand in the future, local retailers have sped up and intensified their pace of opening up new stores. It is more likely that Chinese companies will try to grab shares in the international market through foreign brands. In May 2014, CR Vanguard, the largest retail company in China, successfully acquired the foreign-owned Tesco to form a multi-type retail joint venture company, in which Tesco invests its China business in cash and hold 20% stake while CR Vanguard holds the remaining 80%. Following the deal, all the 135 former Tesco stores become CR Vanguard stores and the Tesco brand is discontinued in China.

M&A across types of operation becomes increasingly popular The retail industry has unveiled its M&A activities across types of operation. Businesses seek to have a sustainable profitability through mergers and acquisitions that facilitate the operating strategy adjustment and the attainment of a diversified development. On December 22, Wu-Mart signed a contract with Kingfisher Group of UK and agreed to pay 140 million in pound sterling (equivalent of RMB1.4 billion) in exchange for 70% stocks in B&Q China. Following the conclusion of the deal, Kingfisher still holds 30% of B&Q’s stocks. This acquisition is viewed in the industry as across two types of operation that are farthest apart.

China Power of Retailing 2015 21 Dynamic M&A activities among Chinese companies The total size of M&A deals among Chinese companies in 2014 alone was far more than that of 2011 to 2013 combined. It also set the record in terms of the single-transaction amount. Under the circumstances of a slowing macro economy, Chinese retail companies seek to rapidly optimize resource allocation, increase market share and gain competitive edge through M&A and integration. In May 11, 2014, Better Life Commercial Chain Share Co., Ltd announced its acquisition of 100% stake in Guangxi Nancheng Department Store Co. Ltd. The total acquisition amount of RMB1.57 billion makes it the largest M&A transaction among Chinese companies in the retail sector in recent years.

Figure 2-10 M&A scales in retail sector ($million)

14000 39

12000

10000

8000 36

6000 33 4000 13 24 2000 9 13 48 32 7 12 3 0 2011 2012 2013 2014

M&A among Chinese companies Foreign companies acquire Chinese companies Chinese companies acquire foreign companies

2.2 Trends Online retail continues to grow at a high speed The online retail market continues its momentum of rapid growth in 2014 with the market share further expanding. The development of e-commerce remains fast thanks to the popularization of internet and network terminals, constant innovation in payment technology and speedy improvement in the efficiency in logistics and distribution. According to the data of 2014 China Online Shopping Market published by iResearch (see below), the total amount of transaction in China’s online shopping market in 2014 reached 2.81 trillion yuan, representing a yoy growth of 48.7%, 10.7 percentage points lower than a year before, and for the first time in recent years the 50% level is broken. Regardless, the share of online shopping market continues rising. In 2014, revenue from online shopping accounted for about 10.71% of the total retail sales of consumer goods with the online penetration rate breaking 10% for the first time, indicating that the competitiveness and operating dynamics of online shopping are way ahead of the traditional physical retailing. With an exceptionally fast development in mobile shopping

China Power of Retailing 2015 22 and the channels getting closer to consumers, the online retail market is expected to remain growing at a rapid rate.

Figure 2-11 Scale of transactions in the online shopping market in China

45000 80.0%

40000 70.0%

35000 60.0% 30000 50.0% 25000 40.0% 20000 30.0% 15000 20.0% 10000

5000 10.0%

0 0.0% 2011 2012 2013 2014 2015e

网络交易规模（Scale of online 亿元） 增长率Growt%h % transactions (RMB100 million) Data source: iResearch

Physical retailers speed up transformation and intensify efforts to enhance customer experience Record number of physical chain stores are closed Statistics show that a total of 201 stores were closed by major national retail chains (department store, supermarket) in 2014, representing a yoy growth of 474.29% from the 35 closed stores in 2013 and a new record in history. Among them, 12 are department stores and 146 are supermarkets. Attention needs to be given to the fact that 118 closed stores were owned by foreign retail enterprises, accounting for 75% of the total number of the closed stores (including the Sino-foreign joint venture Postmark). Tier II and tier III cities in Jiangsu, Zhejiang and Anhui have seen most stores closed. A document internally circulated in China Wanda Group on July 13, 2015 revealed its plan to close more than 40 stores that incurred heavy losses in Jinan, Tangshan, Jiangmen, Wenzhou, Shenyang and Jingzhou in Hubei. It also planned to make some adjustments to and reduce the operating spaces in some stores in Baoshan of Shanghai, Quanzhou, Xiangyang and other places. Affected by factors such as rental contract expiry, structural adjustment, weak profitability and transformation, physical retail enterprises have chosen to close some stores to better optimize their business deployment.

China Power of Retailing 2015 23 Physical retailing embraces new technology and emphasizes customer experience improvement Despite many challenges they are facing now, physical stores will not disappear. It becomes extremely critical for physical stores to differentiate operation and enhance customer experience if they want to increase sales. Emerging technologies used in routine operations can help provide convenience to the customers and also lift up the store’s management level. These innovative technologies provide strong support to retailers in precisely detecting consumer needs, guiding the route in consumption, and satisfying consumer behaviors, thus effectively increasing opportunity and volume of transactions. In the meantime, they enable retailers to offer richer, more fashionable and customized information services to customers. Yonghui’s Bravo YH, Letus’ “future supermarket” and Suning supermarket all shed lights on the development of physical retailing. More factors of technology will be reflected in shopping malls, department stores, mass marketplaces and neighborhood supermarkets to speed up their pace into the age of smart retailing. Major technology applications to be used in the retail industry include:

· Locate consumers and match their locations with their interests. The app is able to retrieve and analyze the information about consumers’ record of consumption and social activities through GPS, indoor map and hotspot technologies. It can then push to the consumers the contents they may be interested in at relevant locations. · Collect data to predict consumer behaviors. By digging in consumers’ data such as where they live, routine schedule, interests and hobbies and social behaviors etc, the app is able to predict the consumers’ next move and provide them with the services and products in which they are likely to be interested. · Real-time scene management. Based on the information about location and environment, the app can adjust itself to meet consumers’ needs on a more customized and precise basis so that it becomes handy to the consumers when they are in need of a certain resource or system.

Retail sector is transforming to an all-channel mode and O2O industry chain becomes complete gradually O2O became the first priority for many physical retail enterprises in 2014. Starting with feiniu.com of RT-Mart and yunhou.com of Better Life Commercial Chain Share Co, many well-known retailers have intensified investment in e-commerce. In the meantime, e- commerce retailers represented by Intime Retail (Group) Co Ltd that received strategic investment from Alibaba Group proactively seek to cooperate with physical retailers, symbolizing that a transformation into an all-channel business by integrating online and offline resources has become the collective action of the retail industry. Data from iResearch show that the O2O market grew to the size of RMB200 billion in 2014 and is expected to reach the size of RMB465.54 billion in 2015. In 2014, the top 100 chain department stores in China contributed a total amount of online transaction of RMB6.1

China Power of Retailing 2015 24 billion at a penetration rate of about 1.6%, which is expected to go further higher in the future when more traditional enterprises open their online business. In 2015, Alibaba invested RMB28.3 billion in Suning Appliance Co., Ltd while JD.com spent RMB4.3 billion to acquire stakes in Yonghui Superstore, marking the arrival of the time when the retail sector becomes two-wheel drived: online and offline. In addition to the multiple and diversified channels of shopping, consumers will experience a change of lifestyle that offers conveniences from life to all kinds of incremental services.

Figure 2-11 Online transaction amount from chain department store enterprises in China

140 10.0%

120 8.0% 100

80 6.0%

60 4.0% 40 2.0% 20

0 0.0% 2010 2011 2012 2013 2014e 2015e 2016e

中国连锁百货企Online transaction业 a线m上ou销nt 售fro额m （ch亿ain元） 中国连锁百货企Online sales pen业et线rat上ion销 %售 fr额om渗 c透hain率（ %） department store enterprises in China department store enterprises in China. (RMB100 million)

Data source: iResearch

Enterprises compete in O2O deployment Taking advantage of the huge online traffic in their respective platforms and through self- marketing, connecting to the platform of a third party or cooperating with traditional large retail stores, the three internet conglomerates BAT (Baidu, Alibaba, Tencent) start to construct all-inclusive O2O ecological chains. The traditional retail enterprises, on the other hand, choose to build their own platforms that have the functions from searching, placing order, making payment to delivery in addition to cooperating with BAT. With the areas of investment made by internet giants increasing, O2O industry chain improving and mobile payment getting more mature, retail enterprises are forced to undergo the transformation into an all-channel business in order to solve problems rising from resource barriers, distribution of interests between online and offline business as well as marketing and promoting.

China Power of Retailing 2015 25 Table 2- 1 O2O deployment

Enterprise O2O deployment Suning.com went live in 2010. Suning later consolidated all the online and offline prices in 2013 and changed its name to Suning Appliance Co., Ltd, poised for an all-commodity market. As an effort of integrating online and offline business, Suning makes the two back- end systems connect to each other. Consumers now can buy anything

that is offered online and when a commodity is out of stock in a certain Suning store, consumers are guided through an online ordering process and Appliance can wait for delivery at home. To enhance the customer experience and service quality, Suning also makes attempts to launch return/change of commodities in physical stores, one-hour express delivery after a commodity leaves the warehouse and smile while service, etc. RT-Mart joined Uitox from Taiwan to establish feiniu.com, which went live on January 16, 2014, in an effort to make up for the limited shelf space in offline stores, create an O2O mode that is based on RT- RT-Mart Mart’s more than 300 physical stores across the country, and deeply integrate online and offline resources to build an all-channel operation that best serves its customers.

Beijing Wangfujing Department Store (Group) Co.,Ltd integrates its From offline to online and offline operations on the foundation of physical stores online through multiple channels in the mode of “N+1”: “N” represents building new channels on the foundation of new technologies, Wangfujing including the web-based official shopping website, web-based platform flagship store, WAP mall on the mobile platform, WeChat Mall, APP, E-shopping guild workbench, in-store self-service terminals and 24-hour virtual storage rack.

It acquired yunhou.com and developed three core products – payment Better Life by earned points, personal consumption finance and pre-paid Commercial services. It integrates and connects consumers and merchants Chain Share through the platform and provides third-party group purchase and Co booking, operation of advertising and online traffic services.

Gome’s O2O comprises of three parts: online “1+1+N” development, online channel + mobile terminal + social joint operation on points and supply platform, in the hope to build consumption scenarios from

searching, placing orders, taking delivery to making payment by

executing an all-channel deployment strategy using mobile internet to Gome connect offline with online channels. In addition to its own online platform, Gome also keeps good partnerships with TMall, Amazon and Dangdang, aiming at constructing a comprehensive open platform.

China Power of Retailing 2015 26 Enterprise O2O deployment

Glorious Oriental acquired Shijitianle Mansion to open up dongpi.wang, which integrates resources and builds platform for the business of logistics and delivery, warehousing, and providing safe shopping environment. The O2O built by dongpi.wang has a physical experience square with a business area of 120,000 square meters near Beijing West Railway Station that showcases commodities it sells, while its online outlet provides free internet marketing services to Shijitianle the merchants that open stores in the physical experience square. Shijitianle has offline stores in Beijing, Shanghai, Shandong and Shanxi. It promotes a concept of “one hundred stores in one hundred cities” – to open up experience stores in the cities selected by quality customers to support delivery of what have been ordered online, as an attempt to reinforce the advantages of dongpi.wang.

LBX Pharmacy online store announced its strategic cooperation with meituan.com in May 11, which, based on the foundation of internet LBX Pharmacy finance O2O, integrates offline stores, online self-run platforms and e- Cross-sector commerce channels to offer diversified medication services to consumers.

Online travel websites join hands with e-commerce giants to establish platforms that benefit both. Recently tuniu.com and JD.com announced their strategic cooperation and JD.com will invest USD350 million to acquire tuniu.com shares. After the acquisition, tuniu.com Online travel will be the exclusive operator for JD’s travel-vacation channel. By websites taking advantage of JD.com’s overseas online traffic and massive customer base, tuniu.com aims to provide better service to customers. In the meantime, JD.com will offer its users more and better online travel consumption experience in the hope to build the best online e- From online commerce platform in China. to offline Tencent builds an O2O ecological chain through WeChat platform as entrance: supported by WeChat payment, it integrates local services Tencent for life including Didi Taxi and dianping.com to create a closed loop that enables online and offline interactions.

As an E-commerce platform specializing in fresh foods, Yummy77 also operates offline neighborhood stores that stracte the customers Yummy77 who have experienced its offline service to its online platform for more business.

Data source: Deloitte Analytics, Processed from publicly available information

“Last-kilometer” delivery may be solved by convenience stores Logistics has not kept pace with the enterprises on the way to transform into the all- channel O2O operations. E-commerce enterprises are hindered by the difficulty in the last-kilometer delivery due to insufficient logistics infrastructure in cities and the varied, sometimes unsatisfactory, service quality in logistics enterprises. The following four

China Power of Retailing 2015 27 methods are taken by e-commerce enterprises in an attempt to solve this problem, among which, the integration of idle resources and smartly taking advantage of neighborhood convenience stores become the key. However, such a mode has pushed up costs for O2O start-ups and prevented O2O enterprises from growing as fast as expected, leaving the ultimate goal of delivery to the door unattained. From a long-term development perspective, many O2O modes need to continue the search for effective ways to lower losses in logistics so that they can outgrow the stage of capital investment and build a functioning industry circulatory system to fundamentally meet the supply-and- demand requirements by businesses and consumers alike.

Figure 2-13 “Last-kilometer” service modes

Invest in Integrate idle Build own distribution service resources to On-the-spot service distribution center spots near provide express neiborhoods services • Fresh food O2O, • Neighborhood O2O • Housekeeping O2O, • Fresh food O2O catering O2O • O2O enterprises build Beauty O2O • Make use of idle • Invest heavily on numerous service • Control resources of logistics resources to distribution centers to spots in the places not service providers who lower costs and fundamentally reduce covered by regular have certain special provide express the delivery time to the logistics service or skills and offer them to delivery services. minimum and more demanding in customers who are in Deliveryman’s after- guarantee the quality logistics. Deliveries are need. For example, work time or off-work of all the goods first made to these aiyibang.com and days may be used to delivered. spots, and then to the helijia.com run an O2O run temporary delivery residents in nearby business that sends errands. Owners of neighborhood, or salarized, specially convenience stores picked up by buyers. trained housekeepers near neighborhood or and nail technicians to office buildings may be service the customers mobilized for delivery and publicizes service for extra contents on their compensation. While respective platforms. doing this, the system dispatches the goods to be delivered to the nearest idle resources who then complete the last stage of the delivery.

Data source: Deloitte Analytics, Processed from publicly available information

Cross-border e-commerce becomes new growth engine and vertical e-commerce businesses continue to emerge. Cross-border e-commerce becomes new growth engine and the share of import keeps rising steadily The cross-border e-commerce transactions in China reached RMB4.2 trillion in 2014, growing by 33.3% on yoy basis. Fueled by favorable state policies, the push by willing industry participants and constant improvement of the industry chain, the cross-border e- commerce is expected to continue expanding at a steadily fast pace. In 2014, 85.4% of cross-border e-commerce transactions came from export and the remaining 14.6% came from export. Although the cross-border e-commerce in China has just started, with the

China Power of Retailing 2015 28 Chinese consumers’ quest for imports surging, the share of import is likely to increase rapidly. However, the impact of state policies will keep the growth in the share of imports by cross-border e-commerce businesses at a steady pace. Shopping overseas provides a new growth engine for the retail industry. It will attract online and offline enterprises from across the world to deploy in cross-border e-commerce, sparking fierce competition.

Figure 2-15 Scale of cross-border e- Figure 2-16 Import & export structure commerce transactions in China in cross-border e-commerce transactions in China

6 100% 5 80% 4

3 60%

2 40%

1 20% 0 0% 2011 2012 2013 2014 2015e 2011 2012 2013 2014 2015e

Scale of transaction (RMB trillion) % of imports % of exports

Data source: CECRC, Deloitte Analytics

Table 2-2 Shopping overseas becomes a new growth engine for e-commerce

Major domestic e-commerce enterprises expand their business externally in 2014. Overseas Examples include g.taobao.com from taobao.com, TMall international, the shopping overseas section on jumei.com, and the cross-border e-commerce project team in expansion Suning. In the meantime, e-commerce conglomerate Alibaba will speed up its penetration into the US market through more investment to expedite business deployment in the US and compete with local brands such as Amazon. Recently, Alibaba continues buying the shares of Zulily to increase its holding of Zulily A shares to 11.5 million that have a market value of USD1.156 billion. It has become the largest foreign shareholder of Zulily, an e-commerce business specializing in mother and baby products in the US.

The gradual easing of cross-border e-commerce policies has attracted foreign e- Domestic commerce enterprises to China’s overseas shopping market. Farmaline, a expansion European large e-commerce pharmacy, has opened a Chinese website where Chinese consumers can purchase more than 30,000 products that are paid through UnionPay and have the purchased products delivered directly to them. Farmaline, as the largest e-commerce business in Belgium easily accessible from many places in Europe, is able to provide the fullest variety of big-brandname commodities from France, Germany and other European countries at cheaper prices than other similar platforms even after logistics costs are added.

China Power of Retailing 2015 29 Data source: Deloitte Analytics, Processed from publicly available information

Factors that contribute to the continuous development of cross-border e- commerce · Leaders from the State Council have put the cross-border e-commerce in high priority. On July 26, 2013, General Office of the State Council issued Some Opinions on Measures to Drive Steady Growth of Import and Export and Structural Adjustment. It introduces specific supporting policies including the classification of subjects that are authorized to operate e-commerce exporting, establishing a new type of customs supervision that adapts to e-commerce exporting and enables statistics by categories, establishing adaptive mode of inspection and supervision, supporting regular collection and payment of foreign exchanges by enterprises, encouraging banking and payment institutions to provide payment service for cross-border e-commerce, adopting adaptive tax policies and building an e-commerce export credit system, helping solve the problems in customs, inspection and quarantine, tax as well as collection and payment of foreign exchanges, etc.

· Set up pilot zones to provide customs clearance service in cross-border e-commerce trade. Pilots are set up in 7 cities including Shanghai, Chongqing, Hangzhou, Ningbo, Zhengzhou, Guangzhou and Shenzhen and focuses are given to bonded import, direct purchase or export. All the brand names in e-commerce, logistics and retail enterprises are solicited to these pilot zones to create an economy of scale to some degrees. In addition, the above policies issued by General Office of the State Council are applicable in all the pilot cities in an attempt to drive the overall cross-border e- commerce development.

· The establishment of free trade zones in shanghai, Tianjin and Nansha has attracted large enterprises to the cross-border e-commerce and has made the industry grow in a healthier and more standardized way. In the meantime, a large quantity of lower- priced imported products will be flooding in.

· The continuously increasing emphasis on cross-border e-commerce platforms by traditional enterprises as well as the seemingly unquenchable crave by Chineese consumers for well-known brandname foreign products that are fine in quality but cheaper in price will turn the cross-border e-commerce into a new driver in the trade development in the future.

B2C increases in market share and is developing in concert with B2B In 2014, B2B cross-border transactions accounted for an absolutely dominating 93.5% of the entire scale of cross-border e-commerce transactions in China. As the industry is seeing a trend of increasingly smaller cross-border e-commerce retailers and more diversified channels in which the products move from factories to consumers, cross- border orders become more fragmented and are in smaller amount. Combined with the advancement in logistics and internet technologies, the share of B2C transactions is

China Power of Retailing 2015 30 going to climb in the future. However, due to its larger transactional amounts and steady orders, B2B will remain as the most important mode in the exploitation of overseas market by Chinese enterprises in the foreseeable future. B2C, on the other hand, is closer to and directly interacts with consumers and is thus better able to understand the market demands. With mutual complementation outweighing competition, B2B and B2C are likely to be developed in concert.

Figure 2-17 Structure of B2B and B2C in the scale of cross-border e-commerce transactions in China 2010-2015

100% 2.20% 2.80% 4.10% 4.60% 6.50% 8.70% 90%

80%

70%

60%

50% 97.80% 97.20% 95.90% 94.40% 93.50% 91.30% 40%

30%

20%

10%

0% 2010 2011 2012 2013 2014 2015e

B2B% B2C%

Data source: CECRC

E-commerce giants intensify “cross-border” efforts In China, the number of cross-border e-commerce platforms has exceeded 5,000. Out of more than 200,000 cross-border e-commerce enterprises, 80% are from cities such as Guangzhou and Ningbo that have foreign trade traditions. E-commerce giants in cross- border led by Alibaba, JD and Amazon, and soon to be followed by yhd.com, dangdang.com and vip.com, have started implementing their cross-border e-commerce strategies in an effort to speed up deployment and seize more market shares. In the meantime, other cross-border e-commerce enterprises such as ymatou.com, metao.com, mia.com and mgpyh.com have intensified their efforts in building their respective brand names in vertical subsegments such as mother and baby, beauty and clothing markets.

Table 2-3 Cross-border e-commerce giants and their strategic moves

Cross-border e-commerce Cross-border e-commerce strategies giants

China Power of Retailing 2015 31 In May 2014, Alibaba announced its cooperation with ShopRunner, an e-commerce logistics company in US, to enable Chinese users to directly order overseas products through Alibaba’s platform. Alibaba makes cross-border e-commerce deployment through sudutong and TMall international and connect the data in alipay collected in the “Double 11” grand promotion with the customs information system to Alibaba further expand the overseas market through the assistance of big data. On May 5 of this year, Alibaba announced in Hangzhou that 1688.com, a procurement and wholesale website owned by Alibaba, will officially add the platform that supplies goods around the globe. As a key component of Alibaba Group’s strategy in cross- border importing, the platform serves as a medium that links the sellers from countries of origin with retailers in China.

At the end of 2012, JD.com launched the English version of its website to make it accessible to overseas buyers. On April 15, 2015, the global purchase business went live via JD’s website where 500-600 merchants gather to offer hundreds of thousands of categories of commodities. JD also announces that it will clear the JD.com channels for cross-border e-commerce customs clearance and bonded warehouse, work with the government to open five ports of entry to cross-border e-commerce by the end of the year, and add more SKUs to the product categories. Teams formed by experts from JD will be sent to overseas to carry out negotiations.

Amazon set up its office in Shanghai Free Trade Zone in August 2014 and has since built the cross-border e-commerce platform within the FTZ to enable Chinese consumers to buy directly from other countries via Amazon website. In early November 2014, Amazon (China) announced to open six major overseas spots that Amazon offer direct-delivery service to Chinese buyers who can directly purchase from more than 80 million commodities sourced from US, UK, France, Germany, Spain and Italy. Meanwhile, Amazon participated in the “Double 11” grand promotion through “buy overseas” + “direct delivery to China”.

Data source: Deloitte Analytics, Processed from publicly available information

Physical retailers test the water in cross-border e-commerce In their continuous search for ways to counteract e-commerce competitors and in the transformation into online businesses, physical retail enterprises target the cross-border e-commerce as a future direction. In the second half of 2014, Chongqing Department Store started its venture into cross-border e-commerce by launching the sjgo365.com platform. In April 2015, MOPARK opened its offline experience store, the first department store cross-border e-commerce O2O in Guangzhou. Now the mode will be expanded across all the stores across the company. In May, Guangzhou Department Store announced the launch of its cross-border e-commerce channel and concurrently opened 3 experience stores. On July 1st, ewj shop owned by CR Vanguard opened its shop in Qianhai Free Trade Zone that offer more than 500 commodities directly shipped from Hong Kong including toiletry, articles of everyday use, imported and fresh foods etc. On July 21, Tianhong (Rainbow) announced its launch of “Tianhong Daojia” (Tianhong delivered to your home) that moved its offline business to online the platform, as well as the “cross-border e-commerce experience stores” that brought its online business to

China Power of Retailing 2015 32 physical offline stores. This was the second O2O transformation in Tianhong’s execution of an all-channel strategy. Due to policy restrictions, cross-border e-commerce only started in the second half of 2014. That put online and offline enterprises at about the same start line and online enterprises have not shown an apparent advantage over the physical retailers.

Risks and barriers cross-border e-commerce enterprises have to face Cross-border e-commerce enterprises are in a start-up phase where cross-market, cross- country, cross-culture and cross-custom problems will pose risks and create barriers to the steady growth. Mainly the risks and barriers are of two types:

First, cross-border supply chain management. The two most problematic phases are management of overseas suppliers and execution of cross-border logistics. Due to the difficulty in the sourcing of high quality products, many import e-commerce platforms have weaker control over overseas suppliers. As a result, fakes or imitations have brought tremendous negative impact on the import e-commerce business. Meanwhile, cross- border logistics that relies on transshipment companies subjects the logistics chain to breaking, causing a slower speed of customs clearance and insufficient expected tariff management ability that discount consumer experience.

Second, supervisory policy direction needs a systematic clarification. Currently, each pilot zone applies relevant policies differently. In addition, policies regarding taxes on small- amount importing that directly affects consumer interests are not clear. Small-amount foreign trade is beset by problems such as evading tax, commodity inspection and non- tariff barriers, as well as insufficient after-sale service and credit crisis etc.

China Power of Retailing 2015 33 Figure 2-18 Market share of scale of transactions through B2C online shopping websites in China 2014

1.30% 0.70% 1.30% 1.40% 1.70% 7.60% 2.90% 3.20%

18.60% 61.40%

tmall.com jd.com suning.com vip.com gome.com yhd.com dangdang.com amazon.cn jumei.com other

Data source: iResearch, Deloitte Analytics

Mobile shopping goes mainstream and mobile e-commerce brings new hopes to retailers Data from CECRC show that as of December 2014, the scale of mobile online transactions in China reached RMB928. 5 billion, a yoy growth of 240% over 273.1 billion in 2013, and is continuing the trend of fast growth. According to the latest statistics from iResearch, in the first quarter of 2015, China’s mobile shopping market grew to a size of RMB362.34 billion, representing a yoy growth of 168.3%, and is still growing rapidly. In the overall online shopping market, transactions conducted through mobile platforms account for 47.8% and are moving up quickly. Since 2015, all the major e-commerce platforms and many traditional brandname enterprises have expedited their deployment on, added more business capacity to and improved the services for mobile platforms, pushing the number of mobile users and amount of transactions via mobile platforms to grow exponentially. With the mobile payment technology further improving and penetrating, it is expected that mobile shopping transaction amounts will seize more than half of the overall online shopping market share in China in 2015.

The Report on Data of the E-commerce in County Regions (first issue) (“Report”) published by AliResearch shows that on the Alibaba retail platform, the amount of mobile shopping in county regions in 2014 broke RMB200 billion, representing a yoy growth of more than 250% and outgrowing online shopping of the same period by a large margin. In the villages and towns where physical retailers have a weak presence, mobile shopping shows signs of a strong growth momentum and is hopeful to become a new blue sea for retail enterprises aimed at expanding their markets.

China Power of Retailing 2015 34 Figure 2-19 2011-2016 Scale of mobile online transactions in China

30000 600%

25000 496% 500%

20000 400%

15000 295% 300% 240% 10000 200%

5000 84.30% 100% 42.10% 0 0% 2011 2012 2013 2014 2015e 2016e

Scale of transactions (RMB 100 million) Growth %

Data source: CECRC

Figure 2-20 China online transactions contributed by PC platform and mobile platform

100% 90% 25.90% 30.40% 80% 34.00% 40.00% 47.80% 70% 60% 50% 40% 74.10% 69.60% 30% 66.00% 60.00% 52.20% 20% 10% 0% 2014Q1 2014Q2 2014Q3 2014Q4 2015Q1

Amount of online transactions conducted via mobile platforms (%) Amount of online transactions conducted via PC platforms (%)

Data source: iResearch

Businesses speed up efforts in seizing the mobile market share In the first quarter of 2015, Ali Wireless continued to hold a dominating position in the enterprise mobile platform market, accounting for 84.5% of mobile shopping market share. JD.com and VIP.com both saw a moderate rise, accounting for 5.2% and 2.8% respectively in the mobile platform market share. Other enterprises not viewed as core players in the mobile platform market also recorded growth to a certain degree, rising from 4.2% in the fourth quarter of 2014 to 4.6% in the first quarter of 2015. Meanwhile, all enterprises have sped up their efforts in seizing more mobile market shares through holiday promotions, opening up mobile overseas purchasing and WeChat stores, further fueling the fierce competition in the mobile shopping market.

China Power of Retailing 2015 35 Table 2.5

Taobao Launched “3.8 Life Festival” on its mobile platform to enhance the convenience of online shopping experience, also introduced “Taoxiaopu” tool to lower the threshold for sellers to open stores on mobile platforms.

Distributed virtual “Hongbao” (red-paper bags with money inside) for a total amount of RMB100 million through WeChat and mobile QQ in the JD.com Spring Festival to promote brand awareness and drive mobile platform users’ loyalty.

Brought group purchasing onto the mobile platform and added APPs for VIP.com subsegments to emphasize the sub-categories on the mobile platform.

Intensified efforts in overseas purchasing business, “Jisumianshuidian” Jumei.com (top speed duty free shop) leads its growth on the mobile platform.

Traditional enterprises such as Suning.com, Gome.com, dangdang.com, yhd.com, and Amazon have gone all out on the mobile platform in an Traditional enterprises attempt to grab more mobile market shares through mobile WeChat stores, mobile overseas purchasing and holiday promotions via mobile platforms.

One example is Meilishuo.com that has brought its independent mobile Other mobile shopping overseas purchasing APP to live and connected with WeChat wallet to enterprises get more online traffic.

Data source: Deloitte Analytics, processed from publicly available information, iResearch

Figure 2-21 Market share by mobile shopping enterprises in China in terms of scale of transaction

100% 4.70% 4.20% 5.20% 4.20% 4.60% 4.60% 4.80% 5.30% 90% 5.70% 5.70% 3.30% 4.50% 4.60% 4.50% 5.20% 80% 70% 60% 50% 87.40% 86.50% 86.00% 40% 84.50% 84.50% 30% 20%

10% 0% 2014Q1 2014Q2 2014Q3 2014Q4 2015Q1e Ali Wireless Mobile JD Mobile VIP etc. Others

Notes: Mobile VIP etc. include: Mobile VIP, Mobile Suning, Mobile Gome, Mobile yhd, Mobile jumei, mobile dangdang, mobile Amazon and mmb. Data source: iResearch

China Power of Retailing 2015 36 III Hypermarkets and supermarkets

3.1 Statistics collected from sample supermarkets and hypermarkets 03 enterprises that mainly operate supermarkets and hypermarkets have responded to the questionnaire. Among them, 29, or 28%, have a revenue of over RMB10 billion; 14% report a revenue between RMB5-10 billion; and the enterprises that have a revenue below RMB5 billion account for 58%.

Figure 3-1 Distribution of sample supermarkets and hypermarkets by revenue

above above RMB10 RMB10 billion billion 20% 28%

RMB5-10 billion RMB5-10 14% billion 38%

Average scale of enterprises The average revenue from the 103 sampled supermarket enterprises in 2014 was RMB11.36 billion with annual growth rate remaining at 2.6%, lowering than the average growth rate of 4.5% across all the sampled enterprises. The growth rate in the number of stores was 1.4% while the growth rate in business area was 8.6%, indicating that the average area per store increased. In the meantime, the number of employees fell by 0.5%, indicating that enterprises chose to cut operating costs by cutting the number of employees to cope with the rapidly rising labor cost. Below store analysis shows that the average efficiency per square meter and efficiency per head in the stores of the sample supermarkets and hypermarkets increased from a year before.

China Power of Retailing 2015 37 Figure 3-2 Average scale of sample supermarket and hypermarket enterprises

120.0 10.0% 110.7 113.6 8.6% 100.0 8.0%

79.7 80.0 73.4 6.0%

60.0 4.0%

2.6% 40.0 2.0% 1.4%

20.0 0.0% 10.2 10-0.25% 4.3 4.4 - -2.0% revenue (RMB100 number of stores (100)business area (10,000 number of employees million) square meters) (1,000)

2013 2014 growth %

Expenses The labor cost remained as the largest expense in supermarkets and hypermarkets, accounting for 54.4%, followed by rents and utilities, accounting for 31.1% and 14.5% respectively. Among them, labor cost fell by 0.1 percentage points, rents increased by 0.7 percentage points while utilities dropped 0.6 percentage points, reflecting how hard enterprises tried to cut expenses in a costly environment.

Figure 3-3 Expense structure in sample supermarket and hypermarket enterprises

100% 15.1% 14.5% 80%

60% 54.5% 54.4%

40%

20% 30.4% 31.1%

0% 2013 2014

rents labor utilities

Note: Among the sample enterprises in 2014, 60.2% own stores. Among these enterprises, averagely, the number of owned stores accounted for 20.4% of total stores.

China Power of Retailing 2015 38 Figure 3-4 Expenses of sample supermarket and hypermarket enterprises

30000 12.0% 11.2% 27118.82342 25407.91861 25000 10.0% 9.2%

20000 8.0% 7.4% 15468.3461 14160.42494 15000 6.7% 6.0%

10000 4.0% 7013.1584517219.881338 2.9% 5000 2.0%

0.4% 0 0.0% rents(RMB10,000) labor cost (RMB10,000) utilities (RMB10,000)

2013 2014 growth % in 2013 growth % in 2014

Internet retail business 37% of the sample supermarket and hypermarket enterprises engage in internet retail business. The average annual internet sales revenue was RMB37.57 million, accounting for 0.9% of total revenue. Although it was higher than the 0.2% from a year before, its contribution to total enterprise revenue was low.

Proprietary brand 6.4%。42% of sample supermarket and hypermarket enterprises owned proprietary brands, which generated a revenue equaling to 6.4% of total revenue.

3.2 Operating conditions in the sample stores of hypermarkets We classify the sample stores by the size of business area in accordance with the national standard of retail type classification: hypermarkets that have more than 6,000 square meters of business area, and normal supermarkets (supermarkets) that have less than 6,000 square meters in business area. This section is specifically dedicated to the operating conditions of the sampled stores in hypermarkets and the following section will cover the operating conditions of sampled stores in supermarkets.

Among the hypermarkets responding to the questionnaire, 25 sampled stores have complete data and have operated more than one year, each of them has a better operating performance and represents best level in the industry. Out of the 25 stores, 14 are located in tier I and tier II cities, and 11 are located in tire III and tire IV cities. The average business area is 11,000 square meters with the lowest at 6,000 square meters and highest at 23,000 square meters. The average revenue is RMB260 million with the lowest being RMB80 million and highest being RMB690 million.

China Power of Retailing 2015 39 Average scale of stores In 2014, the average revenue in all the sampled stores saw a slight growth (increasing by RMB8.36 million per store), and the total number of single product available for sale increased by 1,078 from a year before. The slight growth in revenue was achieved in a slightly increased business area and a slightly decreased number of employees, reflecting how the enterprises enhanced the operating efficiency under the pressure of continuously rising rents and labor costs in recent years.

Figure 3-5 Average scale of sample stores in hypermarkets

3.5 3.3 4.0% 3.2 3.5% 3.0 3.3% 3.4% 3.0% 2.5 2.6 2.5 2.5% 2.2 2.2 2.0% 1.9% 2.0 1.5% 2013 1.0% 1.5 2014 1.1 1.1 0.5% growth% 1.0 0.0% -0.5% 0.5 -0.9% -1.0% - -1.5% revenue (RMB100 number of single business area number of million) product available for (10,000 square employees (100) sale (10,000) meters)

Store operating efficiency In line with the above conclusion, both the efficiency per square meter and efficiency per head in sampled stores of hypermarkets in 2014 increased to a certain degree. Efficiency per head, in particular, increased by 3.5% from a year before. As the growth in total revenue was close to the growth in the number of single product available for sale, the revenue per single product did not change.

Table 3-1 Efficiency per square meter, efficiency per head, and revenue per single product in the sampled stores in hypermarkets

Efficiency per square Efficiency per head meter Sales per single product Project (RMB (RMB10,000/square (RMB10,000) million/person/year) meter/year) 2014 2.4 1.2 0.9

2013 2.3 1.2 0.9 Growth in 2014 1.4% 3.5% 0%

China Power of Retailing 2015 40 Average daily revenue per transaction per store In 2014, the average daily revenue per transaction per store was RMB84.9, growing 6.4% from RMB79.8 in 2013. Although much higher than 0.9% in 2013, the growth is relatively smaller than the growth % in both 2011 and 2012, both growing by 13.0%. Sales through other channels such as online and specialty stores might have explained a slow growth in daily average revenue per transaction in 2013. It then recovered in 2014 as traditional retailers began to get used to such a new setting.

Figure 3-6 Growth % in average daily revenue per transaction

16.0%

14.0% 13.5% 13.6% 12.0%

10.0% 9.0% 8.0%

6.0%

4.0%

2.0% 0.9% 0.0% 2010-2011Growth % 2011-2012Growth % 2012-2013Growth % 2013-2014Growth %

Expenses In 2014, the three kinds of expenses combined (rents, labor and utilities) accounted for 7.8% of sales revenue, a rise of 2.6% from a year before. The major reasons contributing to the rise were the increase in rents and labor costs, especially the latter that increased by 7.2% from a year before. Labor cost remains to be the biggest chunk in hypermarkets’ total expenses, followed by rents and utilities.

Table 3-2 Three expenses in the sample hypermarket stores

Ratio of three Rents Employee salary Utilities Project expenses over (RMB10,000) (RMB10,000) (RMB10,000) revenue

2014 7.8% 598.8 1,101.7 315.9

2013 7.6% 575.0 1,028.2 310.2

Growth% in 2014 2.6% 4.1% 7.2% 1.8%

China Power of Retailing 2015 41 Figure 3-7 Structure of three expenses in sample hypermarket stores

100% Annual growth rate of 16.2% 15.6% three expenses 80% 2012-2013 2013-2014

60% -2.2% 1.8% 53.8% 54.7%

40% 6.4% 7.2%

20% 30.1% 29.7% 1.1% 4.1%

0% 2013 2014

Rents Salary 水电费

Store gross margin % The average gross margin % in hypermarkets was 16.4%, higher than 2013’s 15.6%, and showed a wide gap between the lowest (8.3%) and the highest (24.6%). In comparison, the average gross margin % was 16.2% among stores of all sampled types of operation, slightly lower than that of hypermarkets.

Figure 3-8 Distribution of gross margin % in sample hypermarket stores

30.0 25.0 20.0 15.0 10.0 5.0 0.0 S t o r e s1 S t o r e s2 S t o r e s3 S t o r e s4 S t o r e s5 S t o r e s6 S t o r e s7 S t o r e s8 S t o r e s9 S t o r e s 10 S t o r e s 11 S t o r e s 12 S t o r e s 13 S t o r e s 14 S t o r e s 15 S t o r e s 16 S t o r e s 17 S t o r e s 18 S t o r e s 19 S t o r e s 20 S t o r e s 21 S t o r e s 22 S t o r e s 23 S t o r e s 24 S t o r e s 25

Gross margin % Average gross margin %

Note: As the reported stores are among the best in each sampled enterprise, they have a better operating condition and an average gross margin % higher than the level of normal hypermarkets.

Logistics, distribution and inventory turns The average ratio of centralized distribution in the sample stores was 64%, slightly higher than the 63% in 2013 by 1%. The average inventory turns were 36 days, one day shorter than in 2013 on average.

China Power of Retailing 2015 42 Comparison of hypermarkets of different business areas As hypermarkets differ dramatically in terms of store business areas, we further classify these stores into three categories by business area to increase compatibility, namely 6,000-9,999 square meters, 10,000-14,999 square meters and above 15,000 square meters.

Average scale of sample stores by the three categories Table 3-3 shows that revenue from all the stores of different sizes in hypermarkets increased, among which the highest growth of 4.9% came from small-sized stores (6,000- 9,999). Both the large-sized and medium-sized stores showed a slight increase in the number of employees while the small-sized stores decreased in the number of employees by 4.1%.

Table 3-3 Average scale of sample hypermarket stores by three categories

Number of Categories by Average number Average single business area Revenue of full-time Year business area products (square (RMB10,000) employees (square meter) available for meters ) (person) sale (unit)

2014 47,679 17,455 300 31,527 ≥15000 2013 45,934 16,821 299 31,585 2014 Growth % 3.8% 3.8% 0.4% -0.2% 2014 26,597 12,090 205 30,102 10000-14999 2013 26,221 12,190 201 28,738 2014 Growth % 1.4% -0.8% 1.8% 4.7% 2014 24,330 7,214 201 20,070 6000-9999 2013 23,197 7,048 210 19,270 2014 Growth % 4.9% 2.4% -4.1% 4.2%

Operating efficiency in the sample stores in three categories Table 3.4 suggests that among the three categories of stores, efficiency per head in small-sized (6,000-9,999) stores increased by 9.4%, higher than the other two categories by a large margin. Efficiency per head reflects people’s quality and professional and technical capabilities, and is closely related to the operating and labor costs in the stores.

In 2014, a relatively higher efficiency per square meter was reported in large-sized and small-sized stores, at RMB27,000 and RMB34,000 per square meter per year respectively. The medium-sized stores, in comparison, had a lower efficiency of RMB22,000 per square meter per year. In general, efficiency per square meter was improved on average across all the three categories.

China Power of Retailing 2015 43 Only the medium-sized stores out of the three categories of stores showed a slip in the revenue per single product, a 3.2% lower than a year before. In 2014, by comparison, large-sized stores had the highest revenue per single product, followed by medium-sized stores, and the small-sized stores stood at the last.

Table 3-4 Efficiency per square meter, per head and revenue per single product available for sale in three categories of sample hypermarket stores

Efficiency per Efficiency per Revenue per single Categories by square meter head (RMB1 Year product business area (RMB10,000/square million/person/ (RMB10,000) meter/year) year)

2014 2.7 1.6 1.5 ≥15000 2013 2.7 1.5 1.5 2014 Growth % 1.1% 6.4% 4.9% 2014 2.2 1.3 1.0 10000-14999 2013 2.2 1.3 1.0 2014 Growth % 2.3% -0.3% -3.2% 2014 3.4 1.2 0.7 6000-9999 2013 3.3 1.1 0.6 2014 Growth % 2.5% 9.4% 1.8%

2014 Comparison of operating efficiency in three categories of sample stores

4.0 3.4 3.5

3.0 2.7

2.5 2.2 2.0 1.6 1.5 1.5 1.3 1.2 1.0 1.0 0.7 0.5

- Efficiency per square meter Efficiency per head (RMB1 Revenue per single product (RMB10,000/square meter/year) million/person/year) (RMB10,000)

≥15000 10000-14999 6000-9999

Average daily revenue per transaction in three categories of sampled stores As the figure indicates, in 2014, all the three categories of sample stores recorded an increase in average daily revenue per transaction to different degrees, among which,

China Power of Retailing 2015 44 large-sized stores（≥15,000 square meters）had the smallest increase of 5.7%, medium- sized stores (10,000 – 14,999 square meters) and small-sized stores (6,000-9,9999) had higher increases of 7.8% and 6.4% respectively, possibly due to the fact that the latter two had a faster growth in the number of single products offered for sale.

Figure 3-10 Average daily revenue per transaction by three categories of sample hypermarket stores

120.0 9.0% 103.4 97.9 8.0% 100.0 7.8% 82.6 85.2 7.0% 76.6 80.0 80.0 6.4% 6.0% 5.7% 5.0% 60.0 4.0% 40.0 3.0% 2.0% 20.0 1.0% 0.0 0.0% ≥15000 10000-14999 6000-9999

2013 2014 Growth %

Gross margin % in three categories of sampled stores In 2014, three categories of sampled stores reported a gross margin % of 15.4%, 17.1% and 16.0% respectively. Gross margin % in the medium-sized stores (10,000 – 14,999 square meters), although highest among the three categories, fell from a year before in terms of the growth rate. In comparison, large-sized stores （≥15000 平米）had the lowest gross margin % while small-sized stores (6,000 -9,999) had the highest growth rate.

Figure 3-11 Gross margin % in three categories of sample hypermarket stores

20.0% 4.0% 3.8% 17.2% 17.1% 15.4% 15.4% 16.0% 16.0% 15.1% 3.0%

12.0% 1.9% 2.0%

8.0% 1.0%

4.0% 0.0% -0.5% 0.0% -1.0% ≥15000 10000-14999 6000-9999

2013 2014 Growth %

China Power of Retailing 2015 45 3.3 Operating conditions in the sample supermarket stores This section focuses on the analysis of the operating conditions of “normal supermarkets” with a business area below 6,000 square meters. Out of the 16 supermarkets sampled in the questionnaire, 7 are located in tire I and tire II cities, and 9 are located in tire III and tier IV cities. The average business area of these supermarkets is 2,000 square meters, the smallest being 500 square meters and the largest being 5,600 square meters. The average revenue is RMB60 million, the lowest being RMB10 million and the highest being RMB220 million.

Average scale of supermarket stores In 2014, the revenue in sample supermarkets fell by 1.6% and that in sampled hypermarkets grew by 3.3%. Like the hypermarkets, the business area of supermarkets increased slightly by 1.5% and the number of full-time employees dropped by 3 people per store on average. The fact that the revenue fell at a slower speed than the number of employees indicates that the operating efficiency improved from a year before. The number of single products available for sale increased by 1,222, close to that in hypermarkets.

Figure 3-12 Average scale of sample supermarket stores

1.4 1.3 12.0%

1.2 10.1% 10.0% 1.2 8.0% 1.0 6.0%

0.8 4.0% 0.6 0.6 0.6 0.6 2.0% 0.6 1.5% 0.0% 0.4 -1.6% 0.2 0.2 -2.0% 0.2 -4.2% -4.0%

0.0 -6.0% Revenue (RMB100 Number of single Business area (10,000 Number of full-time million) products available for square meters) employees (100) sale (10,000)

2013 2014 Growth %

China Power of Retailing 2015 46 Store operating efficiency Due to a falling revenue from a year before, the efficiency per square meter fell 3.0% in 2014. The efficiency per head, on the other hand, continued to improve and recorded a growth of 2.7% from a year before, demonstrating the continued improvement on labor efficiency in supermarkets. The revenue per single product dropped by 10.6% mainly due to the falling revenue and rising number of single products offered in the supermarkets.

Table 3-5 Efficiency per square meter, efficiency per head and revenue per single product available for sale in sample supermarket stores

Efficiency per square Efficiency per head meter Revenue per single Projects (RMB1 (RMB10,000/square product (RMB10,000) million/person/year) meter/year)

2014 2.66 1.04 0.47

2013 2.74 1.01 0.52

2014 Growth % -3.0% 2.7% -10.6%

Average daily revenue per transaction per store In 2014, the average daily revenue per transaction per store was RMB48.1 and fell by 4.2% from 2013. The sharp reverse from the continuously ring trend in previous years reflected the fierce competition in supermarkets that halted the growth in revenue.

Store expenses The expenses in rents, employee salaries and utilities in sampled supermarket stores all increased from a year before, resulting in a 0.3 percentage points increase in the ratio of the total three expenses over the total revenue (the growth % was 4.4% in 2014). Employee salaries, increasing by 3.9%, posted the highest growth. Given the fact that the total number of employees fell by 4.2% averagely, the increase in labor costs was mainly a result of the rising salaries. As the labor costs climbed markedly and increased its share in the three expenses by 0.6 percentage points, the ratios of rents or utilities over the total expenses fell slightly.

Table 3-6 Three expenses in sample supermarket stores

Ratio of three Rents Employee salary Utilities Project expenses over (RMB10,000) (RMB10,000) (RMB10,000) revenue

2014 6.8% 139.4 229.6 52.0

2013 6.5% 137.4 221.0 51.4

Growth% in 2014 4.4% 1.5% 3.9% 1.2%

China Power of Retailing 2015 47 Figure 3-13 Structure of three expenses in sample supermarket stores

100% 12.5% 12.3% Annual growth rate of three expenses 80% 2012-2013 2013-2014 60% 54.0% 54.6% 5.5% 1.2% 40%

20% 33.5% 33.1% 7.3% 3.9% 0% 2013 2014

Rents Total salary Utilities 3.5% 1.5%

Store gross margin % The average gross margin % in the sampled supermarket stores was 12.7%, markedly lower than the 14.6% in 2013. The gross margin % differentiated significantly from the lowest at 7.1% to the highest at 17.4%. If calculated by the average revenue of the sample supermarket stores, the difference between the store with the highest gross margin % and that with the lowest % was RMB6.72 million. The average gross margin % in all the stores across all types of operation in the industry was 16.2%, higher than that of the sampled supermarkets.

Figure 3-14 Distribution of gross margin % in sample supermarket stores

20.0 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0

Gross margin % Average gross margin %

Logistics, distribution and inventory turns The average ratio of centralized distribution in the sample stores was 69%, slightly lower than 2013. The average inventory turns were 34 days, three days longer than in 2013.

China Power of Retailing 2015 48 Comparison of supermarkets of different business areas We further classify these sampled stores into three categories by business area to increase compatibility, namely 500-999 square meters, 1,000-2,999 square meters and above 3,000 square meters.

Average scale of stores by the three categories Generally, supermarkets across all the three categories experienced slight revenue slowdowns that hinted difficult situations supermarkets of all scales faced such as the defueling growth and fiercer competition. Only the large-sized stores （≥3000 square meters）saw an expansion in the business area while the other two categories remained unchanged. The number of employees in both the large-sized and medium-sized stores fell sharply. In large-sized stores especially, the average number of employee fell by 5.4%.

Table 3-7 Average scale of sample supermarket stores by three categories

Average Number of Categories by Average number of full- single business area Revenue Year business area time products (square (RMB10,000) (square meter) employees available for meters ) (person) sale (unit)

2014 9,882 4,322 74 18,464

≥3000 2013 10,062 4,212 78 18,662

2014Growth % -1.8% 2.6% -5.4% -1.1%

2014 5,342 1,678 62 11,957

1000-2999 2013 5,413 1,678 65 9,801

2014Growth % -1.3% 0.0% -3.6% 22.0%

2014 941 325 14 6,213

500-999 2013 959 325 14 5,650

2014Growth % -1.9% 0.0% 0.0% 10.0%

Operating efficiency in the three categories of sample stores In line with the above data in revenue, business area and number of employees, all the sample stores across all the three categories showed a drop in the average efficiency per square meter and both large-sized stores （≥3,000 square meters）and medium-sized stores （1,000-2,999 square meters）reported an increase in the efficiency per head.

China Power of Retailing 2015 49 Table 3-8 Efficiency per square meter, per head and revenue per single product available for sale in sample supermarket stores in three categories

Efficiency per Efficiency per Categories by Revenue per single square meter head (RMB1 business area Year product (RMB10,000/square million/person/ (RMB10,000) （square meter） meter/year) year) 2014 2.3 1.3 0.5 ≥3000 2013 2.4 1.3 0.5 2014 Growth % -4.3% 3.8% -0.7% 2014 3.2 0.9 0.4 1000-2999 2013 3.2 0.8 0.6 2014 Growth % -1.3% 2.4% -19.1% 2014 2.9 0.7 0.2 500-999 2013 2.9 0.7 0.2 2014 Growth % -1.9% -1.9% -10.8%

Comparison of operating efficiency in sample supermarket stores in three categories

3.5 3.2 3.0 2.9

2.5 2.3

2.0

1.5 1.3

1.0 0.9 0.7 0.5 0.4 0.5 0.2 - Efficiency per square meter Efficiency per head (RMB1 Revenue per single product (RMB10,000/square meter/year) million/person/year) (RMB10,000)

≥3000 1000-2999 500-999

Average daily revenue per transaction in the sample supermarket stores in three categories The figure shows that among the three categories, the large-sized stores (≥3, 000 square meters) had the highest average daily revenue per transaction followed by stores with a business area between 1,000 – 2,999 square meters. The small-sized supermarkets lagged behind.

China Power of Retailing 2015 50 Figure 3-16 Average daily revenue per transaction in the sample supermarket stores in three categories

56.4 56.4 60.0 54.6 1.0% 0.0% 51.3 0.0% 50.0 -1.0% 40.0 36.9 35.6 -2.0%

30.0 -3.0% -3.4% -4.0% 20.0 -5.0% 10.0 -6.0% -6.0%

- -7.0% ≥3000 1000-2999 500-999

2013 2014 growth %

Gross margin % in the three categories of sample supermarket stores The gross margin % of the sampled supermarkets in the three categories was 12.7%, 12.7% and 13.2% respectively. Supermarkets that had a business area between 500 and 999 square meters were leaders in the chart. In terms of the growth of gross margin %, except for the stores with a business area above 3,000 square meters, the stores in the other two categories both showed a slight dip in the gross margin %.

Figure 3-17 Gross margin % of the sample supermarket stores in three categories

13.8% 1.5% 13.6% 13.6% 1.0% 1.0%

13.4% 0.5% 13.2% 13.2% 0.0% 13.0% 13.0% -0.5%

12.8% 12.7% 12.7% -1.0% 12.5% 12.6% -1.5%

12.4% -2.0%

12.2% -2.6% -2.5% 12.0% -2.9% -3.0%

11.8% -3.5% ≥3000 1000-2999 500-999

2013 2014 growth %

China Power of Retailing 2015 51 IV Convenience stores

4.1 Operating conditions in sample enterprises Below analyses are based on the data collected from 41 enterprises operating convenience stores solely or as their primary business. 90% of these enterprises are of the size of below RMB10 billion. Among them, 22, or 54%, are below RMB1 billion, and 15, or 36%, are between RMB1-10 billion. In terms of revenue, 2 enterprises report a revenue of RMB10-30 billion and another 2 reported a revenue of more than RMB30 billion.

Figure 4-1 Revenue of sampled convenience store enterprises

above RMB30 billion 5% RMB10-30 billion 5%

below RMB1 RMB1-10 billion billion 54% 36%

Average scale of enterprises Figure 4-2 shows that in 2014, the number of stores and business area of the sampled convenience store enterprises grew by 6.0% and 2.9% respectively. Their revenue grew by 5.3% mainly attributable to the addition of new stores and improvement of operating efficiency.

China Power of Retailing 2015 52 Figure 4-2 Average scale of sample convenience store enterprises

100.0 7.0% 6.0% 6.0% 5.3% 80.0 72.2 70.6 5.0% 4.0% 2.9% 60.0 3.0% 44.8 47.2 41.7 42.9 2.0% 40.0 1.0% 0.0% 20.0 14.9 15.8 -1.0% -2.2% -2.0% 0.0 -3.0% Revenue (RMB100 Number of stores (100)Business area (10,000 Number of employees million) square meters) (100)

2013年 2014年 2014 growth %

Expenses As the sample convenience stores were still in an orbit of rapid growth and the number of stores and business area were expanding, consequently, the rent and utility expenses remained in a state of rapid rise in 2014. Despite the drop in the number of employees from a year before, the rise in labor costs sent the people expenses up at a fast speed in 2014. Rents grew the fastest at 15.9%, much higher than the growth in revenue, followed by employee salaries that posted a yoy growth of 7.6%. The yoy growth in utilities was 6.7%, similar to that in revenue, indicating that convenience stores were pressured by a rising labor and utility cost. In terms of the expense structure, the ratio of rents over the total three expenses increased 1.6 percentage points while the ratio of employee salaries and utilities over the total three expenses dropped slightly.

Figure 4-3 Enterprise expenses in sample convenience store enterprises

45,000.0 18.0% 39809.0 40,000.0 15.9% 37003.9 16.0% 35,000.0 14.0%

30,000.0 12.0%

25,000.0 10.0% 19435.1 20,000.0 16763.6 7.6% 8.0% 6.7% 15,000.0 6.0%

10,000.0 6651.0 7097.2 4.0% 5,000.0 2.0%

0.0 0.0% Rents (RMB10,000) Employee salaries Utilities (RMB10,000) (RMB10,000) 2013年 2014年 2014 growth %

China Power of Retailing 2015 53 Figure 4-4 Expense structure in sample convenience store enterprises

120.0%

100.0% 11.0% 10.7% 80.0%

60.0% 61.2% 60.0%

40.0%

20.0% 27.7% 29.3% 0.0% 2013年 2014年 Rents Labor Utilities

Note: 83% of the sample convenience store enterprises own stores. In 2014, the number of self-owned stores increased by 3.7%.

Internet retail business Among the sample convenience store enterprises, 62% have internet retail business that contributed a yearly revenue of RMB23.95 million averagely, accounting for 0.51% of total revenue.

Proprietary brands Among the sample convenience store enterprises, the revenue from selling proprietary brands accounted for 13% of total revenue, higher than that in supermarkets and department stores.

4.2 Operating conditions in sample convenience stores Among the sampled convenience stores responding to the questionnaire, 16 have complete data and have operated for more than one year. Out of the 16 stores, 13 are located in tire I and tire II cities, and 3 are located in tire III and tier IV cities. The average business area of these stores is 138 square meters, the smallest being 50 square meters and the largest being 400 square meters. The average revenue is RMB4.79 million, the lowest being RMB830,000 and the highest being RMB16.32million. As the reported stores are those with good sales records, they have a higher revenue and better operating performance. The average daily revenue of these sample stores, for example, is RMB13,000.

Average scale of stores In 2014, revenue from these sample stores grew on a yoy basis by 3.8%, changing little from a year before. The number of employees fell by 5.2% from a year before, causing people efficiency to climb tremendously. The number of single products available for sale in each store increased by 182 in average.

China Power of Retailing 2015 54 Figure 4-5 Average scale of sample convenience stores

8.0 8.0% 7.2% 7.1 6.7 6.0% 3.8% 6.0 4.0% 4.6 4.8 2.0% 4.0 0.7% 0.0% 2.5 2.7 -2.0% 2.0 1.4 1.4 -4.0% -5.2% 0.0 -6.0% Revenue (RMB million) Number of single Business area (100 Number of employees products available for square meters) (person) sale (1,000)

2013年 2014年 2014 Growth %

Store operating efficiency The efficiency per square meter increased by 3.1% and the efficiency per head increased by 9.6%, both greater than a year before. The revenue per single product dropped on yoy basis by 3.2 percentage points mainly due to the fact that the growth in the number of single products offered was faster than the growth in revenue.

Figure 4-1 Efficiency per square meter, per head and revenue per single products available for sale in sample convenience stores

Efficiency per square Efficiency per head meter Revenue per single Project (RMB1 (RMB10,000/square product (RMB10,000) million/person/year) meter/year)

2014 3.5 0.7 0.2 2013 3.4 0.7 0.2 2014 Growth % 3.1% 9.6% -3.2% Note: Figures are calculated based on the average efficiency per square meter, efficiency per head and revenue per single product in each sample store, but not estimated by average revenue of all the stores.

Average daily revenue per transaction per store In 2014, the average daily revenue per transaction per store was RMB19.1, increasing by 10.1% than 2013 (RMB17.4)

Store expenses Rents and labor expenses grew largely by 6.0% and 5.2% respectively while utilities fell slightly from a year before by 0.4%. Employee salary took the biggest chunk in store expenses, accounting for 46.9% of the total three expenses, followed by rents and utilities that accounted for 42.5% and 10.6% respectively.

China Power of Retailing 2015 55 Table 4-2 Three expenses in sample convenience stores

Ratio of three Rents Employee salary Utilities Project expenses over (RMB10,000) (RMB10,000) (RMB10,000) revenue

2014 11.9% 24.3 26.8 6.1

2013 11.8% 22.9 25.5 6.0

2014 Growth% 1.0% 6.0% 5.2% -0.4%

Figure 4-6 Structure of three expenses in sample convenience stores

100% Annual growth rate of 11.2% 10.6% three expenses 80% 2012-2013 2013-2014 46.7% 46.9% 60% -1.6% -0.4%

40% 13.2% 5.2% 20% 42.1% 42.5%

0% 11.6% 6.0% 2013 2014 Rents Total salary Utilities

Store gross margin % The average gross margin % in the sampled convenience stores was 23.3%, slightly higher than the 21.1% in 2013. The gross margin % differentiated significantly among stores with the lowest being 13.5% and highest being 33.7%. If calculated by the average revenue of the sampled convenience stores, the difference between the store with the highest gross margin % and that with the lowest % was RMB900,000. The average gross margin % in all the stores across all types of operation in the industry was 16.2%, lower than that of the sampled convenience stores.

Figure 4-7 Distribution of gross margin % in sample convenience stores

40.0 30.0 20.0 10.0 0.0

Gross margin % 毛利率均值

China Power of Retailing 2015 56 Logistics, distribution and inventory turns The average ratio of centralized distribution in the sample stores was 85%, rising by 5% than 2013. The average inventory turns were 29 days, two days longer than in 2013 on average.

Comparison of convenience stores of different business areas We further classify these sampled convenience stores into three categories by business area to increase compatibility, namely 50-99 square meters, 100-199 square meters and above 200 square meters.

Average scale of sample convenience stores in the three categories Below table shows that although in general the revenue of the sample convenience stores grew by 3.8%, most of the growth came from large-sized stores (≥200 square meters). Both the medium-sized （100-199 square meters）and small-sized stores（50- 99 square meters）showed little change in revenue.

Table 4-3 Average scale of sampled convenience stores in three categories

Average Number of Categories Average number of full- single by business Revenue business area Year time products area (square (RMB10,000) (square employees available for meters ) meter) (person) sale (unit)

2014 749 480 9 6,567 ≥200 2013 653 480 10 5,948

2014 Growth % 14.6% 0.0% -10.0% 10.4%

2014 498 147 6.5 2,800 100-199 2013 471 147 6.9 2,625

2014 Growth % 5.8% 0.0% -5.3% 6.6%

2014 358 67 6.0 1,439 50-99 2013 352 64 6.1 1,357

2014 Growth % 1.8% 3.3% -2.3% 6.0%

Operating efficiency of the sample stores in three categories Large-sized （≥200square meters）and medium-sized (100-199) stores showed signs of improvement to a different degree in efficiency per square meter and efficiency per head. In comparison, small-sized stores（50-99 square meters）fell slightly in efficiency per square meter. Overall, small-sized stores had higher efficiency per square meter and revenue per single product while large-sized stores had higher efficiency per head.

China Power of Retailing 2015 57 Table 4-4 Efficiency per square meter, per head and revenue per single product in sampled convenience stores in the three categories

Efficiency per Efficiency per Categories by Revenue per square meter head (RMB1 business area Year single product (RMB10,000/squa million/person/ye square meter (RMB10,000) （ ） re meter/year) ar) 2014 2.1 90.5 0.1 ≥200 2013 2.1 77.1 0.2 2014Growth % 1.8% 17.4% -7.5% 2014 3.4 76.3 0.2 100-199 2013 3.2 68.3 0.2 2014Growth % 5.8% 11.7% -0.8% 2014 5.4 59.6 0.2 50-99 2013 5.5 57.2 0.3 2014Growth % -1.5% 4.2% -4.0%

Figure 4-8 Comparison of operating efficiency in sample convenience stores in three categories

6.0 5.4

5.0

4.0 3.4

3.0 2.1 2.0 0.9 1.0 0.8 0.6 0.1 0.2 0.2 0.0 Efficiency per square meter Efficiency per head (RMB1 Revenue per single product (RMB10,000/square meter/year) million/person/year) (RMB10,000)

≥200 100-199 50-99

Average daily revenue per transaction per sample store in three categories The average daily revenue per transaction in all the sampled convenience stores across the three categories showed some improvement. Medium-sized stores （100-199） in particular reported an increase in average daily revenue per transaction from RMB16.4 to 18.2, growing by 10.5%. Small-sized （50-99 square meters）stores also showed a remarkable rise from RMB15.1 to 16.6, growing by 9.9%.

China Power of Retailing 2015 58 Figure 4-9 Average daily revenue per transaction in sampled convenience stores in three categories (yuan/person/day)

45.0 11.0%

40.0 38.5 35.3 10.5% 10.5% 35.0

30.0 10.0% 9.9% 25.0 9.5% 18.2 20.0 9.1% 16.4 16.6 15.1 15.0 9.0% 10.0 8.5% 5.0

0.0 8.0% ≥200 100-199 50-99

2013年 2014年 2014 growth %

Gross margin % in the sample convenience stores in three categories Figure 4-10 Gross margin % in sample convenience stores in three categories

30.0% 8.0%

24.6% 7.0% 25.0% 23.0% 23.4% 23.0% 7.0% 5.9% 6.0% 20.0% 5.0% 15.7% 14.8% 15.0% 4.0%

3.0% 10.0%

2.0%

5.0% 1.0% 1.6%

0.0% 0.0% ≥200 100-199 50-99

2013年 2014年 2014 Growth %

China Power of Retailing 2015 59 V. Department stores and shopping malls

5.1 Operating conditions in sample department store and shopping mall enterprises 66 enterprises that mainly operate department stores have fulfilled the requirements to respond to the questionnaire. A majority of them reported a revenue of less than RMB20 billion. Among them, 35, or 53%, reported a revenue of less than RMB10 billion, 13, or 20%, reported a revenue between RMB10-20 billion, and 18, or 27%, booked a revenue of RMB20 billion. Half, or 33, of these enterprises are from tire I and tire II cities and most of the remainder come from tire III or tire IV cities

Figure 5-1 Revenue of sample department store enterprises

RMB20-70 billion 27%

100亿元以下 53%

RMB10-20 billion 20%

Average scale of enterprise The 66 sample enterprises recorded a low revenue growth of 1.3% in 2014, continuing the trend from a year before. The average number of stores continued to fall by 4.2% but all stores tended to expand in operating space and revenue.

China Power of Retailing 2015 60 Figure 5-2 Average scale of sample department store enterprises

300.0 8.0% 272.6 6.8% 261.2 250.0 6.0%

4.0% 200.0

1.3% 2.0% 150.0 136.1 137.9 120.0 115.3 0.0%

100.0 81.3 86.8 -2.0%

50.0 -4.0% -4.2% -3.9% 0.0 -6.0% revenue (RMB100 million) number of stores (100) business area (10,000 number of employees square meters) (1,000)

2013年 2014年 2014 growth rate

Expenses Sample department store enterprises recorded a rise in labor expenses from 2013 by 7.7% and, although the rise slowed (lower than the 18% from a year before), its percentage over total revenue remained unchanged from a year before (both at 2.9%).

The average rent expenses in sample enterprises increased 10.4% from a year before, the same growth rate as a year before. The increase was mainly due to the rise in operating spaces. The ratio of rent expenses over total revenue actually went down by 0.2% in 2014. Utility expenses fell by 5.8% from a year before but the ratio of utility expenses over total revenue remained barely changed at 0.8%.

Figure 5-3 Expenses of sample department store enterprises

40,000.0 12.0% 10.4% 36,024.3 35,000.0 33,452.9 10.0% 7.7% 8.0% 30,000.0 6.0% 25,000.0 4.0% 20,000.0 2.0% 15,394.3 15,000.0 13,939.3 0.0% 9,563.7 9,009.7 -2.0% 10,000.0 -4.0% 5,000.0 -6.0% -5.8% 0.0 -8.0% rents(RMB10,000) labor cost (RMB10,000) utilities (RMB10,000)

2013年 2014年 growth % in 2014

China Power of Retailing 2015 61 Figure 5-4 Expense structure in sample department store enterprises

100.0% 17.9% 15.9%

57.6% 58.5%

24.5% 25.6% 0.0% 2013 2014

rents labor utilities

Note: Among the sample enterprises in 2014, 62.1% own stores. In average, the ratio of number of owned stores over total number of stores increased from 14.6% in 2013 to 16.3% in 2014 and the number of owned stores added in 2014 increased by 8.7%. Internet retail business The average revenue generated from internet sales by the sample department store enterprises was RMB40.91 million, accounting merely for 0.2% of total revenue.

Proprietary brands 78% of sample department store enterprises had proprietary brands, which generated 2.1% of the total revenue.

5.2 Operating conditions in the sample department stores Out of the 20 department stores sampled in this questionnaire, 11 are located in tire I and tire II cities, and 9 are located in tire III and tire IV cities. The average business area is 36,000 square meters with the lowest at 11,980 square meters and highest at 87,000 square meters. The average revenue is RMB1.18 billion with the lowest being RMB250 million and highest being RMB3.1 billion.

Average scale of stores In 2014, the revenue from the sample department stores fell by 4.8%. The business areas in these stores did not change much from a year before, the number of employees fell by 4.8%, and the number of single products offered increased by 4.2%.

Figure 5-5 Average scale of sample department stores

China Power of Retailing 2015 62 14 6.00% 12.4 11.8 12 4.00% 4.2% 10 2.00% 8 0.0% 0.00% 6 4.8 5.0 4.2 3.6 3.6 4.0 -2.00% 4

2 -4.8% -4.8% -4.00%

0 -6.00% revenue (RMB100 number of single product business area (10,000 number of employees million) available for sale square meters) (100) (10,000)

2013年 2014年 2014 growth%

Store operating efficiency The efficiency per square meter, efficiency per head and revenue per single product available for sale all fell slightly in 2014, indicating the worsening operating efficiency.

Table 5-1 Efficiency per square meter, efficiency per head, and revenue per single product available for sale in the sample department stores

Efficiency per square meter Efficiency per head Sales per single Project (RMB10,000/square (RMB10,000/person/year) product (RMB10,000) meter/year) 2014 3.4 301.2 2.0 2013 3.5 301.5 2.1 2014 Growth% -2.9% -0.1% -4.8% Average daily revenue per transaction per store The average daily revenue per transaction per store in 2014 was RMB376.7, representing a yoy growth of 4.0% (RMB362.2 in 2013) which was half of the growth rate from a year before.

Store expenses Rise was seen in all three expenses except for utilities. Employee salary remained to be the biggest contributor to the total expense in department stores and its ratio over the total expense decreased 1.6 percentage points. Given the fact that the number of employees fell 4.8%, it is apparent that a rising labor expense was directly related to the increasing salary level. Rent expense was the second biggest contributor and rose more sharply than a year before, indicating that the level of rents had a noticeably faster rise in 2014. Utility expense, accounting for the least in total expense, fell from a year before, signaling the efforts made across the stores in cost control.

China Power of Retailing 2015 63 Table 5-2 Three expenses in the sample department stores

Ratio of three Rents Employee salary Utilities Project expenses over (RMB10,000) (RMB10,000) (RMB10,000) revenue 2014 4.8% 1906.8 2324.3 672.5

2013 4.4% 1648.1 2145.9 707.1 Growth% in 2014 8.2% 15.7% 8.3% -4.9%

Figure 5-6 Structure of three expenses in sample department stores

100.0% 19.5% 17.7% Annual growth rate of three expenses

2012-2013 2013-2014 44.8% 43.2% 1.0% -4.9%

35.7% 39.1% 7.5% 8.3%

0.0% 2013年 2014年 0.7% 15.7% Rents Total salary Utilities

Store gross margin % The average gross margin % in sample department stores was 16.0%, unchanged from the level in 2013. The difference in gross margin % among different stores was narrower than other types of operation, with the lowest at 9.3% and highest at 22.5%. However, due to the large scale of department stores, if calculated by the average revenue in sampled department stores, the absolute amount of gross margin difference between the stores with the highest gross margin% and the lowest was RMB160 million.

Figure 5-7 Distribution of gross margin % in sampled department stores2

25 20 15 10 5 0

Gross margin % Average gross margin %

2 Three stores did not report information on gross margin % and as a result, the figure only shows information of 17 stores.

China Power of Retailing 2015 64 Logistics, distribution and inventory turns The average ratio of centralized distribution in the sample stores was 66%, slightly higher than that in 2013. The average inventory turns were 33 days, one day shorter than in 2013.

Comparison of department stores of different business areas As department stores differ dramatically in terms of store business areas, we further classify these stores into two categories by business area to increase compatibility, namely 10,000-29,999 square meters and above 30,000 square meters.

Average scale of stores by the two categories Table 5-3 shows that the average revenue and number of employees from all the stores of both categories declined. The greater decline, at 5%, came from stores with a business area of 30,000 square meters or above while those with a business area between 10,000-29,999 square meters declined by 3.7%. A smaller percentage of employees (2.1%) from stores with a business area of 30,000 square meters or above were downsized. In comparison, 10.8% of workforce in stores with a business area between 10,000-29,999 square meters was downsized.

Table 5-3 Average scale of sample department stores in two categories Number of Categories Average Average number single by business Revenue business area of full-time Year products area (square (RMB10,000) (square employees available for meters ) meter) (person) sale (unit)

2014 171,212 52,112 562 84,050 ≥30000 2013 180,201 52,112 574 83,554

2014 Growth % -5.0% 0.0% -2.1% 0.6%

2014 48,247 13,113 227 24,207

10000-29999 2013 50,109 13,158 255 22,209

2014 Growth % -3.7% -0.3% -10.8% 9.0%

Operating efficiency of the sample stores in two categories Stores with a business area of 30,000 square meters or above had an efficiency per square meter and efficiency per head at 5.7% and 3.8% respectively, both declining from a year before. Stores with a business area between 10,000 and 29,999 square meters showed a rise in both indicators.

Comparing the three indicators in stores from the two categories in 2014, employees in the stores with a business area of 30,000 square meters and above were allocated a higher revenue (efficiency per head) per person, namely RMB2.03 million, than those in

China Power of Retailing 2015 65 smaller stores due to economy of scale. However, smaller stores outperformed larger stores in efficiency per square meter and revenue per single product. The latter, in particular, in the stores with a business area between 10,000 and 29,999 was more than twice of that in larger stores.

Table 5-4 Efficiency per square meter, per head and revenue per single product in the sampled department stores of the two categories

Efficiency per Efficiency per Revenue per Categories by square meter head Year single product business area (RMB10,000/squa (RMB10,000/pers (RMB10,000) re meter/year) on/year)

2014 3.3 396.8 1.2 ≥30000 2013 3.5 412.4 1.2 2014 Growth % -5.7% -3.8% 0.0% 2014 3.5 193.6 3.0 10000-29999 2013 3.4 176.8 3.3 2014 Growth % 2.9% 9.5% -9.1%

Figure 5-8 2013 Comparison of operating efficiency in the sample department stores in the two categories

4.5 4.0 4.0 3.5 3.3 3.5 3.0 3.0 2.5 1.9 2.0 1.5 1.2 1.0 0.5 0.0 Efficiency per square meter Efficiency per head (RMB1 Revenue per single product (RMB10,000/square meter/year) million/person/year) (RMB10,000)

≥30000 14000-29999

Average daily revenue per transaction in the sample stores in the two categories Stores in both categories showed some improvement in average daily revenue per transaction in 2014.

Department stores with a business area of 30,000 square meters and above had an average daily revenue per transaction of RMB785.8, tripling that in stores with a business area between 10,000 and 29,999 square meters.

China Power of Retailing 2015 66 Figure 5-9 Average daily revenue per transaction in the sample department stores in the two categories

900.0 5.6% 6.0% 785.8 800.0 760.2 5.0% 700.0

600.0 3.4% 4.0% 500.0 3.0% 400.0 300.0 229.0 241.8 2.0% 200.0 1.0% 100.0 0.0 0.0% ≥30000 10000-29999

2013年 2014年 2014 Growth %

Gross margin % in the sample stores in the two categories The stores in both categories had a 16.3% of gross margin %, but the gross margin % in the stores with a business area of 30,000 square meters or above increased 1.3% from a year before while that in the stores with a business area between 10,000 and 29,000 fell 1.2%.

Figure 5-10 Gross margin % in the sample department stores in the two categories

20.0% 1.3% 1.5% 16.6% 16.0% 16.2% 16.4% 1.0% 16.0%

0.5% 12.0% 0.0% 8.0% -0.5%

4.0% -1.2% -1.0%

0.0% -1.5% ≥30000 10000-29999

2013年 2014年 2014 Growth %

5.3 Operating conditions of the sample shopping malls

Out of the 14 shopping malls sampled in the questionnaire, 8 are located in tire I and tire II cities, and 6 are located in tire III and tier IV cities. The average business area of these

China Power of Retailing 2015 67 shopping malls is 121,000 square meters, the smallest being 26,000 square meters and the largest being 600,000 square meters. The average revenue is RMB2.06 billion, the lowest being RMB100 million and the highest RMB13.5 billion

Average scale of sample shopping malls Sample shopping malls saw a slight growth in revenue by 1.9% in 2014. While both the business area and number of employees were on the rise, the number of single products offered showed little change.

Figure 5-11 Average scale of sample shopping mall stores

25.0 12.0% 20.6 20.2 10.0% 20.0 10.5% 7.3% 8.0% 15.0 12.1 6.0% 11.0 9.6 9.5 9.1 9.8 10.0 4.0% 1.9% 2.0% 5.0 -0.3% 0.0% 0.0 -2.0% Revenue (RMB100 Number of single Business area (10,000 Average number of million) products available for square meters) employees (100) sale (10,000)

2013 2014 2014 Growth %

Store operating efficiency In 2014, the efficiency per square meter, efficiency per head and revenue per single product across all sample shopping malls all declined, by 1.5%, 3.9% and 0.7% respectively.

Figure 5-5 Efficiency per square meter, efficiency per head and revenue per single product in sample shopping mall stores

China Power of Retailing 2015 68 Efficiency per square Efficiency per head meter Revenue per single Projects (RMB10,000/person/ye (RMB10,000/square product (RMB10,000) ar) meter/year)

2014 1.97 264.0 4.0 2013 2.00 275.0 4.1 2014 Growth % -1.5% -3.9% -0.7%

Average daily revenue per transaction per store In 2014, the average daily revenue per transaction per store was RMB652.7 and fell by about RMB65.2 from 2013 (RMB717.9).

Store expenses The increase in rents, labor expenses and utilities accelerated. Rents increased the most by 28.5% and the other two increased by 19.2% and 13.4%. The biggest contributor to cost was employee salary, at 61.8% which was higher than that in other types of operation, followed by utilities and rents.

Table 5-6 Three expenses in sample shopping mall stores

Ratio of three Rents Employee salary Utilities Project expenses over (RMB10,000) (RMB10,000) (RMB10,000) revenue

2014 2.7% 989.7 3634.3 1641.9 2013 2.7% 770.3 3049.0 1448.1 Growth% in 2014 -0.2% 28.5% 19.2% 13.4%

Figure 5-12 Structure of three expenses in sample shopping mall stores

China Power of Retailing 2015 69

100.0%

29.1% 27.9%

61.3% 61.8%

9.5% 10.3% 0.0% 2013年 2014年

Rents Total salary Utilities

Store gross margin % The average gross margin % in the sampled shopping malls was 14.0%, remaining at about the same level from a year before. The gross margin % differentiated significantly with the lowest being 9.3% and highest being 24.4%. If calculated by the average revenue of the sampled shopping malls, the difference between the store with the highest gross margin % and that with the lowest % was RMB300 million.

Figure 5-13 Distribution of gross margin % in sample shopping malls

30 25 20 15 10 5 0 Stores1 Stores3 Stores5 Stores7 Stores9 Stores11 Stores13

Gross margin % Average gross margin %

Logistics, distribution and inventory turns The average ratio of centralized distribution in the sample stores was 48%, higher than 2013 by about 2 percentage points. The average inventory turns were 48 days, one day longer than in 2013 in average.

China Power of Retailing 2015 70 VI Specialty stores

6.1 Operating conditions in sample enterprises 24 enterprises operating specialty stores as their primary business responded to this questionnaire. They covered electrical home appliances, 3C consumer electronics, household products and food. In terms of revenue, 15 enterprises reported a revenue below RMB10 billion, 7 reported a revenue between RMB10 and 100 billion, and another 2 reported a revenue of more than RMB100 billion. 23 of them were from tire I and tire II cities, and 1 from tire III city. Below analysis is based on these 24 sample enterprises.

Figure 6-1 Revenue of sample specialty store enterprises

RMB100- 200 billion 8%

RMB10- 100 billion 29% below RMB10 billion 63%

Average scale of enterprises The number of stores and employees increased from a year before by 14.1% and 16.9% respectively, in contrast to a slower growth in business area (7.5%) and revenue (1.4%).

Figure 6-2 Average scale of sample specialty store enterprises

200.0 182.3 18.0% 179.7 16.9% 180.0 16.0% 148.7 160.0 14.1% 14.0% 127.2 140.0 120.4 12.0% 120.0 112.0 10.0% 100.0 8.0% 80.0 7.5% 6.0% 60.0 40.0 4.0% 13.0 14.8 2.0% 20.0 1.4% - 0.0% Revenue (RMB100 Number of stores (100) Business area (10,000 Number of employees million) square meters) (100)

2013 2014 growth %

China Power of Retailing 2015 71 Enterprise expenses Unlike other types of operation, rents were the biggest contributor to the cost in specialty stores, accounting for 57.6%, followed by labor and utilities. All the three expenses showed an increase with the labor expense leading the rise by 10.1%.

Figure 6-3 Expense structure in sample specialty store enterprises

100% 7.9% 7.8% 90%

80% 33.7% 34.6% 70% 60%

50% 40%

30% 58.3% 57.6% 20% 10% 0% 2013 2014

Rents Employee salaries Utilities

Figure 6-4 Enterprise expenses in sample specialty store enterprises

100,000.0 12.0% 88,961.2 90,000.0 83,916.3 10.1% 10.0% 80,000.0 70,000.0 8.0% 60,000.0 53,444.1 48,525.2 50,000.0 6.0% 6.0% 5.3% 40,000.0 4.0% 30,000.0 20,000.0 11,428.6 12,037.7 2.0% 10,000.0 - 0.0% Rents (RMB10,000) Employee salaries (RMB10,000) Utilities (RMB10,000)

2013 2014 Growth in 2014

Internet retail business Among the 24 sample specialty store enterprises, 12 had internet retail business that contributed a revenue of RMB3.27 billion per year averagely , accounting for 7.8% of total revenue. These 12 stores were mainly in the business of electrical appliances and digital products, as well as some specialty stores in foods and drugs.

China Power of Retailing 2015 72 Proprietary brands Among the sample specialty store enterprises, 12 had proprietary brands of their own and the revenue from selling proprietary brands accounted for 50.5% of total revenue on average.

6.2 Operating conditions in sample stores specializing in electrical appliances and 3C products There were 4 sample specialty stores in the survey, which were all retail stores selling electrical appliances and 3C products. 2 of them are located in tire I and tire II cities and the other 2 are located in tire III and tire IV cities. The average business area was 4,547 square meters with the smallest being 3,107 square meters and largest being 7,000 square meters. The average revenue was RMB120 million with the lowest being RMB70 million and highest being RMB180 million. There were no significant differences in the main line of business and scale of operation among these stores.

Average scale of enterprises On average, the number of single products offered in the sample specialty stores decreased by 33 units per store, a drop of 0.6% from a year before. The number of employees fell by 19.0%, while the revenue increased slightly, fueled by the dramatic improvement in efficiency per head, to reach RMB120 million. In addition, the business area increased by 5.8%.

Figure 6-5 Average scale of sample specialty stores

1.4 10%

1.2 1.2 1.2 5.8% 5%

1.1% 1.0 -0.6% 0%

0.8 -5%

0.6 0.5 0.5 0.5 -10% 0.4 0.5 0.4 0.4 -15%

0.2 -19.0% -20%

- -25% Revenue (RMB100 million) Number of single products Business area (10,000 square Number of employees (100) available for sale (10,000) meters)

2013 2014 2014 growth %

Store operating efficiency The average efficiency per square meter in sample stores fell 1.8% while the efficiency per head and revenue per single product improved by 13.7% and 7.5% respectively.

China Power of Retailing 2015 73 Figure 6-1 Efficiency per square meter, per head and revenue per single product available for sale in sample specialty stores

Efficiency per square Efficiency per head meter Revenue per single Project (RMB10,000/person/ (RMB10,000/square product (RMB10,000) year) meter/year) 2014 2.6 392.4 17.9 2013 2.6 345.3 16.7

2014 Growth % -1.8% 13.7% 7.5%

Note: Numbers are calculated based on the efficiency per square meter, efficiency per head and revenue per single product in each store, not estimated from average revenue.

Average daily revenue per transaction per store The average daily revenue per transaction per store was RMB1,758.7 in 2014, falling by 5.2% from 2013.

Store expenses Rents and utilities in sample stores increased by 22.0% and 9.6% respectively from 2013, while the employee salary dropped 11.0%. Rents, as the biggest contributor, accounted for 51.9% of the total expense, followed by employee salary accounting for 38.3%.

Table 6-2 Three expenses in sample specialty stores Ratio of three Rents Employee salary Utilities Project expenses over (RMB10,000) (RMB10,000) (RMB10,000) revenue In 2014 5.3% 322.8 238.4 60.7

In 2013 5.0% 264.6 267.9 55.3

Growth% in 2014 4.6% 22.0% -11.0% 9.6%

Figure 6-6 Structure of three expenses in sample specialty stores

100% Annual growth rate of three 9.4% 9.8% expenses 80% 2012-2013 2013-2014 45.6% 38.3% 60% -38.4% 9.6%

40% 51.9% 20% 45.0% -11.0% -11.0%

0% 2013 2014 14.3% 22.0%

Rents Total salary Utilities

China Power of Retailing 2015 74 Store gross margin % The average gross margin % in the sampled electrical appliance specialty stores was 10.1%, slightly higher than the 9.8% in 2013. The gross margin % differentiated significantly among stores with the lowest being 5.8% and highest being 16.0%. If calculated by the average revenue of the sampled specialty stores, the difference between the store with the highest gross margin % and that with the lowest % was RMB12.05 million. The average gross margin % in all the stores across all types of operation in the industry was 16.2%, higher than that of the sampled electrical appliance stores.

Figure 6-7 Distribution of gross margin % in sample specialty stores

20.0

15.0

10.0

5.0

- Stores1 Stores2 Stores3 Stores4

Gross margin % Average gross margin %

Logistics, distribution and inventory turns The average ratio of centralized distribution in the sample stores was 77%, rising by 5% than a year before. The average inventory turns were 97 days, 8 days less than in 2013 on average.

China Power of Retailing 2015 75 Appendix: Top 100 Chain Store Enterprises in China

After conducting a survey on China’s chain store and Top 100 Chain Store franchise sector and operating conditions in enterprises Enterprises in early 2015, CCFA published the 2014 Top 100 Chain · RMB2,096.4 billion – total Store Enterprises in China in April of the same year. The revenue total revenue of the top 100 in the survey reached · 107,366 – total number of RMB2.1 trillion, representing a yoy growth of 5.1%. The stores total number of stores arrived at 107,366, increasing 4.2% · RMB21 billion – average scale on yoy basis. The threshold to be listed in the top 100 of revenue was RMB3.1 billion, lower by 9.8% from a year before. · RMB3.1 billion –threshold to The average scale of revenue was RMB21 billion and be listed the average gross margin % was 16.4%, increasing 0.2 · 16.4% -- average gross percentage points from a year before. margin %

Top performers in top 100 chain enterprises Based on the data from 2012-2014, 23 enterprises have been ranked in the top 30 of the top 100 list for three consecutive years, which posted a total revenue of RMB1.14 trillion for the year of 2014, accounting for 54% of the total revenue of the top 100 enterprises. Out of the 23 enterprises, 6 are foreign companies, 1 is Hong Kong/Taiwan company and 16 are domestic companies (including 6 state-owned, 1 state-holding, 8 private and 1 joint-equity enterprises). Foreign and Hong Kong/Taiwan enterprises are all in a single type of operation while 10 domestic enterprises are in a single type of operation and 6 are in a multi-type of operations.

In the past three years, Suning Corporation and Gome Electrical Appliance Holdings Ltd. secured their top three positions for three years in a row while China Resources Vanguard Co. Ltd.’s number three position has not changed. Kang Investment (China) Co., Ltd. (RT) was among the best-performing foreign companies. It grew the revenue by 6.9% in 2014 to continue ranking at the fourth place. Among the domestic companies that made the fastest climb in the list were Yonghui supermarket Limited by Share Ltd. and Chang Chun Eurasia Group Co. Ltd. The former reported revenue growths of 25.5% and 22.6% in 2013 and 2014 respectively, far outpacing the industry average and pushing its ranking up from 13 in 2012 to 12 in 2014. Chang Chun Eurasia kept a robust and steady growth % in the past few years and saw its ranking ascending by 4 places in the past three years.

China Power of Retailing 2015 76 Top Performers in Top 100 Chain Retailers

2014 Revenue Ranking Revenue Company Name (RMB10,000 growth% 2014 2013 2012 including tax)

Gome Electrical Appliance Holdings Ltd 1 2 3 14,348,266.00 7.6%

Suning Corporation 2 1 1 14,276,100.00 3.5%

China Resources Vanguard Co. Ltd. 3 3 4 10,400,000.00 3.6%

Kang Investment (China) Co., Ltd. (RT) 4 4 5 8,567,000.00 6.9%

Walmart Stores (China) Inc. 5 5 6 7,237,558.00 0.2% Chongqing General Trading (Group) 8 9 7 6,148,418.00 2.0% Co., Ltd Yum! Brands Inc., China Division 10 10 8 5,070,000.00 1.0% Carrefour (China) management 11 11 10 4,572,212.00 -2.1% consulting services Co., Ltd Yonghui supermarket Limited by Share 12 13 13 4,300,000.00 22.6% Ltd Dashang Grp Co.,Ltd 13 12 11 3,768,000.00 -4.6%

Wuhan Department Store Group Co. 14 15 14 3,400,003.00 10.8% Ltd.

Chang Chun Eurasia Group Co. Ltd. 15 19 19 3,232,232.00 14.3%

Zhongbai Holdings Group Co., Ltd 16 18 16 3,221,803.00 9.9%

ShijiaZhuang Beiguo Renbai Group 17 16 17 3,213,628.00 6.5% corp Hisap 18 20 15 3,035,023.65 10.1% Shanghai Nong Gong Shang 19 17 12 2,938,187.00 -2.1% Supermarket Co., Ltd Hainan Airlines Commercial Holdings 20 22 20 2,790,000.00 5.7% Limited

Rainbow Department Store Co., Ltd. 23 25 23 2,338,992.00 6.2%

Liqun Group Co., Ltd 24 24 22 2,307,900.00 0.9% Yantai Zhenhua Department Store 25 26 27 2,306,100.00 5.0% Group Co., Ltd. Wenfeng Great World Chain 27 28 26 2,170,674.00 4.8% Development Co., Ltd. Beijing Wangfujing Department Store 28 23 21 2,166,596.00 -8.4% (Group) Co., Ltd. Jiangsu Five Star Appliance Co., Ltd 29 21 18 2,100,000.00 -21.1% Total 113,908,692.65 3.93%

Data Source: CCFA, Deloitte Analytics

China Power of Retailing 2015 77 Notes about calculation Operating indicator Revenue per transaction（RMB yuan）= Revenue/number of transactions

Efficiency indicator · Efficiency per head=Total revenue/total number of employees · Efficiency per square meter= Total revenue/operating area · Revenue per single product＝Total revenue／number of single products · Inventory turns=Total revenue/（beginning inventory+ending inventory）/2

China Power of Retailing 2015 78 Top 100 Chain Retailers in China 2014 Growth Total in # 2014 Revenue Revenue Company Name number number Remarks （RMB10,000） growth% of stores of （unit） stores% Gome Electrical Appliance 1 14348266 7.6% 1698 7.1% ★ Holdings Ltd 2 Suning Corporation * 14276100 3.5% 1696 4.3% ① ★ China Resources Vanguard 10400000 12.6% 4127 7.6% ② 3 Co. Ltd. ★ Under which: CR Suguo 3342400 -1.3% 2103 -0.3% Kang Investment (China) 4 8567000 6.9% 304 15.2% ★ Co., Ltd. (RT) 5 Walmart Stores (China) Inc. 7237558 0.2% 411 1.0% ③ ★ Shandong Commercial 6 6392336 4.6% 638 11.0% ☆ Group Co., Ltd. LianhuaSupermarket 7 6175076 -10.3% 4325 -6.0% ④ ★ Holdings Co., Ltd. Chongqing General Trading 8 6148418 2.0% 335 2.8% ★ (Group) Co., Ltd 9 Bailian Group * 5986000 1.2% 4400 -6.4% ⑤ ☆ Yum! Brands Inc., China 10 5070000 1.0% 6600 10.0% ★ Division Carrefour (China) 11 management consulting 4572212 -2.1% 237 0.4% ★ services Co., Ltd Yonghui supermarket 12 * 4300000 22.6% 337 15.4% ★ Limited by Share Ltd 13 Dashang Grp Co.,Ltd * 3768000 -4.6% 200 3.1% ★ Wuhan Department Store 14 3400003 10.8% 98 -2.0% ★ Group Co. Ltd. Chang Chun Eurasia Group 15 3232232 14.3% 81 8.0% ★ Co. Ltd. Zhongbai Holdings Group 16 3221803 9.9% 1037 2.1% ★ Co., Ltd ShijiaZhuang Beiguo Renbai 17 3213628 6.5% 102 8.5% Group corp. 18 Hisap 3035024 10.1% 572 12.2% ★ Shanghai Nong Gong Shang 19 2938187 -2.1% 2566 -3.0% ★ Supermarket Co., Ltd Hainan Airlines Commercial 20 2790000 5.7% 507 5.2% ★ Holdings Limited Better Life Commercial 21 2703795 27.6% 525 18.0% ⑥ ★ Chain Share Co. Wanda Department Store 22 2559996 65.2% 99 32.0% ★ Co. Ltd. Rainbow Department Store 23 2338992 6.2% 67 8.1% ★ Co., Ltd.

China Power of Retailing 2015 79 24 Liqun Group Co., Ltd. 2307900 0.9% 600 3.4% ★ Yantai Zhenhua Department 25 2306100 6.6% 111 -1.8% ☆ Store Group Co., Ltd. Beijing Wumart Commercial 26 2196447 11.3% 565 3.3% ⑦ Group Co., Ltd. Wenfeng Great World Chain 27 2170674 4.8% 879 -4.6% ★ Development Co., Ltd. Beijing Wangfujing 28 Department Store (Group) 2166596 -6.0% 28 3.7% ★ Co., Ltd. Jiangsu Five Star Appliance 29 2100000 -21.1% 184 -2.6% ★ Co., Ltd. Shandong Jiajiayue 30 2094516 10.2% 608 1.2% ★ Investment Holdings Limited Parkson Retail Group 31 * 1944944 -4.2% 57 -1.7% ☆ Limited Metro Jinjiang Cash & Carry 32 1890000 8.0% 81 11.0% ★ Co., Ltd. Intime Commercial (Group) 33 1831852 0.8% 47 30.6% ★ Co., Ltd. 34 Lotte Mart Co., Ltd. * 1800000 16.1% 123 11.8% ★ Golden Eagle International 35 Retail Group (China) Co., 1725746 -8.2% 29 7.4% ★ Ltd. 36 Zhengzhou Dennis Group 1720000 21.1% 226 24.9% 37 Sinopec easyjoy sales co. ltd 1713019 28.3% 23730 1.3% ★ 38 Beijing Digiton 1690279 12.1% 1484 1.3% ★ Anhui Huishang Group Co., 39 1670609 -0.4% 2160 -6.5% ★ Ltd. 40 A Best 1650301 -3.0% 110 -5.2% ★ Auchan (China) Investment 41 1650000 5.1% 68 15.3% ★ Co., Ltd. Shandong Weifang 42 Department Store Group 1638966 8.3% 600 5.3% ★ Co., Ltd. Guangzhou Watsons Co., 43 * 1638136 14.0% 2088 23.3% ★ Ltd. Hefei Department Store 44 1600000 -2.1% 176 -7.4% ⑧ ★ Group Co., Ltd. Beijing Hualian Hypermarket 44 * 1600000 8.8% 145 3.6% △ Co., Ltd. Liaoning Xinglong Dajiating 46 1544693 9.6% 37 5.7% ★ Commercial Group Wuhan Zhongnan 47 1492240 8.7% 49 -5.8% ★ Commercial Group Co., Ltd. Beijing Jingkelong Group 48 * 1422535 3.5% 285 21.8% ★ Co., Ltd. New Hua Du Supercenter 49 1406160 3.0% 122 3.4% ★ Co., Ltd. Beijing Capital Retailing 50 1384886 -1.6% 18 5.9% ★ Group Co., Ltd.

China Power of Retailing 2015 80 51 Lotus 1378203 0.2% 77 0.0% ★ Jiangsu Huadi International 52 1328734 -0.9% 47 2.2% ★ Holdings Group Ltd. Ren Ren Le Commercial 53 1279645 -2.2% 117 -8.6% ★ Group Co., Ltd. Beijing Caishikou 54 1212121 -10.8% 19 18.8% Department Store Co., Ltd. Beijing Leyushiji Technology 55 1168686 0.3% 2168 -8.9% ⑨ ★ Group Co., Ltd 56 McDonald's (China) Co., Ltd. * 1150000 11.7% 2100 20.0% ★ 57 Guangzhou Grandbuy Corp. 1134911 -0.6% 27 -3.6% ★ Dongguan rum Group 58 Meiyijia convenience stores 1099365 71.1% 6390 14.5% ⑩ ★ Ltd. Maoye International Holdings 59 * 1076414 -5.4% 41 2.5% Limited 60 IKEA 1021956 24.4% 16 14.3% ★ PetroChina Sales Company 61 988000 -5.7% 15000 7.1% ★ (uSmile) AEON (China) Investment 62 976537 11.4% 50 13.6% ★ Co., Ltd. 63 Xinjiang Friendship Group * 966000 -14.0% 61 5.2% ★ Shandong Xinxing Group 64 910918 -5.5% 586 -10.4% ★ Ltd. Chengdu Hongqi Chain Co., 65 881249 6.6% 1577 8.0% ★ Ltd. Nanjing Central Department 66 * 800760 -8.9% 15 50.0% Store (Group) Co., Ltd. Jinan Hualian Group Co., 67 797876 11.5% 41 51.9% ☆ Ltd. Yinchuan Xinhua 68 Department Store Group * 797600 3.2% 228 8.6% Co., Ltd. Business Hunan Friendship & Apollo 69 776480 -1.5% 11 0.0% ★ Holding Co., Ltd. 70 Ito-Yokado (China) 727178 0.1% 12 -14.3% ★ Beijing Cuiwei Tower Co., 71 715000 35.5% 8 60.0% ★ Ltd. Shanxi Meet All Chain 72 656037 17.8% 130 46.1% ★ Supermarket Co., Ltd Shandong Quanfuyuan 73 651400 19.9% 267 19.2% ★ Commercial Group Xinyulou Department Store 74 640000 30.6% 18 12.5% ★ Group Co., Ltd. Handan Yangguang 75 Department Store Group 611000 1.5% 175 2.9% ★ Company 76 Eading Group Co., Ltd. 562070 17.0% 363 -5.0% ★ Fuyang Hualian Group Co., 77 550116 6.1% 795 1.1% ★ Ltd.

China Power of Retailing 2015 81 Jialeyuan Commercial Co., 78 533021 5.0% 44 0.0% ★ Ltd. 79 Qingdao Weekly Group. 530500 5.3% 10 0.0% ★ Qingdao Likelai Group Co., 80 525839 14.3% 431 0.9% ★ Ltd. Dashenlin Pharmaceutical 81 516000 11.0% 1600 14.3% ★ Group Inc. Hunan Jiahui Department 82 510370 5.2% 247 2.1% ★ Store Co., Ltd. Beijing Huaguan Commercial 83 507926 12.1% 273 -3.2% ★ Co., Ltd Changsha Tongcheng 84 502552 -0.3% 77 5.5% Holdings Co., Ltd. Sanjiang Shopping Club Co., 85 487046 -5.2% 154 2.7% ★ Ltd. Zhejiang Renben 86 486734 5.8% 1693 4.4% ★ Supermarket Co., Ltd 87 Xiongfeng Group Co., Ltd. 438795 10.5% 135 -10.0% ★ 88 Beijing CSF Market 437051 1.7% 155 8.4% ★ Family Mart Convenience 89 420000 13.5% 1281 20.4% ★ Store Guangzhou Friendship 90 392016 -17.8% 6 0.0% ★ Group Co., Ltd. 91 PARKnSHOP (China) 392012 4.3% 70 7.7% ★ New Cooperation 92 Supermarket Co., Ltd. 390585 4.0% 2236 4.0% △ Shiyan Jiangsu New Cooperation 93 Changkelong Supermarket 380441 6.1% 1029 1.3% ★ Chain Co., Ltd. Shanxi Taiyuan Tangjiu 94 355360 1.9% 1340 7.2% ★ Supermarket Co., Ltd. 95 Jiabei Logistics Co., Ltd. 330000 -7.0% 350 -1.1% ★ China Quanjude (Group) 96 327624 -0.5% 99 3.1% ★ Co., Ltd. 97 Zhejiang Hualian Co., Ltd. 327500 -3.0% 78 -7.1% New World Department 98 * 323900 -1.4% 43 0.0% ⑪ Store China Limited Henan DaZhang Group Co., 99 318000 22.0% 56 1.8% ★ Ltd.. 100 Xinlianxin Group Co., Ltd. 314799 15.4% 48 0.0% ★ Total 209637552 5.1% 107366 4.2%

China Power of Retailing 2015 82 1. ★ indicates that it is a member enterprise of CCFA, ☆ indicates that its subordinating Notes： company is a member of CCFA，△ indicates that its parent company is a member of CCFA. 2. A figure preceded by a * indicates that it is an estimated number.

3. Top 100 enterprises are ranked by the scale of revenue, including the sales before tax by the stores and the sales before tax by the enterprises. Stores here include the directly- operated stores, franchise stores, and chain stores managed through authorizing the use of

brand names. The scale of revenue does not include intra-company sales, transactional amount in wholesale market, or sales of production materials such as cars, gas stations and agricultural means of production.

4. (Scale of revenue and number of stores of) Enterprises primarily in a business of

franchising are not included in the list.

5. Notes about the data of some enterprises: ① Suning Corporation is a subordinate company of Suning Holdings (Group)

which had a scale of revenue before tax of RMB273.576 billion in 2014. ② The revenue of China Resources Vanguard Co. Ltd. included the revenue of

Tesco China between June 1 2014 and December 31. ③ The revenue of Walmart Stores (China) Inc. does not include the revenue from

yhd.com ④ The revenue of Lianhua Supermarket Holdings Co., Ltd. includes the revenue from Carrefour stores in Shanghai. Lianhua Supermarket Holdings Co., Ltd. has equity investment in Bailian Group. ⑤ Shanghai Friendship Group Co., Ltd. was listed among Top 100 last year and the name was changed to “Bailian Group Co., Ltd”, which completed the

business registration on July 31, 2014 and since has included Lianhua Supermarket Co., Ltd. in its consolidated financial statement. ⑥ The revenue includes that from Zhejiang Gongxiao Supermarket Store Co., Ltd. It was listed among the top 100 by the name of Beijing Wumart Commercial Group Co., Ltd. ⑦ The revenue of Better Life Commercial Chain Share Co. does not include data

from Guangxi Nancheng Department Store. ⑧ The data of Hefei Department Store Group Co., Ltd. does not include wholesale

transactions. ⑨ It was acquired by SanPower Group and has no equity investment relationship

with Hisap. ⑩ The actual scale of revenue is RMB 7,684.08 million after the overlapping

revenue from wholesale and franchise is taken out. ⑪ This figure is calculated from the profits reported in the interim and annual reports of the company. The actual revenue before tax is approximately

RMB13.8 billion, -5.1% in revenue growth, with 39 self-owned stores and 0% growth.

China Power of Retailing 2015 83 Contact us

David Lung Managing Partner, Deloitte China Consumer Products and Retail Industry +86 10 8520 7118 [email protected]

Lydia Chen Director, Deloitte Research +86 21 6141 2778 [email protected]

Andrea Ding Manager, Deloitte Research +86 21 2316 6595

[email protected]

Selina Zhao Senior Manager, Deloitte China Consumer Business Industry +852 5508 6589 [email protected]

China Power of Retailing 2015 84

China Power of Retailing 2015 85

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