All posts by 359928DJ

Online commerce and new retail: A discussion of the emergence of social commerce and service commerce in China

“New retail” is the most searched word started form 2017 but showing a decreasing trend in the recent two months. Momentum is slowing down on the concept of new retail instead, people started to chase the other popular concept (e.g. autonomous retail). However, the believers argue that the transformation of retail industry will occur in the near future. To discuss new retail, we need to clarify some concept in advance.

What is new retail?

The traditional retail experienced several transition phase, namely real-estate integration, supply chain optimization and brand recognition under the interruption of online retail. However, the online retail also reached its maturity state with pure visit volume-based business model. “New retail” is the concept generated under the pressure of the two mentioned points. If we want to define new retail in one sentence, it is the integration of online, offline, technological, data, logistics across the single value chain. As Deborah Weinswig commented, Jack Ma, the founder and chairman of Alibaba believed that this is very much how next-generation commerce will look globally, with large retailers and niche category specialists leveraging technology to provide an integrated service with the consumer at its core.

Retailing_Reinvented_20161118_v2How Alibaba developed the new retail business model?

  • Data-driven mass personalization: Multi-dimensional and large volume customer data reserve helped Alibaba on a higher starting point in the development process. As a consumer of the retail store, I experience a recognizable difference since 2016. recommender system understands me better than myself. com is focusing user activity, engagement and duration of the shopping experience on top of the Gross Merchandise Volume (GMV).
  • The emergence of multichannel and multidimensional competition: Foundation by the mobile payment, the user can be reached both online and offline in almost all shopping circumstances. In addition, Alibaba expanded its territory to many other industries such as finance, entertainment, local service, etc. As such, the company covered the touch point with their customer in a multidimensional way, increased the penetration rate of the brand appearance and ultimately enforced the competitive advantage in the retail industry.
  • Investment in logistic and back-end system: Alibaba is contribution large portion of resources in optimizing the logistic management capability and upgrading back-end system to improve customer experience and diminishing cost at the same time.


As already mentioned in the post “beyond Omnichannel: Alibaba’s “new retail” strategy”, HEMA is the pioneer in the “New Retail” industry. Nevertheless, you can also see that the upfront capital investment for offline store opening is huge. The advantages leading to the economics of scale and capital accumulation is not easy to imitate for start-up companies.

How can START-UPs understand the “New Retail”?

Product (consumer products)

  • Logistics: Traditional furniture industry have a much-dispersed range of brands and products which have no quality standardization in China which makes price comparison almost impossible. For example[1], it partnered with reliable suppliers, optimized logistics and filtered out high cost-quality ratio product.
  • Source of supply: International e-commerce provided differentiated product compare to local suppliers to the consumers no matter import or export goods. RED[2] helped their consumer to explore and purchase product all around the world. On the other side, JollyChic[3] brings Chinese product to the world.

Environment (shopping environment, circumstances, and channel)

Traditional e-commerce is mainly based on the visit volume. The concerns are: “How to purchase visit volume at a low price and sell it at a high price”; “How to convert visit volume into real cash?”

Consumer (target market)

The key is to personalize the shopping experience in order to lock-in the purchasing power.


Look back at 2017, the e-commerce companies in China did many tests. There are also trends emerging such as social commerce, subscription-based business model, multidimensional shopping experience, and personalization. The social commerce business model and service commerce business model is particularly interesting to discuss.

Social commerce

As we discussed in the lecture, proximity influence dominant population influence when proximity influence exists in theory.[4]Word of mouth is the main driver for the emergence of the social commerce business model because it solved three problems for the e-commerce companies: Trust, natural, cheap.

Compare to the social commerce that is crazily popular on Wechat, Facebook already implemented social commerce on their platform but with the less successful story. Wechat compares to Facebook has a unique advantage. Wechat Group, Friends circle, Mini-program covers the entire sight and time of the consumers. Unlike Facebook that pushes customized display advertising to the customer, on Wechat platform the e-commerce store can advertise the product through all kinds of ways. If a customer refused to buy the product, the store could engage themselves in Wechat group. If consumer left the Wechat group, they still have to look at their Friend circle. Even they blocked the Friend circle, there are Mini-programs (which contain gamification concept for advertising). Thus, the consumer will be informed about the product all the time if they still use Wechat.


Service commerce

  • Membership-based model

E-commerce companies will provide a special premium for the members of the company. Amazon Prime is the most successful and well-known example of the membership-based model. Mimic the business model from Prime and implement it in Chinese e-commerce industry is not fully applicable because the companies should provide more localized benefit to their consumer. But figuring out the irresistible, unneglectable benefit for the consumer which trigger them to spread good words is still a long way to go.

  • Subscription-based model

The company can facilitate the consumers to grow a habit, increase the purchase frequency and lock-in purchasing power through a subscription-based model. For example, the flower subscription company facilitate the consumer to grow a habit of having fresh flower around them. Originally, the flower is a low purchasing frequency product. However, if a consumer subscribes weekly delivery of flowers, the purchasing is becoming more predictable with a higher frequency.


In general, social commerce and service commerce collect more customer data by engaging them in a high frequency that allows them to customize shopping experience better. New consumer, new market, new product. Companies can deliver their product and service in a new way. I believe that there will be an opportunity for “New Retail” in both online and offline.






[1] NetEase, Inc. (NASDAQ: NTES) is a leading internet technology company in China. Dedicated to providing online services centered around content, community, communication and commerce, NetEase develops and operates some of China’s most popular PC-client and mobile games, e-commerce businesses, advertising services and e-mail services. In partnership with Blizzard Entertainment, Mojang AB (a Microsoft subsidiary) and other global game developers, NetEase also operates some of the most popular international online games in China.

[2] Red provides its users with a platform to learn about and share shopping tips, deals, and experiences from their trips abroad. Users can browse through lists of the most popular brands for a category, and through products on brands’ exclusive pages. They can share pictures of products they have purchased, displaying them in a Pinterest-like interface with commenting and liking features.

[3] has a strong bond with industry insiders and collaborates intensively with main stream. We offer the latest fashion ingredients for those interested; We are a partner with dozens of reputable import & export companies, warehousing & logistics companies and after sales service provider from around the world. []

[4] Dewan, S., Ho, Y.-J. (. & Ramaprasad, J., 2017. Popularity or Proximity: Characterizing the Nature of Social Influence in an Online Music Community. Information Systems Research, 28(1), pp. 117-136.


Personalization or Standardization – A review of “Customers do not always prefer personalized products: The role of personalized options range in personalization”

Nowadays firms have increasingly adopted personalization strategy to provide customers with the option to choose on important feature parameters at the price similar to the standardized products. For example, Dell is well known for its success in mass customization. (Randall, et al., 2005) Subway is also a kind of customization and received huge success. (Choi & LEE, 2015) However, the academic defines the personalization in a different way. It has been suggested as a revolutionary approach to market segmentation. The company now treat the individual customer as individual segments by satisfying their very specific need. The strategy can boost sales and in such bring competitive advantage to the company.

However, it is not necessarily always true for every company. There are many attributes can influence the attractiveness of personalization option, for example, price premium, effort and monitoring quality. If we take a closer look in the effect of effort that the customer needs to take in the personalization process, we can find that the more complex the personalized process is, the less the customer will likely to personalize the item. (Choi & LEE, 2015) Especially the company failed to convey information to the different type of customer. Just like the example of Dell, the inexperienced user cannot tell the meaning of “Memory”. (Randall, et al., 2005) Some of those customers just decided not to make the choice because the complexity exceeds the optimal level.  The product utility that consumer could get through personalization is not strong enough to cover the inconvenience.

This research argues that the customers prefer standard products over the personalized product when the range of personalization is perceived as excessive. The customer is more likely to select standard products over personalized alternatives when faced with inordinately complex decision-making. In order to test the pattern of consumer responses regarding the personalized product and the standardized product, the author decided to use the attitude of customers towards product and the purchase intention as the key factor.

H3: Customers will demonstrate a more positive attitude for standard products over personalized products with a higher level of personalizing options beyond a customer-perceived optimal point.

H4: the customer will demonstrate a higher purchase intention for standard products over personalized products with a higher level of personalizing options beyond a customer-perceived optimal point.

The hypothesis is tested by using stimulation experiment. There are 195 undergraduate students in Korea are recruited. They have been randomly assigned to one of the seven sub-group according to the extent of personalization options. The basic setting is the standardized product, and the other six have the different level of personalization in an ordinal ranking. The incremental increase in the personalization level allows the author to compare between groups and examine the relationship between personalization level and customer response.

The result shows that the customer product attitude shows an inverted U shape as the number of personalizing options increased. This is also the case for the other factor, purchase intention, as the number of personalization option increase, the purchase intention increase until the optimal level and then decrease. (Figure 1 and Figure 2)

The author then conducted an ANOVA analysis on the product attitude and purchase intention respectively for the standardized product and the personalized product (with most extensive personalization options). The results support the Hypothesis 3 while the result of Hypothesis 4 was not statistically significant. To test the mechanism of complexity as a mediator, they also test the hypothesis based on Baron and Kenny (1986). The perceived complexity mediated the effect of product type on product attitude. The mediation tests show that perceived complexity is the influence factor for the preference over standard products and the personalized products when comparing the standard product with the overwhelming personalization options.

The logic of this research is very easy to follow, they successfully demonstrated the importance of setting an appropriate level of personalization to companies that wanted to implement the personalization business model. However, the question arises when evaluating the regression model. Has the author controlled enough factors to isolate the effect of independent variables on the dependent variable? For example, if we look at the product nature, the result doesn’t necessarily apply to the experienced user with the clear expected product. They will likely to appreciate the extensive personalization options to fine tune the product to maximize the fit with their expectation. In addition, the author used to watch as the testing product. It is a relatively straightforward functional product. The personalization option does not include any configuration regarding the function itself but only the design. Will the research show a different result if we test it on Dell computer? The answer is unknown. If we look at a further research in the background of web companies. There is a phenomenon called “filter bubble”. It suggests that with those filter bubbles people are restricted to the filter options and shapes our view to the worldview.  If you are interested, please have a look at the following video.


Choi, J.-E. & LEE, D.-H., 2015. Customers do not always prefer personalized products: The role of personalized options range in personalization. International Academy of Marketing Studies Journal, 19(2).

Randall, T., Terwiesch, C. & Ulrich, K. T., 2005. Principles for User Design of Customized Products. California Management Review, 47(4), pp. 68-85.