E-WOM is described as all informal communications directed at consumers through Internet-based technology related to the usage or characteristics of particular goods and services, or their sellers (Litvin, Goldsmith and Pan, 2008). In contrast with conventional WOM, e-WOM has unique characteristics. For instance, it often occurs in strangers or fellow consumers, and can be and can be anonymous (Goldsmith & Horowitz 2006; Sen & Lerman 2007). In this regard, people feel free to express opinions without identity disclosure (Goldsmith & Horowitz 2006). INTRODUCTION In a word dominated by social media, the diffusion of e-WOM is undoubtedly speeding up. Plus the international trade prevailing, people can experience products from all over the world at home, and they typically collect both positive and negative e-WOM for domestic and foreign brands with the aim of comprehensively evaluating the brands and their products. It is worth mentioning that in reality consumers often adheres to consumer ethnocentrism (CE) to counter the significant effects of imports on domestic economies and defend against foreign products in local markets. So far, there has been relatively little research on the effect of e-WOM on CE. In our study, we employ social media to discover the impacts of e-WOM on CE with respect to domestic and foreign smart phone brands from the Chinese e-WOM receiver’s perspective. Simultaneously, we test consumer pride and prejudice toward mature industries in the home country. Drawing on survey data from 302 consumers, our study reveals several significant findings. First, positive e-WOM regarding local brands may enhance CE, whereas positive e-WOM regarding foreign brands may reduce CE. Second, Negative e-WOM may break the advantage of CE for domestic brand, which result in the dominance of foreign brand. Third, positive e-WOM may enhance brand equity for both domestic and foreign brands. By contrast, negative e-WOM has no significant influence on Chinese consumers’ attitude toward brand equity. Finally, CE has positive influence on brand equity for domestic brand but not effect on foreign brand. To our best of knowledge, our paper is the first to study the effect of e-WOM on CE, which enriches the relevant theory with regard to CE.

China has been the biggest factory in the world, most of products are marked “made in China”. With the rapid grows of consumption in China, it is also the biggest market. However, Chinese consumers with deep-rooted Confucian value system may different from Western countries (Ramasamy & Yeung, 2009). Do they still have strong consumer ethnocentrism? Or they can accept all the things they made but with the foreign brands? The power of WOM to influence customer attitude toward one brand is well known to all the marketing researchers. But the fast development of internet and social media network changed consumers’ behavior, word-of-mouth has acquired electronic WOM (e-WOM) as a new name (Goyette et al, 2010). Customer use E-WOM to evaluate product and make purchase decision. Ethnocentric consumers are against foreign brands as they believe that purchasing these brands will hurt domestic economy and brands, cause loss of jobs and increase the power of capitalist companies and dependency of poorer economies to them (Kaynak & Eksi, 2013). But customers are will to searching the better products. Such as Chinese mainland consumers hire purchase agent to shopping aboard. The purchase agent post information in the social media network as eWOM. This research wants to explore the young Chinese still have high ethnocentric tendency or not influenced by eWOM. If E-WOM can be a marketing method to reduce the ethnocentrism when foreign brands entry a new country. And also the domestic brands can use E-WOM to enhance ethnocentrism to against foreign brands. In this research, study 1 tests positive E-WOM or negative E-WOM to test if it can enhance Chinese consumers’ ethnocentrism or reduce their ethnocentrism for their own country products. This research also tests if consumer ethnocentrism can influence on brand equity and purchase intention. Based on the literature review, researchers establish concept model was shown in Table 1. This study uses SPSS and AMOS to analysis the sample. Based on the results this research gives suggestions to both academic and practice.

With the rapid development of science and technology, big data has been applied in many fields and has brought commercial revolution[1]. The scientific community generally regards big data as "massive data + complex types of data". Commercial applications are more concerned about big data as an analytical (prediction) method and focus on the potential commercialization of analysis results. All walks of life will produce large amounts of data every day. The transition of data-scale brings huge commercial value, which will certainly bring the innovation of business model[2]. Particularly in the internet and other emerging industries, because they get data more convenient and fast. Like Amason, Facebook, Google etc, they use analysis of big data to innovate their business model for maximizing their profits[3], actually business model refers to "an enterprise’s profitable operation mode plus ways to make money"[4]. So the effectiveness of business model innovation of big data on emerging industries has been remarkable. But the impact of big data on traditional industries is still in the exploratory stage. Traditional industry mainly refers to the labor intensive, manufacturing oriented industries, including the traditional commerce and service industry[5]. Learning from the experience of big data on business model innovation of emerging industries, traditional industries can use big data to subvert the business model and accelerate the transformation and upgrading.

Many software enterprises prefer to use usual entrepreneurial approaches and make detailed business plans, which cost them a lot of time and resources. In the highly uncertain environment, the above practice lead to fail at business or entrepreneurship. To avoid the undesirable feature, software enterprises should adopt lean start-up method. The core idea of lean start-up method is to put in a minimalist prototype on the market, and fast iterative product on the basis of customer feedback (Ries, 2011). Because customers are introduced to the products or service iterative innovation process, the enterprise can meet the needs of the market better and grow up rapidly. Meanwhile, the enterprise can find a suitable business model to achieve efficient operation or reduce the risk of entrepreneurship (Maurya, 2013). Combining case study and theoretical deduction, this paper will show a process for software enterprise using lean start-up method. Firstly, based on literature reviews, the paper will sum up the basic logic of lean start-up and specifically expatiate the five-step model for software enterprises which is “idea generation-customer validation-prototype creation-customer feedback-product iteration”. Secondly, this paper will give a lean start-up process for software enterprises. In the process, the first step is drawing a business model canvas rather than a detailed business plan, it may include nine blocks which are key partners, key activities, key resources, value propositions, customer relationships, channels, customer segments, cost structure and revenue streams, each block has a series of hypotheses (Blank, 2013). The second step is adopting the customer development method to test these hypotheses and adjust irrational hypotheses to satisfy customers’ requirements, this step is referred to as validated learning, with the aim of setting up a continuous customer feedback channel and achieving long-term sustainable development. The third step is adopting agile development to build minimum viable product and iterative the product according to customer feedback quickly, in order to reduce waste and save resources. It is essential for lean start-up to use a smaller, faster iterative process to verify the idea (Ries, 2011). Thirdly, this paper will use several typical cases of software enterprises to verify this lean start-up process. Finally, put forward the general rule of lean management so that it can provide reference for the software enterprises.