Yitang Zeng

Chunhui Tan

Enterprise's Online Trust Crisis Management: a Life Cycle View

Keywords: online trust, online trust crisis, online trust crisis management. 1

Online trust is the vital mechanism for the development of ecommerce, and the significance of online trust has become a consensus. Undeniably, an obscure message may be magnified indefinitely and evolve into the enterprise's online trust crisis, which will affect the image of the enterprise, threaten the survival and development of the enterprise, or make the enterprise into a doomed situation that can never be recovered. We study the development phases of enterprise's online trust crisis life cycle, and then put forward framework of enterprise's online trust crisis management strategies based on the characteristics of online trust crisis life cycle, which may be provide some theoretical supports for enterprise's online trust crisis management.

Introduction 1.1 Background

After more than ten years of fast development, the Internet has brought reforms on people's life styles, modes of information transmission, enterprise's managing ways, and ideas of government administration. According to the "Internet World Stats" [START_REF]Internet Users in the World Distribution By World Regions-2012 Q2[END_REF], by the end of June 2012, about 26% of the World's population has Internet access, which represents 566.4% more than in year 2000. Regions like North America and Europe are well above those figures, with 78.6% and 63.2% of the population having online access respectively. The "33th statistical report on the Internet Development in China" [2] showed that the number of Chinese Internet users have reached 618 million, and Internet penetration rate has raised to 39.9% by the end of 2013.The scale of e-commerce has grown substantially over the past years. Global business-toconsumer e-commerce sales will pass the 1 trillion euro mark by 2013, according to a new report by the Interactive Media in Retail Group (IMRG) [START_REF]Global e-commerce sales will top $1.25 trillion by 2013[END_REF], a U.K. online retail trade organization. The e-commerce of China has a rapid growing; the total value of E-commerce in China was 5.6 trillion Yuan (about 675 million euro) in the first three quarters of 2012, which grew 25% from the same time of 2011 [4].

Trust is the currency of all commerce. In traditional commerce, the trust is based such things as societal laws and customs, and on the intuition people tend to develop about each other during interpersonal interactions. As for Internet-based commerce, owing to lacking of the personal relationship, trust becomes even more important. Whether for the traditional entity enterprises, or for the emerging virtual enterprises, online trust is the vital mechanism for the development of e-commerce, and the significance of online trust has become a consensus [START_REF] Liu | Beyond concern: a privacy-trust-behavioral intention model of electronic commerce[END_REF][START_REF] Pavlou | Understanding and mitigating uncertainty in online exchange relationships: a principal-agent perspective[END_REF][START_REF] Luo | Examining multi-dimensional trust and multifaceted risk in initial acceptance of emerging technologies: an empirical study of mobile banking services[END_REF][START_REF] Mesch | Is online trust and trust in social teams associated with online disclosure of identifiable information online?[END_REF]. Online trust can affect consumers' intentions to revisit the site and to recommend the site to others. Online trust plays a key role in creating satisfied and expected outcomes in online transaction. Online Trust has been found to be a significant antecedent to customer's willingness to transact with an e-vendor. Online trust serves to mitigate the perceptions of risk, uncertainty and vulnerability that are associated with the disclosure of personal and identifiable information.

The Internet has proven to be a powerful and very popular vehicle for distributing information to millions of individuals. If there were any negative information about one company in the Internet, this information might diffuse broadly in several hours or even in several seconds. The spread of Internet public opinions often plays the role of the catalyst of corporate crisis and the accelerator of dissemination. An obscure message may be magnified indefinitely and evolve into the enterprise's online trust crisis. Like viruses, online trust crises can be mutated, acquiring new and dangerous forms in, for example, social forums like Facebook, or video distribution sites such as YouTube. Once the enterprise's online trust crisis has be happened, the credibility and reputation of the enterprise will be heavily injured, the word-of-mouth and image of the enterprise will be heavily damaged, and the survival and development of the enterprise will be threaten, or make the enterprise into a doomed situation that can never be recovered. Either in China or in other countries, a lot of famous enterprises have met the online trust crises. Some of them fall in trouble and recovered from the crisis through a very long period. However, some of them were not so lucky and directly ended the corporate life cycle.

The objective of this paper is to address the following research questions:

(1) What is the life cycle of online trust crisis diffusion?

(2) What countermeasures can be used in the enterprise' online trust crisis management in the life cycle of enterprise' online trust crisis?

Hopefully, this study will help enterprises to gain some useful suggestions to manage online trust crises.

Define online trust and online trust crisis

Trust as a social phenomenon has been studied in various disciplines and the notion of trust has been examined under various contexts over the years. Many researchers have interpreted it and made a lot of contributions from the perspective of philosophy, psychology, management, and marketing [START_REF] Mayer | An integrative model of organizational trust[END_REF][START_REF] Bachmann | Trust, Power and Control in Transorganizational Relations[END_REF][START_REF] Devosk | Conflicts among human values and trust in institutions[END_REF][START_REF] Alesina | Who trusts others?[END_REF]. Among definitions, the generalized definition of trust by Rousseau et al. [START_REF] Rousseau | Not so different after all: a cross-discipline view of trust[END_REF] is broadly accepted. In their opinion, "trust is a psychological state comprising the intention to accept vulnerability based upon positive expectations of the intentions or behavior of another"(p.395). Based on the study of trust, researchers widened the definition of trust and applied it to online trust upon Rousseau's definition, Bart et al. [START_REF] Beldad | How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust[END_REF] emphasize that "online trust includes consumer perceptions of how the site would deliver on expectations, how believable the site's information is, and how much confidence the site commands" (p.140). Corritore et al. [START_REF] Midha | Impact of consumer empowerment on online trust: An examination across genders[END_REF] define online trust as "an attitude of confident expectation in an online situation of risk that one's vulnerabilities will not be exploited" (p.740). In our opinion, online trust is a psychological affirmation of common expectations in an online environment of uncertainty that is caused by online principal parts, based on their wishes, participant's characteristics and the environmental factors, e.g. system, technology and third-party certification.

What is a crisis? The viewpoint of Seeger et al. [START_REF] Seeger | Communication, organization and crisis[END_REF] is representative for an organizational setting. They define that crises are "the specific, unexpected, and nonroutine events or series of events that create high levels of uncertainty and threat or perceived threat to an organization's high priority goals" (p.235).

Based on the above notions, the enterprise's online trust crisis means that the related information about the irresponsible behaviors or negative events of the enterprise were published, disseminated and diffused via Internet, which will decline dramatically the degree of trust of consumers, suppliers, distributors, social public, government departments, thus create high levels of uncertainty and threat or perceived threat to one enterprise.

Review of Literature

The topic for this study cuts across more than one substantive area in the review of the literature. However, its framework is premised on a strong thematic organization based on the online trust and crisis management.

Online trust

The literature on online trust is extensive and multi-faceted and online trust has been extensively studied.

Luo [START_REF] Luo | Trust production and privacy concerns on the Internet A framework based on relationship marketing and social[END_REF] examined several key mechanisms that can help increase customers' trust of e-commerce and decrease privacy concerns. These mechanisms include characteristic-based (e.g., community), transaction process-based (e.g., repeated purchases), and institution-based trust production (e.g., digital certificate). Wang and Emurian [START_REF] Wang | An overview of online trust: concepts, elements, and implications[END_REF] pointed out that online trust is a difficult task to accomplish because it requires the establishment of trusting relationships in the online world. The study of Gefen et al. [START_REF] Gefen | A research agenda for trust in online environments[END_REF] showed that trust in online environments is predicated on beliefs in the trustworthiness of a trustee; trustworthiness is composed of three distinct dimensions--integrity, ability, and benevolence. Integrity is the belief that the online merchant adheres to stated rules or keeps promises. Ability is the belief that the online merchant has the skills and competence to provide good quality products and services. Benevolence is the belief that the online merchant wants to do good to the customer without regard to making a sale. Beldad et al. [START_REF] Beldad | How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust[END_REF] provided an overview of the available research into the antecedents of trust in both commercial and noncommercial online transactions and services. There are three clusters of antecedents: customer/client-based, website-based, and company/organization-based antecedents. Benedicktus [START_REF] Benedicktus | The effects of 3rd party consensus information on service expectations and online trust[END_REF] offered that online trust beliefs vary positively with consensus ratings and trust is higher when ratings trends increase rather than decrease. Bock et al. [START_REF] Bock | The progression of online trust in the multi-channel retailer context and the role of product uncertainty[END_REF] evaluated the effects of antecedents of online trust in the context of multi-channel retailers at different phases, taking into consideration the moderating effects of product types. With increases in product uncertainty, the effects of word-of-mouth, offline trust, and efficacy of sanctions on online trust are greater for experience products than for search products. Kim and Ahmad [START_REF] Kim | Trust, distrust and lack of confidence of users in online social media-sharing communities[END_REF] offered a framework for modeling the trustworthiness between a content consumer and a content provider in online social media-sharing communities where users have interacted with each other as either a content consumer or a content provider.

Crisis management

Many researchers have discussed crisis management.

Heath [START_REF] Heath | Dealing with the complete crisis-the crisis management shell structure[END_REF] introduced an integrated management approach in the Crisis Management Shell Structure, which includes decision component, advisory component, operation component and information component, in terms of what the components units do, why they do these activities, and who is involved. Mak et al. [START_REF] Mak | Building online crisis management support using workflow systems[END_REF] presented a novel application of workflow technology to coordinate and disseminate tasks and related information for Crisis Management Support Systems (CMSS). Their research results indicated that the ability of workflow technology to coordinate, monitor, organize and distribute specific tasks and the associated required information in a timely and efficient manner appears to make it an ideal tool for strategic crisis management. Murray and Foster [START_REF] Murray | Crisis Resource Management Among Strangers: Principles of Organizing a Multidisciplinary Group for Crisis Resource Management[END_REF] provided the principles of organizing a multidisciplinary group for crisis resource management. Ryzenko and Smolarkiewicz [START_REF] Ryzenko | Space-enabled information environment for crisis management. Scenario-based analysis and evaluation in an operational environment[END_REF] presented analysis of usefulness of space applications in crisis management activities carried out on the national level. According to them, the key to successful crisis management lays in understanding operational needs; integration into common information environment; and standardization of information exchange. The research of Pearson and Sommer [START_REF] Christine | Infusing creativity into crisis management: An essential approach today[END_REF] showed that through crisis management planning and preparation, organizational leaders do what they can to make timely decisions based on the best facts that they can gather. Speakman and Sharpley [START_REF] Speakman | A chaos theory perspective on destination crisis management: Evidence from Mexico[END_REF] proposed an alternative, chaos theory-based approach to crisis management. The elements of chaos theory include edge of chaos, the butterfly effect, bifurcation and cosmology, selforganization, strange attractors and the lock-in effect. Sardouk et al. [START_REF] Sardouk | Crisis management using MAS-based wireless sensor networks[END_REF] proposed a crisis management approach based on wireless sensor networks, which overcomes the problems encountered by the base stations and insures relevant, rich and real-time information about events.

From the previous survey, none of these previous articles focused on the enterprise online trust crisis management. Online trust crisis managing strategies have been substantially altered comparing with the traditional crisis management.

The Life Cycle Model of Enterprise's Online Trust Crisis

There is a life cycle for the development of everything in the world. The life cycle concept is originally used to describe a period of one generation of organism in a biological system [START_REF] Chou | Information systems outsourcing life cycle and risks analysis[END_REF]. Since 1960s the theory of life cycle was raised, the concept of life cycle is applied widely, especially in the fields of politics, economy, environment, technology, and society. In essence, the term life cycle can be popularly understood as a period "from Cradle to Grave", or from its birth to its end. This also applies to the enterprise's online trust crisis. Similarly, the theory of life cycle can be used to describe the stage of development of enterprise's online trust crisis.

Based on the change of individuals' attention, we investigate the stage of development of enterprise's online trust crisis from the perspective of time series, then the whole online trust crisis life cycle can be divided into four phases (see Figure 1): incubation phase, outbreak phase, diffusion phase and decline phase.

Figure 1. The life cycle of online trust crisis

There are different characteristics and symptoms in the different stages of enterprise's online trust crisis life cycle. And these characteristics play an important role in enterprise's online trust crisis management. The characteristics of each stage of enterprise's online trust crisis life cycle are shown in Table 1.

Incubation phase

The incubation phase includes the period from the appearing of signs of enterprise's online trust crisis to the perceived loss caused by online trust crisis. In this phase, the online trust crisis has not yet broken out; the degree of attention is low. The number of individuals involved is little, network issues are dispersed, the information of online trust crisis is relatively hidden, and the sphere of influence of online trust crisis is small. However, the signs of online trust crisis begin to appear, for example, the sporadic appearance of report on the enterprise adverse events, the sporadic negative comments against the enterprise. If these signs could be taken seriously and handled properly, then the online trust crisis will be nipped in the bud or the damages will minimize to a low degree.

Outbreak phase

The outbreak of enterprise's online trust crisis is triggered with potential predisposing factors. There are two sources for enterprise's online trust crisis: one is internal incentive; the other is external incentive [START_REF] Tan | Research on the Discrimination of Enterprise Online Trust Crisis Based on "Twice Evaluation[END_REF]. As internal incentive, the corporate itself produces negative events, such as error of strategies, unfavorable events of functions or deviation of implementation. These will cause the enterprise's online trust crisis, when these negative events are communicated and diffused with Internet news, BBS, blogs and podcasts, RSSs, SNSs, IM, or micro-blogs, just to give some examples of potential channels for the bad news. As external incentive, the negative events usually relate with production and operation. The trust crisis event of the enterprise is reported by Internet news media. The unfavorable remarks on the enterprise are then further released by individuals with social media. The evaluations and reports on the enterprise's crises may also published by other third parties. The adverse information on the enterprise might be published maliciously by competitors. These all will lead to the enterprise's online trust crisis, which is communicated and diffused with network channels.

Diffusion phase

During this period, the network becomes a "catalyst" of online trust crisis. The publicity of the crisis events is enlarged quickly in a short time, which is catalyzed and fermented through network environment, and attracts more individuals' concerns and participations. The number of individuals involved increase gradually, and the degree of attention increases sustainably, network medias change from niche to mass, the strong medias intervene actively, and negative information disseminating channels are formed rapidly, thus the enterprise sinks in the whirlpool of trust crises. Network public opinions are complicated, after the massive outbreak of online trust crisis, there will be "joint" effects in many fields, and increasingly more related things are involved widely. The enterprise's online trust crisis is most difficult to control in this phase.

Decline phase

Finally the enterprise's online trust crisis enters the decline phase, mainly because of two reasons. One is that the individuals' views are shifted by new crisis events of other organizations. The other is that the online trust crisis is treated effectively. The cyber hotspot sustains for a period of time, if new events emerge and new stimulus generated, a lot of individuals will automatically shift to new network issues, and they will pay decreasingly attentions to the old network hotspot, then it will be cooled, faded and fallen. When the enterprise's online trust crisis is treated effectively, the crisis will disappear gradually and the enterprise will enter into a new development stage. However, if the treatment was invalid, the residual factors of the online trust crisis will ferment and the online trust crisis will re-enter into a new life cycle.

The Framework of Enterprise's Online Trust Crisis Management Strategies

There are different characteristics in different stage of the enterprise's online trust crisis life cycle, and these characteristics determine the countermeasures used in the online trust crisis management. It is vital to find the countermeasures in accordance with the online trust crisis life cycle. The fishbone diagrams are causal diagrams created by Ishikawa [START_REF] Kaoru | Guide to Quality Control, Asian Productivity Organization[END_REF] in the 1960s. These show the causes of a specific event and each cause or reason for imperfection is a source of variation. A fish bone diagram is a common tool used for a cause and effect analysis, and it immediately sorts ideas into useful categories [START_REF] Nancy | Tague's The Quality Toolbox[END_REF]. Nowadays, the fishbone diagram is widely used in the field of management.

According to the characteristics of each phase of online trust crisis and the basic principles of crisis management, drawing lessons from the idea of fishbone diagram, we construct the framework of enterprise's online trust crisis management strategies, as shown in Figure 2. The framework can provide references on the enterprise's online trust crisis management decision-making. The Strategies of Enterprise's Online Trust Crisis Management

The management in Incubation phase

There are some signals to indicate the possibility of the online trust crisis though the great trust crisis events cannot yet happen during the incubation phase. At this time, the enterprise should pay more attention to the prevention of online trust crisis. If all kind of incentives which may induce the enterprise's online trust crisis could be monitored timely and the related signals could be analyzed carefully and forewarned effectively, then it could be possible to avoid the ordinary events suddenly upgrading to the burst of online trust crisis. The countermeasures in the incubation phase are discussed in more detail below.

Drawing up crisis management plan

The enterprise needs to take the online trust crisis management into the overall work of enterprise's crisis management, and draw up the online trust crisis management plan based on the principles of integrity, predictability, initiative, operability and timeliness. It is crucial to make a plan for online trust crisis management, because it can effectively prevent the occurrence of some online trust crisis events, and avoid expanding the trust crisis as far as possible after the trust crisis is really happening. This is just a precaution for crisis management. Apart from definite management budget and segmentation of management target, there are two key points in online trust crisis management plan: one is the construction of online trust crisis management information system; the other is the construction of online trust crisis management team. The online trust crisis management information system is a subsystem of enterprise information system, which has the functions of trust crisis information collection, collation, analysis, identification, transmission, feedback, communication, publishing, recovery and assessment. The online trust crisis management team should establish the managing mechanism with centralized command and division of labor and cooperation. The online trust crisis management team should form strong professional personnel. There are some key functions of online trust crisis management team. Firstly, it should coordinate the relationships among internal departments, the enterprise and news media, and the enterprise and the social public. Secondly, it should collect, analyze, predict and evaluate various crisisrelated information. Lastly, it should report the information to the enterprise decisionmaking setup.

Strengthening information monitoring

Although the occurrence of enterprise's online trust crisis may be sudden for unknown reasons with a certain degree of randomness, yet some information, views and attitudes will be displayed in network channels from the appearing of initial signals to the occurrence of online trust crisis. So the enterprise's online trust crisis can be monitored [START_REF] Tan | Research on the Model of Enterprise's Online Trust Crisis Prevention Based on Ontology and Web Mining[END_REF]. In order to get the signals of the enterprise's online trust crisis, the enterprise should monitor the external information related with the survival of the enterprise. The external information includes politics information, economy information, policy information, science and technology information, finance information, market information, competitor information, supply and demand information, and consumer information. Additionally the enterprise should monitor the internal sensitive causes, which result from corporate mismanagement, business decision-making errors, the problems of product and service quality, financial crisis, the poor quality of staff, and the error of PR strategies.

Reinforcing signal analyzing

The analysis of cyber information monitored is a process to find problems and solve problems. After the collection of data, the analyzing process of information arrangement, identification, filtering and evaluation should be carried out. There are differences in the methods and focus of signals processing for different information communication platforms. As for network news data, the main core elements of the original should be maintained as far as possible, such as news title, source, release time, content, click number, reviewer, comment content and the comment number. As for BBS, blog, podcast, RSS, SNS, IM data and other social media, the original element and diffusion effects should be preserved as far as possible and formed the formatting information, such as the title of the post, the spokesman, the release time and content, content and number of replies, and so on. The abnormal information should be classified and analyzed timely, the hot spots, sensitive spots and dangerous spots, which may possibly cause online trust crisis, should be researched. The successful identification of potential and possible threats will lay the foundation for the enterprise's online trust crisis management.

Timely crisis forewarning

All signals analyzed and processed should be timely submitted to the crisis management team. The crisis management team should evaluate professionally the signals to determine whether the crisis forewarning is need. After an action decision, the online trust crisis forewarning should be realized automatically with the information technologies as one module of the enterprise information system. The forewarning indicators are built according to parameters such as the news source, news authority, comment number, release time and intensive degree, the viewpoint and orientation of the article or post, the degree of concern, and so on. This module owns the functions of semantic analysis, statistical analysis, comprehensive analysis and feature extraction by making full use of natural language processing, viewpoint mining, artificial intelligence, and visualization technology. In this way, the signals can be checked if they were in a normal range, once beyond a particular scope, the alarm is submitted to the online trust crisis management.

The management in outbreak phase

This stage is especially critical for the enterprise's online trust crisis management. If the enterprise's online trust crisis could not be disposed improperly, the consequences of the trust crisis events will be in a deteriorating direction, the "heat" of online trust crisis will increase, and more individuals will participate in the discussion and communication. Thus, cyber will become the "blower" for the enterprise's online trust crisis, and the online trust crisis will be worsening. Following actions are needed.

Promptly implementing the crisis management plan

Once the online trust crisis is outbreaking, the enterprise should confirm rapidly and timely the crisis, find the source of crisis, determine the potentially affected the public, and implement promptly the online trust crisis management plan, assembling all kinds of resource to control the influence power of online trust crisis within a smaller range as far as possible. According to different crisis forms, the enterprise online trust management team should format the corresponding crisis control groups to provide effective organizational support. In addition, the enterprise online trust management team should strengthen the cooperation with government agencies, NGOs and media, and rely on the opinion leaders and the public to reduce the damage to a minimum.

Getting the support of opinion leader

Opinion leader is an active media user who interprets the meaning of media messages or content for lower-end media users [START_REF] Gnambs | Convergent and discriminant validity of opinion leader: Multitraitmultimethod analysis across measurement occasion and informant type[END_REF]. There is a lot of promoting by opinion leaders almost behind every network hot issue. In some events, the viewpoints of opinion leaders can play and unexpected role on the settlement, because as the person concerned in the event, the point of view of the enterprise is difficult to get fully recognized by individuals. Therefore, the enterprise should actively win the support of opinion leaders and make full use of the third-party persuading role of opinion leaders, encouraging opinion leaders to guide online speech through blogs, podcasts, SNS, RSS, and other social media. The opinion leaders should be the strong support for the enterprise and the external opinion. At the same time, the enterprise should cultivate actively its own "opinion leaders" to form a positive guiding force in the "new opinion stratum".

Timely conveying positive message

Winning the time is equal to winning the image. There may not be enough reliable information at the onset of the crisis. In order to avoid information vacuum and rumors flying long, the enterprise must strive for controlling the situation in a short time and endeavor to communicate with public in the first time, conveying positive messages, indicating attitudes, informing of the activities being adopted. Then the public will feel the enterprise's responsibility consciousness and public philosophy, and they will be in favor of the enterprise psychologically. The key point to keep the initiative in information release is that the enterprise itself should be the first hand information release source and provide the necessary background information to media and public as much as possible, not giving too much playing space to media. The enterprise should inform news media about the crisis basic facts and the management countermeasures in the shortest period of time, and clarify the stance and attitude to get the trust and support of the media and lead actively public opinions. In such a way, the enterprise will quickly control the situation by not giving up any rights of speech.

The management in diffusion phase

Due to the openness, timeliness and interactivity of Web 2.0, there are cascading effects during the diffusion phase of online trust crisis. It is difficult to manage online trust crisis in the diffusion phase. In addition to adhering continuously the countermeasures mentioned above, the enterprise should also do the following works.

Effectively integrating media's power

The enterprise online trust crisis management team should actively coordinate the relationship with the mainstream traditional media and online media. The enterprise can communicate and dialogue with individuals frankly in proper communicating atmosphere with unblocked information channels. During the communication, the positive interaction between the enterprise and the society will be formed, and the chaos of social public caused with blocking messages and uniformed information will be avoided. It is very important to ensure the rights of speech of individuals, which can overcome the desire for fear or revenge of public to reduce the instability factors.

In this way, the public's resentment on the crisis event can be led to the rational thinking of the nature and solutions of the event. And then the attitudes and behaviors of individuals will be advantageous to resolve online trust crisis and reduce the negative influence and loss.

Sustainably release real information

The enterprise should release information sincerely, meet and maintain the public's right to know, winning opportunities for subsequent disposal of the trust crisis. The online trust crisis can be led and mediated in the direction of control by disclosing relevant information, and the social anxieties will be reduced. The enterprise can sustainably release real information and enhance the transparency of information through the enterprise's website, enterprise's news spokesman, hotlines, being a guest on network media and social media.

Strengthening set-up of network issues

The primacy effect [START_REF] Jones | Pattern of performance and ability attribution: An unexpected primacy effect[END_REF], in psychology and sociology, is a cognitive bias that results in a subject recalling primary information presented better than information presented later on. In the network era, the energy of primacy effect increases in hundreds or thousands times in the process of network communication. It is an effective way to guide the cyber opinions by setting up the official network issue. When the online trust crisis is breaks out, the enterprise should try its best to set the related subjects or topics in the first time consciously. On one hand, the attentions of individuals will be directed to the special themes. On the other hand, the diffusion of online trust crisis will be decreased as much as possible. The enterprise can actively get the rights of speech and guide the development of network opinions by setting communicating topics initiatively, making the network discussion become more efficient, hierarchical, systematic and controllable.

Realizing personalized communication with individuals

In order to achieve the communicating goals in the situation of crisis, the target audience should be divided into several types and each type should adopt different communicating method and channel. The classification standards include the value, behavior habit, life style, education degree, racial, economic status, age, gender, and information selection habit of individual. Aiming at the personalized communication needs of each type of target audience, the enterprise should choose the proper transmission time, transmission channel, information content and expression forms based on satisfying the targeted communication. Of course, these all depend on information technologies.

Management in decline phase

Whatever the cause, when the enterprise's online trust enters into decline phase, the enterprise should carry out crisis evaluation, crisis debriefing and image remodeling.

Crisis evaluation

The crisis evaluation includes the evaluation of basic support, the evaluation of disposal process and the evaluation of settlement results. The evaluation of basic support looks for loopholes of online trust crisis monitoring, forewarning and management plan to make up the shortfalls. The evaluation of disposal process can help the enterprise to improve the online trust crisis management process and enhance the enterprise's ability to cope with the online trust crisis in the future. After the online crisis trust, the enterprise should track and mend continuously the settlement results, and think over the recovery measures. The evaluation of settlement results should be fed back to the online trust crisis management plan, perfecting the plan, and providing effective basis for the future online trust crisis.

Crisis debriefing

The crisis debriefing is an inevitably phase in online trust crisis management. The work of crisis debriefing is an important mechanism the enterprise tries its best to recover the cyber order to its normal state and prevent the germination of new online trust crisis. On one hand, if the enterprise really produced the trust events and had negative effects on social public, the enterprise should take responsibility and apologize actively and initiatively to get their understanding. On the other hand, if some organizations and persons violate laws, regulations or the network obligation and cause damages to the enterprise, the enterprise should actively investigate and pursue such organizations' or persons' legal liabilities.

Remodeling image

The destructiveness given by online trust crisis is mainly manifested in the deterioration of the enterprise's image. Thus, when the online trust crisis enters into the decline phase, the enterprise must try its best to reshape the corporate identity. The process of remodeling image is actually the process that the enterprise pursues self-improvement and constantly gets the public's recognition, understanding and support. On one hand, the enterprise should complete the internal works to truly provide high-quality products and service to society. On the other hand, the enterprise must maintain good relations with all kinds of social public, planning and implementing a serial of PR activities manifesting the brand reputation and corporate identity, product promotion, and public benefit activities reflected the enterprise's social responsibility.

Conclusions

With the rapid development of Internet and telecommunication network, the occurrences of online trust crises become increasingly more frequent. The negative influences and destructive effects caused by online trust crises are growing. We study the phases of enterprise's online trust crisis life cycle and put forward the frame of enterprise's online trust crisis management strategies based on the characteristics of online trust crisis in incubation phase, outbreak phase, diffusion phase and decline phase, which may provide some theoretical supports for enterprise's online trust crisis management. Crisis management is also called crisis communication management [4]. The emphasis of enterprise's online trust crisis management is to achieve and enhance communication with the public. Communication becomes the core of management in each stage of online trust crisis cycle. Of course, the enterprise's online trust crisis management requires a lot of manpower, material and financial resources, and thus it could be difficult to realize for micro and small enterprises (MSEs). Based on recent cases, Internet users pay more attention to the production and operation of wellknown enterprises, and well-known enterprises have become the main body of the outbreak of online trust crisis. All well-known enterprises should attach importance to online trust crisis management.

Figure 2 .

 2 Figure 2. The fishbone diagram of enterprise's online trust crisis management strategies

Table 1 .

 1 The characteristics of each stage of enterprise's online trust crisis life cycle

	Phase	Degree of attention	Number of individuals involved	Degree of convergence on network issues	Network communicati on channels	Sphere of influence


Xuewen Gui
email: guixuewe@mail.ccnu.edu.cn

Xiaolan Wu

Song Liu

Insight into the Construction of Occupational Classification in E-Commerce in China

Keywords: e-commerce, occupational classification system, e-commerce industry

The great advances on e-commerce industry have tremendously promoted the development of Chinese economy and society. However, thus far, there has been a lack of a comprehensive occupational classification system of e-commerce in China, which has inhibited the further improvement of Chinese e-commerce industry. In this article, on the basis of current situations, we highlight the importance, summarize the relevant researches and learn excellent experience of constructing e-commerce occupational classification system, from China and overseas, and thus put forward the reasonable methods and contents of the construction of e-commerce classification system in China.

Introduction

The rapid development of Internet technology has facilitated the emergence of Chinese e-commerce era during the past two decades. As a new kind of economic style, e-commerce has attracted considerable attentions from all sectors of society in China because of its excellent abilities to enhance economic benefit and effectiveness of traditional business. Especially in recent years, e-commerce has been recognized as sunrise industry or green industry, and has become one of the most fashionable and promising industries. The statistics from China E-business Research Center has demonstrated that the total transaction amount in e-commerce industry in China has reached 10.2 trillion Yuan RMB ($1.63 trillion) in 2013 [START_REF]Report on Monitoring Data of Chinese E-Commerce Market[END_REF]; "The 12th Five-year Plan of E-Commerce Development" predicted that the total transaction amount of ecommerce in China would exceed 18 trillion Yuan RMB in 2015 [START_REF]The 12th Five-year Plan of E-Commerce Development[END_REF]. Meanwhile, according to the data provided by China E-business Research Center, there would be over 2 million employees engaging in e-commerce industry by the end of the fourth quarter of 2013 and e-commerce has brought over 1.5 million job chances for employees [START_REF]Report on Monitoring Data of Chinese E-Commerce Market[END_REF]. Obviously, e-commerce industry has huge influences on society and economy at present. However, thus far, there has been a lack of a comprehensive occupational classification system in China, which may lead to the poor understanding of the standards and requirements of e-commerce personnel training in universities, pose negative effects to training e-commerce professionals, and trigger the mismatch between demand and supply of e-commerce professionals. Thus it inhibits the further development of Chinese e-commerce industry. Therefore, it is highly desirable to construct a comprehensive occupational classification system, because it can provide reliable guidance for the training of e-commerce professionals, contribute to the construction of meliorating occupational classification system, and lay solid foundation for the construction and development of economy in China. This article is based on the current status of Chinese e-commerce occupational classification, sheds light on the excellent experience of the occupational classification from America and Canada as well as Chinese IT industry, subsequently demonstrates the principles and goals as well as the construction contents of e-commerce occupational classification system in China.

Research Background

Occupation and its classification

It is well known that occupation is defined as a social work with the goal of meeting material and spiritual needs by means of expertise and knowledge, in which human beings engage to gain income, achieve personal values, and realize social values as well as create wealth for society [START_REF] Li | Methodology and Functions of Occupational Stratification[END_REF]. Correspondingly, an accurate description of occupational classification then refers to that following certain scientific methods and standards, the various occupations are arranged and classified systematically to form a logical and ordered system [START_REF] Gui | Theory and Method on Effect Measure of E-commerce Promoting Economic Development: Relevant Theory and Method on Effect Measure of E-commerce Promoting Economic Development[END_REF]. Many advances on occupational classification have been achieved in various countries, which promotes the development of economy and society. For instance, Holland thought that occupations could be classified into six major categories, such as realistic, Investigative, artistic, social, enterprising, and conventional, and subcategories on the basis of the concept of personality types with the aid of Bayesian statistics and the Dictionary of Occupational Titles (DOT) [START_REF] Viernstein | The Extension of Holland's Occupational Classification to all Occupations in the Dictionary of Occupational Titles[END_REF]. Moreover, in 2010, the Office for National Statistics (ONS) published the second version of the occupational classification, which is revised every ten years in UK by collaborating with experts and consulting with users and producers of occupational statistics [START_REF] Elias | SOC2010: Revision of the Standard Occupational Classification[END_REF]. Obviously, these advances on the construction of occupational classification played positive effects on the continuous development of society.

E-commerce

Many previous reports have demonstrated that the concept of e-commerce could be defined from the following three aspects: in narrow sense, e-commerce belonged to a kind of business activity which focused on the exchange of goods and services on the basis of IT; in middle-level sense, e-commerce could be viewed as the electronization of business workflow in various industries, which was also called as e-business in-cluding a wide range of businesses and services, such as e-government, networking, the electronization of intra and inter-enterprise operating system [START_REF] Feng | Analysis on Basic Principles of Occupational Classification Standard in China[END_REF]; in broad sense, e-commerce was a new model of economic activity which conducted various businesses online [START_REF]Eleventh Five-year Plan on E-Commerce development[END_REF]. In general, e-commerce is a cross-discipline subject covering the fields of economy, management, information technology, and law, and is associated closely with other industries, such as manufacturing, service and public utilities ones, which requires high-quality talents with both solid professional knowledge and skilfully practical operation abilities [START_REF] Chen | Research on Cross-border E-commerce Talents Cultivating Pattern-Analysis based on Yiwu[END_REF]. Furthermore, the emergence of e-commerce was highly inspired by the development of IT, and both of them shared some similarities in the occupation characteristic and requirement, such as web transactions that includes advertising, buying, selling positions and the application of IT covers through almost the whole e-commerce industry. The great similarity between e-commerce and IT provides a strong indication that constructing occupational classification system in e-commerce can base on methods and principles of occupational classification of IT industry [START_REF] Elias | SOC2010: Revision of the Standard Occupational Classification[END_REF]. Obviously, in view of the above considerations and the highly developed feature of network technology at present, the relatively more suitable description of ecommerce should be conducted from the perspective of narrow sense. Therefore, this article attempts to give a detailed discussion on various commodity exchange dominant commercial activities by electronic means and their corresponding occupational categories from the perspective of narrow sense of e-commerce.

Research on e-commerce occupations

Forty years ago, China Labor & Social Security promulgated "Dictionary of Occupation in China", the first programmatic document to give an objective and comprehensive classification of Chinese occupations, which basically reflected the structures of social occupations and provided significant basis for statistic information of workers, employment guidance, and occupation introduction, etc. [START_REF]Dictionary of National Occupational Classification and Vocational qualification Authentication Committee[END_REF]. However, because of the development of economy, the advance of science and technology, and the improvement of industrial structure during the past four decades, the dictionary, at present, cannot meet the requirement for the construction of Chinese occupational classification in various industries, especially in newly emerging industries, such as ecommerce. Furthermore, the rapid development of e-commerce triggers the tremendous changes in its occupational structure and operation mode. Thus, these reasons result in that the principles of the occupational classification in the dictionary not only are unable to reveal the trend of the current e-commerce industry comprehensively and objectively, but also fail to provide efficient guidance for the development of the industry. So far, there have been few research works focusing on the construction of occupational classification, even fewer in e-commerce industry. Research works on the classification of e-commerce occupations are still in their infant stage, which reserves numerous spaces for the further development. Recently some documents have generated on the construction of occupational classification of e-commerce. However, they mainly focused on elucidating the significance of occupational classification and their instructive effects on vocational education, which could not meet the demand of the development of Chinese e-commerce industry.

With the continuous development of Chinese e-commerce, researchers have gradually realized the importance of e-commerce occupational classification, which stimulated their great research interests on this theme. [START_REF] Liang | Analysis on Professional Orientation and Personnel Training of E-Commerce[END_REF] first thought that the e-commerce positions could be divided into two categories in terms of the evolution process, namely the traditional positions modified by the effect of new information technology and the situation of e-commerce booming, and the newly-emerging positions induced by computer science, Internet and communication technology, which were the pioneering works on the original classification of e-commerce positions [START_REF] Liang | Analysis on Professional Orientation and Personnel Training of E-Commerce[END_REF]. Subsequently, [START_REF] Meng | Analysis on E-Commerce Personnel Training and Employment[END_REF] demonstrated the four types of ecommerce positions including technology, business, management, and e-commerce engineering ones, which further promoted the construction of Chinese e-commerce occupational classification [START_REF] Meng | Analysis on E-Commerce Personnel Training and Employment[END_REF]. [START_REF] Gui | New Impetus of Economic Booming-Mechanism and Effect of E-Commerce Measurement: E-Commerce Occupations[END_REF] from the viewpoint of the development status of commercial services and applications, classified e-commerce occupations into two categories, namely e-commerce service and e-commerce application, on the basis of job demands [START_REF] Gui | New Impetus of Economic Booming-Mechanism and Effect of E-Commerce Measurement: E-Commerce Occupations[END_REF]. The iResearch Consulting Group conducted extensively interviews and investigations on e-commerce enterprises and pointed out that the occupational classification positions in e-commerce industry could be sorted into six categories, such as positions of e-business operation, marketing, network engineering, logistics, procurement and customer service; besides, with the same method, a detailed subordinate classification was conducted on the basis of the above six categories [14].

On the basis of the aforementioned research results, it can be found that as great efforts have been made in e-commerce industry, the investigations on the e-commerce occupational classification has become more and more comprehensive and deepening. However, despite of some advances, the state-of-the-art of e-commerce occupational classification cannot satisfy numerous requirements of the development status and market demands in the industry. Therefore, the construction of a maturity e-commerce occupational classification in China is highly pursuing, but still a great challenge.

The Experience of Occupational Classification in China and Abroad

According to the researches of the authors, there also have been few completely comprehensive e-commerce occupational classification systems in abroad, which is adverse to the improvement of e-commerce worldwide. Thus, we have to build a new system to serve for the industry. In order to construct a consummate e-commerce occupational classification in China, we should take some effective and practical experience as references from China and overseas. The following are several typical examples of occupational classification from Canada, America and Chinese IT industry.

3.1

Features of occupational classification in abroad

Standard system. An occupational classification book published in Canada, is one of the most abundant, substantial and comprehensive reference tools for the classification of e-commerce industry. This reference book demonstrates that the occupations in Canada can be systematically and thoroughly classified into 10 broad occupational categories, 40 major groups, 140 minor groups and 500 unit groups. There are approximately 40,000 occupational titles classified in the 500 unit groups of the NOC (National Occupational Classification) 2011, which constitute the classification system. In the system, each major group has a unique digit code orderly, as well as minor group, unit group and occupational title [15]. This reference book featuring with extremely comprehensive and professional characteristics of occupational classification method, covers a wide range of occupational classification for almost all positions in Canada, and provides detailed description of work skills and access requirements. Inspired by its broad universality, the construction methodology of occupational classification in this book is applicable not only for Canada, but also for other countries with different social systems, as well as for the construction of Chinese e-commerce occupational classification.

Flexible methods.

There is a widely applied information system on occupational classification in America. The system classifies jobs from generality to individual into 23 major occupational groups of the revised SOC (Standard Occupational Classification) system. These major groups include 97 minor groups, 461 broad occupations, and 840 detailed occupations according to the following six criterions: requirements of knowledge, requirements of practical experience, qualification of job holders, personalities, special work requirements and professional features [START_REF] Cosca | Revising the Standard Occupational Classification system for 2010[END_REF]. Meanwhile the design of the system also focuses on the quality of the users experience, allows to be classified by different methods during collecting data, and displays high flexibility and customization, which agrees well with the practical demands of users. Thus, the construction methodology of occupational classification in this system is of great value for directing the construction of Chinese e-commerce occupational classification system.

Dynamic update of contents.

The contents in occupational classification system in America can be updated periodically, which can remove the outdated positions and simultaneously monitor newlyspringing up professions on the basis of changes of social industries, such as revolution of IT, popularity of office automatic (OA) system and explosion of tertiary industry continuously. So users can make good use of the system to compare the newly developing positions with their own, and thus grasp the latest occupational information to serve for themselves. Additionally, the system gives emphasis to collecting the information of service-oriented and professional positions and eliminating the records of positions of labor-intensive industries to update the system, which is in well accordance with the laws of social development.

Adaptable for users.

The occupational classification system in America is divided into four hierarchies which are convenient to information acquisition for both organizations and individuals according to their own requirements. The users can compare the data with their own work properties to orientate themselves to make decisions or to fulfill diverse needs.

Features of IT industry in China

A research group of IT field constructs a specific occupational classification system which is built according to two main reasons. The first reason is based on the considerations of the practical situation where the development prospects of economy, technological innovation and industries transformation present in China. The second reason is the rapid development of IT occupations with a large number of employees and positions emerging. In the scheme, the occupations in IT industries are firstly classified into 3 main categories, such as the major group, the application group and the related group. Secondly, the major group is subdivided into 5 minor groups, such as software, hardware, web, information system and manufacturing groups, which represent 5 crucial pillars in IT industry. Thirdly, the application group is subdivided into 7 minor groups, such as control, design, business, entertainment, education, and communication groups. Fourth, there are 41 unit groups formed on the basis of dividing the 12 minor groups mentioned above. Additionally, there is no subdivision in the related group [17]. The classification system data in the scheme shows that it covers almost all the positions and reflects the basic structure of occupations comprehensively in IT industry, which has been verified by its practical applications in personnel training and course arrangement.

In addition, because of the high variability of the IT occupations, the research group is currently considering constructing a long-term observable pre-warning system to monitor the variation of relevant positions, which will provide theoretical and experimental support for perfecting and updating the IT occupational classification system.

The Construction of Occupational Classification System in E-Commerce Industry in China

On the basis of combining the experience of the above excellent occupational classification methods with the situation of e-commerce development in China, the approach to construct occupational classification system in e-commerce industry can be divided into three parts, namely principles, aims and methods.

4.1

Principles and goals

Scientific and standardized.

Taking the development of global economy, improvement of industrial structure, and the progress of science and technology into consideration, the occupational classification system in e-commerce industry should be classified in light of properties, objects, range, and surroundings of work. Furthermore, the system should be constructed rigorously in line with rules of "Dictionary of Occupation in China". On the basis of the above considerations, the occupation system of Chinese e-commerce industry should be divided into four categories including major groups, minor groups, unit groups and detailed occupations. Of these classifications, the major groups are categorized according to working properties and capability requirements; the minor groups are classified further on the basis of working tasks and division of labor within the respectively major groups; the unit groups are divided and aggregated further on the basis of objects, circumstances and demands of work in the same minor groups; the detailed occupations are classified further according to the tools, equipment, techniques, etc. within the same unit groups; besides, those immature and indefinite positions should also be placed and explained properly. Moreover, if the method is in line with the traditional classification standards and rules, it may lead to the classification system failing to cover all the occupations in e-commerce industry accurately, because of the rapid, variable, and time-depending development of the e-commerce occupations, and as a result, the classification may be repeated or neglected. Therefore, it is highly desirable to classify e-commerce occupations flexibly to cover all their corresponding aspects to meet the criterion of national occupational classification.

Rational and applicable.

As the ultimate aim of classifying the occupational system of e-commerce is to boost the development of e-commerce industry and to provide efficient assistance for the economy development, so the system should agree well with the rational and applicable rules. During the classification process, the core concept for the construction species of each hierarchy should keep integrity, the standards of classification level should be identical, and the structure of the occupational system should be logical, which can ensure the rationality of occupational classification in e-commerce industry. Besides, the expressions in the system should be as concise and clarified as possible, which can sufficiently reveal the job properties, activity modes and work requirements, and also be applicable for business and national administration.

Comprehensive and long-acting.

The construction of occupational classification system of e-commerce should be comprehensive and long-acting throughout its every aspect including data collection, position setting and position description. Moreover, it should combine the advantages of all the similar researches and display distinct characteristics. Except for the rules mentioned above, the system should be advanced in its framework and long-acting in function, and in the top list among various occupational classification systems. Only by using this method can the functions of the system be comprehensive and longlasting.

Dynamic and open.

As e-commerce occupations develop rapidly and variably, the system of occupational classification in e-commerce industry should display the feature of dynamic update.

Once new positions emerge, they should be first subjected to classification positioning timely and effectively and subsequently, match automatically on the basis of their working properties, ability requirements. Then, their corresponding affiliation classifications should be confirmed according to the above positioning results and this operation process needs to develop into a continuing system, which can facilitate the dynamic update and timely addition or deletion of e-commerce occupations. By adopting this sort of method, this system not only can reflect the state and trend of occupations scientifically, objectively, completely and accurately, and additionally, but also obeys the rules of development and meets practical demands in e-commerce industry.

Moreover, the construction of e-commerce occupational classification system should meet the relevant criterions and absorb advanced experience in China and overseas. And then, we should select the concrete e-commerce positions as the main constituents, and distinguish the difference among various e-commerce positions by analyzing their contents and styles to form a scientific, rational, ordered, open and applicable system of occupational classification.

The construction approaches of e-commerce occupational classification system

Meeting requirements and standards.

Through investigating and interviewing those relevant e-commerce enterprises in China to collect information from e-commerce market, we should grasp the situation of positions setting and then analyze the category of e-commerce corresponding to "Dictionary of Occupation in China" to place the e-commerce occupational classification system and finally construct the system in line with related standards and requirements strictly. Also, the system should meet requirements of Chinese current market system, and simultaneously be in accordance with national circumstances. Furthermore, the system should exhibit unique characteristic and also provide references to the revision and improvement of the "Dictionary of Occupation in China".

Learning experience.

The authors hold that the systematically occupational classification results carried out previously in China and abroad should be studied thoroughly, and the statistics of those relevant positions in e-commerce industry should be paid more attentions. Moreover, after comparative researches, we should draw a comprehensive summary of all relevant experience, adopt excellent methods and eliminate outdated approaches.

Constructing a dynamical system.

The completed e-commerce occupational classification system should meet the standards of Chinese occupational classification, and in the meantime, it can develop into an independent system. In the vertical direction, the system should establish a logical framework including major groups, minor groups, unit groups, detailed occupations, and further form the main part and related part occupations in the classification, while in the horizontal direction, the definitions and descriptions of positions should be accurate and complete, which consist of basic skills, basic knowledge, work environment, relevant training, professional qualifications etc.

In addition to accurately revealing the state of e-commerce occupations, the system should predict the development trend of e-commerce industry. Therefore, it is suggested to build monitoring systems in universities or e-commerce institutes to track the trend of occupations, to detect emerging and fading ones, so that the contents and structures of the system can be adjusted and updated timely to reflect the e-commerce development authentically.

4.3

The construction of e-commerce occupational classification system

The system of e-commerce occupational classification should mirror the contents in the form of the catalog table, and can be divided into vertical and horizontal parts which interconnect and correspond with each other. In the catalog table, by taking management responsibilities and technical operations abilities as references, the vertical part is classified into four grades including high level, middle level, primary level and bottom level, all of which have an ordered arrangement. This construction method of e-commerce occupational classification, enables its pyramid-like characteristic, is well arranged and able to comprehensively cover the whole e-commerce industries.

While the horizontal part of the system is classified according to the sequence modes of occupations, which can reflect the positions types comprehensively and avoid the repeating classification of emerging positions induced by monotonous arrangement. Additionally, because of the rapid development of e-commerce industry, the verticalhorizontal classification method can timely update the state of positions variation and maintain the system open. Furthermore, the single existence of every position ensures the independence and integrity of the system and the methods for maintaining and adding new classifications are very simple and convenient, which provides reliable references for the construction of other industries. Below is the construction method of detailed e-commerce occupational classification system (as shown in Table 1) It can be seen from table 1 that in the vertical direction, the e-commerce occupational categories consist of 4 major groups: senior manager, middle-level manager, comprehensive primary-level staff and general staff representing four ranks which share similarities with the form and the personnel structure of traditional enterprises. At the same time, the comprehensive primary level staff contains three types of occupations which are business type, technology type and service type, however other ranks are not obviously with such types. In the horizontal direction, the construction of the system is on the basis of the four occupational categories, and highlights the vocational characteristics of e-commerce industry. Moreover, the method for the contents arrangement can basically meet the criterion of "Dictionary of Occupation in China", which is beneficial for the human resource management and labor statistics in China.

Additionally, the system covers not only the majority of traditional occupations, but also some ones associating with newly emerging technology and information. Among the system, the whole senior management positions, parts of middle level and comprehensive primary-level staff positions and almost all the general staff ones originated from the evolution of traditional industries, and are still the dominating part of occupational categories in e-commerce industries and maintaining their characteristics and skills of original vocations, which also endows e-commerce industries with unique characteristic and novel definition, such as General manager in the rank of Senior manager, Executive officer in the rank of Middle-level manager, Financial officer and Casher in the rank of Comprehensive primary-level staff and Securityguard in the rank of General staff, etc.. Parts of middle-level and comprehensive primary-level staff positions associating with lately-emerging technology and information, have generated following the development of information technology, especially the e-commerce industry such as Director of IT, Information manager, App developer, CRM personnel, etc. Besides, all the positions of the system listed above are categorized basing on the narrow sense of the e-commerce concept, and basically include all of them in the system of the industry, which induces the formation of a comprehensive system.

Obviously, the classification system established herein not only gathers all occupations in e-commerce industry, but also endows them with the specific industry characteristics. However, the occupations in American and Canadian classification systems are not classified according to industry content, which poses great obstacles to the development of those industries. Compared to Canadian and American occupational classification systems whose aims are to facilitate the management, the occupational classification systems of Chinese e-commerce established in this study helps the enhancement of e-commerce knowledge and professional qualities and has a goal of optimizing allocation of human resources and promoting the development of ecommerce, though both kinds of occupational classification methods share the same theories. More importantly, the construction methods originate from the combination between the consideration of current situations in Chinese e-commerce and the references of advanced occupational classification experience from China and abroad, which resulted in the formation of e-commerce occupational classification with Chinese characteristics.

Conclusion

In summary, through basing on the current state, obeying the rules of the development of relevant industry, following the corresponding classification modes and standards and learning advanced experience of classification system in China and abroad, we propose the construction methods and principles, and finally realize the reasonable construction of Chinese e-commerce occupational classification system. We believe that the successful construction of occupational classification system in e-commerce will have a far-reaching impact on the development of society and economy in the following aspects. First, the proposed methods and principles of classification can enrich fundamental theories of occupational classification. Second, constructing Chinese e-commerce occupational classification system can perfect the classification framework of the whole industries in China. Third, this event can undoubtedly boost the development of e-commerce industry. Fourth, the established theory of occupational classification in this study can offer efficient guidance, not only for the classification construction of other Chinese industries, but also for the construction of occupational classification system in other countries. However, some problems still remain unsolved, such as the classification of position properties, salary, job requirements, which encourage us to conduct a further exploration on these issues from a broader and deeper viewpoint in future.

Table 1 .

 1 E-commerce occupational classification contents

	Rank	Type	Occupations contents
	Senior manager		General manager/ Vice general manager
	Middle-level		Executive officer,	Director of marketing,
	manager		Chief financial officer,	HR director,
			Director of operation,	Director of equipment,


Baohua Dong
email: baohua@whu.edu.cnfuyue412@gmail.comlyzhang@whu.edu.cn

Qihua Liu
email: qh_liu@163.com

Yue Fu

Liyi Zhang

A Research of Taobao Cheater Detection

Keywords: Fake trading, Product review, SVM, Cheater detection

Introduction

According to the 33rd China Internet network development state statistic report issued by China Internet Network Information Center (CNNIC), by the end of December 2013, the number of online consumers in China has reached 302 million [START_REF]China Internet Network Information Center[END_REF]. Such a huge online shopping market makes numerous entrepreneurs see business opportunities, thousands of new stores set up on Taobao every day. However, many of them have little online traffic due to low credibility. Therefore, many newly opened stores try to improve their reputation in various ways. The most typical one is fake trading. Fake trading refers to the cheating behavior that some merchants in e-commerce platform improve sales, store ratings and credit score by improper means. Fake trading has developed into a huge industry. We can find hundreds of third party fake trading platforms and thousands of QQ or YY groups that are serviced for fake trading. Consumers usually read the reviews before buying. However, due to the existence of fake trading, it is difficult for them to judge the reality of reviews. Thus, reading reviews while shopping online is a double-edged sword, real reviews make them understand the products better, but when a spam review comes, they will be misguided. Thus, finding spam reviews timely is of great significance. This paper adopts the method of identifying cheater to identify spam reviews. If a reviewer is cheater, the reviews he has published can be regarded as spam reviews.

2

Related work

Online reviews research has been a hot topic in recent years, especially spam reviews that attract attention of many scholars at home and abroad. Researches on spam reviews mainly concentrate on text classification and consider the recognition process as the classification of spam and true reviews through manual label, extracting features from the text and using machine learning methods to identify spam reviews automatically. However, due to the judgment of true or fake of product reviews is relevant to psychology, philosophy and many other fields, in addition, it involves the process of natural language understanding and opinion extraction of the review text, therefore, it is difficult to detect fake reviews based on review content, the effect is not very good either. Thus, scholars began to focus on the behavioral characteristics of reviewers based on which we can determine whether a review is a spam review. This method is often used to find spammers. It holds that, if a user is a spammer, then his reviews have strong possibility to be spam reviews. Jindal et al [START_REF] Jindal | Finding unusual review patterns using unexpected rules[END_REF] take reviewer's behavior into consideration and analyze the possibility of the reviewer to be a spammer through finding abnormal review patterns. If a user repeatedly publishes positive reviews, then there is strong possibility that he is a spammer. Wu et al [START_REF] Wu | Distortion as a validation criterion in the identification of suspicious reviews[END_REF][START_REF] Xie | Review spam detection via temporal pattern discovery[END_REF] use the proportion of positive singletons (singleton refers to the only review that a reviewer had published) in all the reviews and the time aggregation degree of these singletons to analyze reviewer's suspicious behavior. Wang et al [START_REF] Wang | Identify Online Store Review Spammers via Social Review Graph[END_REF] discover the reinforcement relations of reviews' trustiness, reviews' honesty, and stores' reliability. They use such relations to discover suspicious spammers. Mukherjee et al [START_REF] Mukherjee | Detecting Group Review Spam[END_REF] use frequent pattern mining to find groups of reviewers who frequently write reviews together, and then they construct features to find the most likely groups of spammers. They also construct a graph modeling the relations between groups of spammers, spammers and products for group spammer ranking [START_REF] Mukherjee | Spotting fake reviewer groups in consumer reviews[END_REF]. Zhang [START_REF] Zhang | Exploiting shopping and reviewing behavior to re-score online evaluations[END_REF] focuses on detecting the credibility of customers by analyzing online shopping and review behavior, and then they re-score the reviews for products and shops. Spammers can be taken as the special case of their work, which had very low credibility. Lim et al [START_REF] Lim | Detecting Product Review Spammers using Rating Behaviors[END_REF] propose a behavioral approach to detect review spammers who try to manipulate review ratings on some target products or product groups. However, because these studies basically define the behavior of spam reviewers artificially, then determine the spammers or spam reviews. The precision of this method is hard to estimate. In addition, the former studies mainly focus on reviews of one or several products; few studies focus on the historical review data of the reviewers that exist on a platform such as Taobao. For this reason, we collect cheaters' account information from the third party fake trading platforms and real buyers' account information from popular stores on Tmall. We get the historical review data of these buyers on Taobao using crawler software, and then extract features from three aspects including reviewer, commodity, and review to identify the cheaters.

3

Feature extraction

There are many forms of fake trading; currently the most used one is fake trading on third-party platform, which links both side (sellers who need fake trading and cheaters who engage in fake trading) through an intermediate platform. Both sides publish relevant information on the middle platform, and platform provides guarantee as a third party for both sides to reach an agreement. There are several typical fake trading platforms, such as hiwinwin.com, shuaxinyong.com, shuakewang.com, etc. Many scholars have adopted the machine learning method, establishing spam review feature library for identification of spam reviews. Among them, most of the scholars extracted corresponding features according to the content of review, such as review sentiment polarity, scoring etc. However, since the review content belongs to natural language, which is difficult to process, and there is no significant difference between true reviews and spam reviews. Therefore, it is almost impossible to identify spam reviews from the comment content. For these reasons, many scholars begin to look for features from other sources. Mukherjee et al [START_REF] Mukherjee | Spotting opinion spammers using behavioral footprints[END_REF][START_REF] Mukherjee | Spotting fake reviewer groups in consumer reviews[END_REF] believe that the factors such as content similarity, maximum number of reviews, ratio of first reviews and review length have a significant effect on identifying spam reviews. In another paper, Mukherjee et al [START_REF] Mukherjee | What Yelp Fake Review Filter Might Be Doing?[END_REF] report that opinion spammers are usually not longtime members of a site. Real reviewers, however, use their accounts from time to time to post reviews. These features have played a certain effect on identifying artificially labeled spam reviews, but whether they can be used to identify the real spam reviews remains to be verified. More importantly, the previous research object is the data of Amazon, but there are many acts of fake trading and spam reviews on Taobao. In order to identify cheaters on Taobao, this paper absorbs the previous research results, analyzing the information of cheaters on third party spam trading platform and information of normal reviewer from Tmall, and we summarized the specific characteristics of cheaters on Taobao. Review centric features include gender (F1), number of registration days (F2) and identity authentication status (F3). Commodity centric features include total number of commodity categories (F4), number of categories purchased in a single day (F5). Review centric features include average length of reviews (F6), daily number of reviews (F7), and no repetition rate of reviews (F8).

Using the above features of reviewers to constitute an eigenvector for every reviewer, calculation methods of the eigenvector are as follows:

1 0 , 1 0 : 1 ( ) F n n female male   ,( ) ;: 2 0 , 1 , 2 : ( ) F n n n number of registration days     ,( )   3 ,
T f x w x b   (1)
where w denotes a vector of weights and b denotes an intercept. The value of ( ) f x presents the quality of the instance x , the higher value of ( ) f x is, the higher quality of the instance x is. The sign of ( ) f x is employed in our classification. If the sign is positive, then x is classified into the positive category (real buyer), otherwise into the negative category (cheater). The building of SVM needs labeled training data (in our case, the categories are "real buyer" and "cheater"). Briefly, the learning algorithm creates the "hyper plane" in (1), and the hyper plane separates the positive and negative instances in the training data with the largest margin.

Experimental program

This study selects historical review data of cheaters and real buyers as object, using LIBSVM tool for training and testing experimental data. Specific programs are as follows: Firstly, data processing and format adjusting are done on historical review data of reviewers. We use the crawler software crawling the basic personal information and review information of reviewers on Taobao. These data are consolidated, and we build a data set of historical reviews for each reviewer. Elements and the format of all data sets are the same. Secondly, we assign features according to reviewer, commodity, and review to construct a standard data set. We extract features from historical review of each reviewer and construct a data set using feature data of all reviewers. All data are labelled completed. Thirdly, we call LIBSVM tool and use radial basis kernel function to train samples and generate a model file. We construct a classification model using the data of 70 cheaters and 70 normal reviewers for testing. Lastly, we test and forecast the generated model using the test data set. We use the classification model to test the remaining 30 cheaters and 30 normal reviewers, in order to testing the effectiveness of the classification model.

Evaluation indexes

The most commonly used classification indexes for text classification are recall, precision and F1-measure [15]. The recall of a class X is the ratio of the number of users correctly classified to the number of users in class X. The precision of a class X is the ratio of the number of users classified correctly to the total predicted as users of class X. The F1-measure is the harmonic mean between both precision and recall, and it is usually reported to evaluate classification effectiveness. Our research can also be seen as a classification problem. To assess the effectiveness of our classification strategies, we use the standard classification index of recall, precision and F1-measure.

(1)Recall Recall refers to the ratio of the cheaters correctly classified to the number of cheaters in our dataset. The calculation formula is as follow:

TP Recall TP FN  
(2)Precision Precision refers to the probability that cheaters are correctly predicted to be cheaters. The calculation formula is as follow: TP Precision TP FP  

(3)F1-measure F1-measure refers to the harmonic mean between both precision and recall. The calculation formula is as follow:

2* * 1 ( )

Recall Precision F Recall Precision  
|TP| refers to the number that cheaters are correctly predicted to be cheaters, |FN| refers to the number that cheaters are incorrectly predicted to be real buyers, |FP| refers to the number that real buyers are incorrectly predicted to be cheaters.

Experiments and result analysis

Introduction to Dataset

In this study, we collect nearly 50285 data about historical review information of cheaters and real buyers.

The data collection method of cheaters is as follows: Firstly, we get merchants' fake order information and specified requirement from the professional third-party fake trading platforms, such as shuaxinyong.com, hiwinwin.com, shuakewang.com and so on. Secondly, we find out the cheaters' account information by comparing the specified requirements with the order information. Thirdly, we collect the cheaters' personal information by the Taobao inquiry website taodake.com. Lastly, we collect each cheater's data by using the web crawler (The system default reviews and anonymous reviews are not included in the data).

The data collection method of real buyers is as follows: Firstly, we choose the stores with great influence and high credit which don't need to improve credit ratings through fake trading, such as the official flagship store of Xiaomi. Secondly, we find out the real buyers' account information by judging the behavior of the anonymous reviewers. If the reviewer does not have abnormal behavior, that is, the reviews are objective, it can be concluded that the reviewer is a real buyer. Thirdly, we collect the real buyers' personal information through the Taobao inquiry website taodake.com. Lastly, we collect each real buyer's data by using the web crawler (The system default reviews and anonymous reviews are not included in the data).

Experiments

Our experiments take matlab2010b (matlab7.1) as the experimental platform, the support vector machine is professor Lin's libsvm-mat-3.1 version. We adjust the format of data first, and then import it into the matlab and conduct experiments. The training set includes 140 samples (70 cheaters and 70 real buyers), the test set includes 60 samples (30 cheaters and 30 real buyers), and all the samples have been labeled. The experiment uses a RBF SVM model to identify cheaters out of the data set. When the data is normalized, we use the grid search and ten-fold cross validation to optimize the SVM parameters. Then we use the optimized parameters to construct a classification model that can be used to predict the test set. The predict result is shown in Figure .1. We can see that the model established using the data of 70 cheaters and 70 normal reviewers for training have better ability to identify cheaters, 30 cheaters were successfully predicted. Considering our ultimate goal is to kick out the spam reviewers to reduce the harm caused to consumers, although some normal reviewers are mistakenly identified as cheaters, the error is still acceptable. Overall, the classification model we developed has good prediction ability, and it can well separate cheaters and normal reviewers.

Result analysis

The experimental result of all samples is as follow: As we can see, the better cheater recognition effect is due to the choice of 8 characters. The characteristic dimension is relatively high and the RBF kernel function effectively maps it into a high dimensional feature space, so the cheaters and real buyers are certainly linearly separable. What's more, the effect is better.

Conclusion

This paper identifies the spam reviews by identifying cheaters. We choose the history review data of 100 cheaters and 100 real buyers as our research object. From these data we extract 8 features using SVM algorithm to construct a classification model, and the precision of the final classification model we built to identity the cheater reaches up to 89%. The experimental result shows that, extracting features from the history review data can identify the cheaters effectively. It can be applied to the recognition of the cheaters in Taobao.

Figure 1 .

 1 Figure 1. The actual classification and predictive classification of the test set

Table 1 .

 1 The final results of all samples classified by the classification model

		Cheaters
	The number of cheaters correctly identified	The number of cheaters identified by the model	The actual cheaters number of	recall precision F1-measure
	93	104	100	93%	89%	91%

Acknowledgement. The work is supported by the Natural Science Foundation of China (No. 71373192,71363022) and the MOE Project of key research Institute of Humanities & Social Science in Chinese Universities (No: 14JJD870002)