Virtual  Virtual Communities 1 have opened a broad field of research during the last years. Although numerous researchers have studied this research object [1] [2] [3] [4] [5] [6] [7] , backgrounds, approaches and objectives of the studies differ significantly. The objective of this research is to evaluate success factors for virtual communities that have often been postulated in scientific literature and evaluate their practical importance from the perspective of members and operators of virtual communities. Based on this evaluation, deviations are identified and analysed. The results provide empirically validated insights into developing, introducing and managing virtual communities. The paper is structured as follows: Section 2 provides operational definitions and an explanation on the background for the study. A set of success factors for virtual communities as found in literature and as identified by conducting expert interviews is presented. Section 3 describes the methodology used in this study. Details on data collection are provided in section 4 and 1 Synonymous to "Virtual Community" the term "Online Community" can be used. in section 5 the results of the data-analysis are presented. This paper concludes with a discussion of study results and an outlook on possible future research themes. A list of the success factors (divided by target groups and ranked by importance) is provided in the appendix of the paper. Definitions and Reference Framework For various reasons, no common agreement on the definition of the term "virtual community" could be identified in the literature [9] . First, virtual communities are a multidimensional research object which can be analysed from various perspectives including psychology, administrative science or computer science. The discipline initiating the study tends to define the term virtual community according to its scientific body of knowledge. Secondly, the phenomenon of popular words, so-called "buzz words" used in this area obscures a clear differentiation between scientific terms and jargon [5] . The current study is based on the following working definition: A virtual community consists of people who interact together socially on a technical platform. The community is built on a common interest, a common problem or a common task of its members that is pursued on the basis of implicit and explicit codes of behavior. The technical platform enables and supports the community's interaction and helps to build trust and a common feeling among the members. Similar to the diversity of definitions of the term virtual community, there exists a high diversity of dimensions used to categorise virtual communities 2 . Despite the large number of dimensions, researchers argue that many existing virtual communities cannot be categorised unambiguously. On the one hand, the reason for the difficulty in categorization may be due to the particular specification of the virtual community. For example, a 2 For an overview see also [10] . community for breast cancer patients with a regional focus can be classified as a geographic community, because of the regional focus, as a demographic community, because of the focus on women, and as a theme-centered community as the focus is issues related to breast cancer 3 . Conversely, the difficulties encountered in attempting to categorise virtual communities might be caused by the fact that the existing categories are overlapping [12] . In order to keep the field of virtual communities used in this study as broad as possible and to be able to categorise virtual communities unambiguously, this study uses the financial interest of the operators of the community to categorise virtual communities. Therefore, in this study, commercial and non-commercial communities are distinguished. Research on success factors generally focuses on the search for methods and models that explain success (of companies) and how to maximise it. Studies attempt to give recommendations -as detailed as possible -on how to provide and use resources in an ideal way. The recommendations are often insufficient as the number of influencing variables is high and the correlation between the variables is extremely diverse. Rather, research on success factors aims at formulating guidelines that can be influenced by the operators and that result in a strategy which is expected to be successful. [8] . Such orientation principles do not claim to fully explain all correlations, but try to give new ideas for the conception of approaches that might be more effective. In order to evaluate factors which contribute to the success of virtual communities, the study authors first summarize 4 success factors of virtual communities as found in literature and subsequently evaluate them according to their importance for operators 5 and members of virtual communities. A review of the literature revealed a great diversity of factors which influence the success of virtual communities. With regard to the evaluation of these factors, this study differentiates between member-and 3 These categories are taken from [11] . 4 The extraction of success factors from literature is not covered in this paper, for more details on this see [13] . Some authors distinguish more stake-holders within a virtual community, especially when it comes to the organisation of a virtual community. Butler et al. [21] e.g. distinguish volunteers, equity holders and payroll employees and they state that each group has different motivations. Empirically identifying and addressing each of these groups is hardly possible in a brief survey. Therefore the authors desist from this differentiation for the purpose of this survey but acknowledge its role for continuative research. operator-oriented success factors. All together, 32 factors were identified: 26 were presented to members of virtual communities and all 32 to the operators (the six factors that are merely operator-oriented are highlighted gray in Table 1 ). The success factors have been reviewed, expanded and adjusted following the results of a Delphi study 6 conducted among experts in the field of virtual communities. The Delphi study also tested potential correlations between the success factors. Table  1 gives an overview of the success factors. To be able to identify the success factors more easily, an identification number was assigned to each factor. 6 Cf. [13] Sidiras, P., Erfolgsfaktoren virtueller Gemeinschaften. Master Thesis at the Information Systems Department, Hohenheim University. ID-# Reaching a high number of members within a short period of time 1 Building trust among the members 2 Evolution of the community according to the ideas of its members 3 Offering up-to-date content 4 Offering high-quality content 5 Appreciation of contributions of members by the operator 6 Assistance for new members by experienced members 7 Establishing codes of behavior (netiquette/guidelines) to contain conflict potential 8 Supporting the community by regular real-world meetings 9 Handling member data sensitively 10 Arranging regular events 11 Intuitive user guidance 12 Personalised page design of the community-site according to the preferences of its members 13 Establishing and supporting sub-groups within the community 14 Integration of the members into the administration of the community For the data collection, an overview of virtual communities by Bullinger et al. [7] was used. The communities listed in this overview were used as a starting point and a call for participation for the questionnaire was posted in all of the still existing communities. Similar to the snowball sampling method, links to other communities were spotted. The additional communities were added and calls for participation were posted on them as well. Altogether, messages were posted in 160 virtual communities covering a wide variety of online communities in respect to both size Online-surveys as a subtype of written surveys are a special way of collecting data. When positioning a questionnaire on the internet compared to sending it out via mail or hand to hand distribution , it can be stated that "only" the medium through which the questionnaire is presented has changed. Choosing an online survey as a method to collect data, poses some important consequences for the process of the investigation and for the design of the questionnaire. For further details see for example [16] and [17] . In summary, some basic problems occur when conducting an internet survey: The universe of internet users is basically undefined [18] ; the sample is self selective and therefore cannot be regarded as being representative, statements about "nonparticipants" cannot be made [18] . The questionnaire used in this study was structured, tested and consequently adapted to the needs of the specific audiences targeted in this study. For this purpose a pretest followed by a discussion with the test persons was conducted. In addition, an online-pretest was carried out that tested the content and the functionality of the questionnaire. The field phase generated a little more than 800 questionnaires for data analysis. After sorting out incomplete or inconsistent answers, 745 data sets were available for analysis. By dividing the questionnaire into several parts (at least 2) and due to different groups of interviewees (users and operators, male and female, commercial and non-commercial, etc.), several starting points for comparing groups with regard to their statements became apparent. On this basis, rankings of success factors (according to the different groups) were established. The differences between their arithmetic means 10 were tested and compared. In addition questions referring to socio-demographic data as well as to internet usage and virtual community usage were analysed independently from the analysis of the success factors. The use of a bipolar verbal ordinal scale allowed members to express their agreement or disagreement with the statements (see figure 1 ). A statictically significant deviation from the means can only be proven by a suited test procedure. In this case a two random sample test for the difference of two aritmetic means (cf. for example [19] ), level of significance (here =0.05) was used. For data analysis the scale was reinterpreted into a numerical scale (shown in figure 2 ) (regarding the procedure see for example [20] ). For the analysis the data sets were divided into six groups: members (all), members (female), members (male), operators 11 (all), operators (commercial), operators (non-commercial). In the following section these different groups will be compared with each other. Table 2 : Key data and answers of the survey among members (male: n=434, female: n=210) First an overview of the characteristics of the respondents is given. This is followed by a description and comparison of the group of members with the group of operators. Table 3 shows the responses of the members of the virtual communities to the question regarding how long on average they stay on the internet during free-and work-time. About half of the time online is spent in the respective communities. Of note is that female respondents spend a large portion of their online-period in their communities as compared to their male counterparts. On average, respondents were members of three different communities, a concentration in only one community was not observed. The frequency of both writing and answering messages in the discussion forum was higher for men than for women. Seldom did either group order products or services via their virtual communities. A reason for this could be that the members are unsatisfied with the evolution of "their" community. This assumption was refuted by the survey: both men and women stated their satisfaction with the evolution of the communities they had joined. Generic statements of the respondents The term operator is used for describing the party that operates (runs and manages) a virtual community. On average, female respondents reported being members of a community for 1.42 years and men 2.02 years. However, female respondents reported more intensive personal (unmediated) contacts than male respondents. 65.1% of the women, as compared to 52.5% of the men, acknowledged having personally met at least one other member. Although there are no comparable values, both values seem to be relatively high, showing that on average every second respondent, irrespective of sex, knows at least one other community member personally. When interpreting this result it could be concluded that virtual communities play an important role in establishing personal relationships. The group of operators (addressees are persons who operate a community, not institutions or companies) can be subdivided into the group of operators with commercial interest and the group of operators with no commercial interest. The survey of operators produced the following results (in addition see Table 4 ). As expected, the length of time the operators were online was much higher than the length of time spent online by members. Interestingly, commercial operators spent less than 50% of their daily online time in their own communities which cannot be explained by the fact that on average they operate 1.82 communities. Noncommercial operators run 1.26 communities on average. Asking operators for an evaluation of their potential profits / potential revenues there is no clear result as the average score of 2.9 corresponds with the answer category "uncertain" -an answer given by both commercial and non-commercial operators. As to reported satisfaction with the evolution of their community, on average both commercial and noncommercial operators indicated that they were "satisfied" with the evolution of their community (2.03 for commercial and 2.15 for non-commercial operators). The reported reasons for satisfaction with evolution included the growing number of members and the interaction between the members of the community. The 4.2 Analysis of the success factors from the perspective of female and male members of virtual communities Table 5 shows the ranking of the importance of the individual success factors as they were perceived by all members. In addition, the table depicts how the success factors are ranked by male and female community members separately. In the last column of table 5 deviations between males and females are presented. The deviations that are significant are highlighted in yellow. The ranking shows that in the perception of the members the handling of member data sensitively" is the most important factor contributing to the success of a virtual community. This is followed by more technical success factors such as stability and reaction time of the website. It is of interest to analyse which success factors were ranked differently by men and women. These differences are discussed in the following paragraphs. Significant deviations (level of significance >0.05) between males and females and therefore different evaluations of the importance of specific success factors were measured in eight cases (see table 5 , deviations are highlighted in red). The success factor "supporting the community by regular real-world meetings" was evaluated as mediumimportant by both men and women although women (mean 2.69) rated it of slightly more importance than men (mean 2.91). This same situation exists e.g. in traditional self-help groups where female participants generally outnumber males. In contrast, the success factor "encouraging interaction between members" was evaluated to be more important to men than to women (mean of 1.99 compared to mean of 2.6). Therefore, although real-world contact between community members is less important to men than to women, men in this study seem to take virtual interaction more seriously than their female counterparts . This result supports the assumption that women have a higher inhibition threshold with regard to communication within the community than men 12 whereas men attach 12 Which is supported by the fact that women post a lot less messages within the community than men, see 4.1. less importance to the "real-world" advancement of the relationships built in the community than women do (as a supplement see table 4 in section 4.1). These results could indicate that women might possibly use the community to make new contacts that can be intensified in the real world. Men, on the other hand, focus on the process of making new contacts but not necessarily intensifying them. The highest deviation between male and female community members can be observed when comparing the ratings of the success factor "existence of an offline customer club as a starting advantage". Female community members ranked this success factor of significantly more importance than did males. Although this factor was ranked lowest by both groups, the higher rating given by women supports the previously discussed assumption that women desire off-line contact with other members. Regarding the success factor "integration of the members into the administration of the community" , (involvement in tasks that only affect the virtual community and its administration), the picture changes again: Men clearly evaluate the importance of the participation in administrative tasks (and similar tasks like facilitating a forum) higher than women do (mean of 2.72 compared to mean of 2.94). Summarising the previous paragraphs, it is noticeable that success factors regarding "off-line" communication and "off-line" interaction are evaluated to be more important to female respondents than to male respondents. Success factors relating to interaction within the community such as posting contributions and performing a task within the community were rated as being more important to male respondents than to female respondents. This insight is supported by answers to the overall questions such as the share of personal contacts that evolved from the community or the frequency of posting messages (see 4.1). It is also backed up by the analysis of answers to open questions asking for explanations for user satisfaction with the communities and for personal contacts emerging from the community.
The definition utilized in this paper is that of REF : ''A virtual community [also known as an online community] consists of people who interact together socially on a technical platform.
Success factors of virtual communities from the perspective of members and operators: an empirical study
37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the
37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the
Computer Science