1624 Social Implications of E-Mentoring sonal relationships to develop, especially when e-mentoring dyad members use knowledge- building experiences, perceive similarities in attitudes, values, and communication schema, and appreciate their self-monitoring and CA behaviors. Also, the propositions suggest that given certain HQYLURQPHQWDOFRQGLWLRQVVXFKDVWKHVRFLDOLQÀX- ences received from peers, supervisors and the organization’s culture, as well as geographic and time differences, e-mentoring may act as a suit- able proxy for traditional mentoring relationships. By taking the time necessary to learn about each partner, e-mentoring relationships can be long- term, healthy relationships, regardless of their &0&IRUPDW5HSRUWHG¿QGLQJVIURP0HQWRUQHW (2004), a formal e-mentoring program for college women designed to assist them with remaining LQWKHVFLHQFH¿HOGIRXQGWKDW • Fifty percent of respondents reported that W K HH PH QW R U L Q JS U RJ U D P ¿ OO H GD J DS L Q W KH L U support system. 0RUHWKDQUHSRUWHGJUHDWHUFRQ¿GHQFH in their chosen area of study and felt they would succeed in their careers. • Close to 40% of respondents said they would be applying at the e-mentor’s company for a job after graduation. • No differences were found in relationship satisfaction for same-race versus cross-race pairings. • Some women of color reported increased VHOIFRQ¿GHQFH GXH WR WKHLU HPHQWRULQJ relationship. Clearly, this anecdotal data suggests that e- mentoring is working. Most of the data we have today about the effectiveness of e-mentoring is anecdotal in nature. Figure 1 articulates the relationship between all the variables of inter- est discussed in this chapter. The model and propositions noted herein need empirical testing, as do future propositions and hypotheses about potential variables. In order to understand how e-mentoring affects employees and what social implications it creates, researchers need to in- vestigate the processes inherent in e-mentoring relationships. Differences between formal and informal e-mentoring relationships, the time and distance effect of CMC on e-mentoring, and the Environmental Conditions • Social Influences • Peer/Supervisor • Organization Culture • Geographic/Time Differences Personal Characteristics • Knowledge-building experiences • Communication schema alignment • Perceived similarity • Self-monitoring • Communication apprehension Media Selection & Use E-mentoring Functions Received: • Career development • Role Modeling • Psychosocial Media Characteristics • Social Presence • Richness E-Mentoring Outcomes: • Satisfaction • Relationship effectiveness • Career Progression • Self-efficacy 2 7 Figure 1. Antecedents and outcomes of e-mentoring relationships 1625 Social Implications of E-Mentoring personal characteristics of who will be success- ful in e-mentoring relationships are burgeoning research opportunities. Further investigation is necessary so that we might understand the nuances associated with the antecedents and outcomes of e-mentoring functions provided. Ensher, Heun, and Blanchard (2003) state that while the majority of research on e-mentoring relationships focuses on formal programs, such as MentorNet, there is evidence that spontane- ous relationships are blossoming through use of CMC technology. Ensher et al. suggest that researchers examine the similarities and differ- ences of e-mentoring when comparing formal and informal relationships. The traditional mentoring literature has investigated formal and informal programs and found informal programs to be more advantageous for dyad members (Wanberg et al., 2003). However, while looking at similarities and differences in formal and informal relationships will inform the literature, it will be a challenge for researchers to investigate (and gather data on) informal e-mentoring relationships due to their casual nature and virtual format. In the mean- time, there are many opportunities to examine formal programs and to understand how long WKHVHUHODWLRQVKLSVODVWZKDWW\SHRILQÀXHQFHV participants feel in formal programs, how men- toring functions are received, and what outcomes occur for dyad members and their organizations. The literature will be greatly informed should researchers gather data from all parties—the e- mentor, e-protégé and their employers. Agreement on variables of interest has been found to provide greater insight and reduces reporting biases by respondents (Godshalk & Sosik, 2000; Sosik & Godshalk, 2004). The social implications of CMC on e-men - toring relationships needs to be investigated as we move further away from having a majority of traditional, FtF relationships and towards having a majority of relationships based on use of CMC technology. Early researchers were emphatic that FtF relationships could not be adequately replicated through the use of technology (Con- nolly et al., 1990; Daft et al., 1987; Rice & Love, 1987; Short et al., 1976). Because of today’s VRFLDOLQÀXHQFHVRQHPSOR\HHVWKHJHRJUDSKLF and time differences that must be overcome to complete assigned tasks, and the commonplace use of communication technology, employees are forging relationship through use of CMC with some success (Carlson & Zmud, 1999; Walther, 1992, 1996). E-mentoring researchers need to empirically examine how mentoring functions are received in an online format and what outcomes occur for both protégés and mentors. Also, the effects of time and distance should be analyzed. 'RHPHQWRULQJUHODWLRQVKLSVÀRXULVKEHFDXVH of, or in spite of, time and distance constraints? How long can such relationships last without FtF interactions? Can audio and video technologies be adequate surrogates for FtF e-mentoring interac- tions? Finally, our model posits certain personal characteristics that would make individuals more likely to use CMC and, therefore, to become more actively engaged in e-mentoring relation- ships. There may be other individual difference variables that should be considered to understand who might participate in e-mentoring programs. Quantitative surveys of e-mentoring program participants will provide such data. Such inves- tigations will inform organizations who plan to offer formal e-mentoring programs. It may be that certain individuals are predisposed for success in an e-mentoring environment, while others may be less interested and engaged. CONCLUSION This chapter has offered a model and various propositions to investigate whether or not CMC technology will allow for the development of e- PHQWRULQJUHODWLRQVKLSV6SHFL¿FHQYLURQPHQWDO FRQGLWLRQVVXFKDVWKHVRFLDOLQÀXHQFHVRISHHUV supervisors and the organization’s culture, as 1626 Social Implications of E-Mentoring well as personal characteristics, are posited as antecedents of an individual’s choice of CMC use and subsequent engagement in an e-mentoring relationship. E-mentoring is clearly a new tool individuals may use to enhance their careers, yet the social implications of this phenomenon are still under investigation. The real challenges surrounding e-mentoring involve what effect, if any, the lack of FtF interaction has on dyad members, their or- ganization and their career progression. 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Wellman (Ed.), Networks in the global village (pp. 331-367). Boulder, CO: Westview. This work was previously published in Social Implications and Challenges of E-Business, edited by F. Li, pp. 1-14, copyright 2007 by Information Science Reference (an imprint of IGI Global). 1630 Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 5.16 An Exploratory Study of the Design Preferences of U.S. and Chinese Virtual Communities Felix B. Tan Auckland University of Technology, New Zealand Helen J. Lin University of Auckland, New Zealand Cathy Urquhart University of Auckland, New Zealand ABSTRACT With the increasing popularity of electronic com- merce, businesses are starting to recognise that developing a good virtual community can help to JHQHUDWHPRUHSUR¿WV9LUWXDOFRPPXQLWLHVFDQ be an instrument for building relationships with customers, and retaining customers’ loyalty. Of interest are the similarities and differences in the design preferences of virtual communities across cultural groups. This paper, therefore, examined the design preferences of virtual communities in two cultural groups. The design preferences studied are Web design, tools used, and types of virtual communities preferred. Content analysis was employed to study 20 of the most popular Chinese and U.S. virtual communities. The study found that there are differences in the preference for the type of virtual communities and the tools XVHGE\&KLQHVHDQG86FRPPXQLWLHV7KH¿QG- ings challenge aspects of Web site design across these cultural groups thought to be dissimilar based on prior research, indicating that designers of virtual communities must treat cultural differ- ences with caution. Implications for research and practice are also discussed. INTRODUCTION Over 100 million non-English speakers are now accessing the Internet from all corners of the 1631 An Exploratory Study of the Design Preferences of U.S. and Chinese Virtual Communities world. In the near future, the number of non- U.S. users is expected to outnumber the U.S (Robbins & Stylianou, 2001). Global businesses are beginning to recognise that developing good virtual communities to meet customers’ multiple social and commercial needs can lead to customer OR\DOW\DQGKHQFHJUHDWHUSUR¿WV$UPVWURQJ Hagel, 1996). In order to attract customers from different cultural groups, virtual communities should be designed to accommodate their varied preferences. It is therefore important to study how virtual communities can be better designed to suit the different cultural groups of customers. Prior research into virtual communities has focused on the community types (Armstrong & Hagel, 1996; Chaudhury, Mallick, & Rao, 2001), tools used (Chaudhury et al., 2001; Preece, 2000) and Web site design (Preece, 2000). However, there has been little work into cultural preferences in the choice of tools and types of communities preferred. Although many have suggested that Web sites (in general) should be designed to suit different cultural preferences (Chen, 2002; Fink & Laupase, 2000), our understanding of the cultural preferences in virtual community Web site design remain limited. The aim of this study is, therefore, to explore the design preferences of U.S. and Chinese virtual communities in hope RI ¿OOLQJ WKLV JDS LQ RXU NQRZOHGJH ,Q WHUPV RISUDFWLFHWKH¿QGLQJVRIWKLVVWXG\FDQKHOS virtual community designers better understand design choices across cultures and hence develop virtual communities that can attract and sustain membership. In the next section, we review prior research with a focus on the culture issue relating to vir- tual community Web site design, as well as tools used and community types. The methodology employed is then discussed. Result and analysis is then presented. Discussion and conclusion follow. LITERATURE REVIEW The Concept of Virtual Communities 7KHUH DUH D QXPEHU RI GH¿QLWLRQV RI WKH WHUP virtual communities in the literature. Toomey, Mark, Tang, and Adams (1998) describe virtual communities as spatially distributed people who are able to meet each other, form relationships, and pool their resources through computer- PHGLDWHG VXSSRUW ,JEDULD¶V GH¿QLWLRQ of virtual communities is focused more on the communication side of the communities, where YLUWXDOFRPPXQLW\LV³DWHUPQRUPDOO\XVHGWR describe various forms of computer-mediated communication, particularly long-term, textually mediated conversations among large groups.” Virtual communities are considered different IURPWUDGLWLRQDOFRPPXQLWLHVDVWKH\DUH³PRUH active and discerning, less accessible to one-on- one processes and provide a wealth of valuable cultural information” (Evans, Wedande, Ralston, +XO7KLVSDSHUWKHUHIRUHGH¿QHVYLUWXDO communities as communities formed by people who can be from a different space/time zone and culture, interact together, share resources and interest, and build-up relationships through computer-mediated communication. The Culture Issue Yap (2002)suggests that each virtual community has its own culture, as it provides a virtual space for people who have the same belief and interest to group together, and also share their knowledge. However, people in the virtual communities may be from different places around the world, shar- ing different real-world cultures. For instance, a virtual community can be formed by people from North America and Asia, who have different beliefs and behaviour patterns (Fink & Laupase, 2000). It can be assumed that over time, people 1632 An Exploratory Study of the Design Preferences of U.S. and Chinese Virtual Communities staying in the same virtual community will even- tually develop a set of cultures to share within the group, but initially, a bridge between the types of interactions in the real and virtual worlds must be provided (Schwartz, Bricker, Campbell, Furness, Inkpen, Matheson, et al., 1998). In order to better understand the cultural preferences in the design RIYLUWXDOFRPPXQLWLHVZHQHHGWR¿UVWFRQVLGHU WKHGH¿QLWLRQRIFXOWXUHDQGLWVGLPHQVLRQV Culture is the integrated pattern of human knowledge, belief, and behaviour that depends upon man’s capacity for learning and transmit- ting knowledge to succeeding generations” (Yap, LWLV³DVKDUHGVHWRIYDOXHVWKDWLQÀXHQFH societal perceptions, attitudes, preferences, and responses” (Robbins & Stylianou, 2001), and ³ZKDWHYHU\SHUVRQFDUULHVZLWKLQKLPRUKHUVHOI patterns of thinking, feeling and potential acting which were learned throughout their lifetime” (Simon, 2001). 0RGHOVRIFXOWXUHFDQEHFODVVL¿HGLQWRVLQJOH dimension, historical-social dimensions, and multiple dimensions (Myers & Tan, 2002; Singh, 2003). Single-dimension models contain dyadic characterisation of culture: examples are high context-low context; monochromic-polychromic; high trust-low trust; ideocentric-allocentric; and monochromic-polymorphic (Singh, 2003). :LWKLQWKHKLVWRULFDOVRFLDOFXOWXUHLVFODVVL¿HG DWWKH³UHJLRQDOOHYHOURRWHGLQWKHVKDUHGVRFLDO heritage and similarity of historical evolution” (Singh, 2003). Examples are the Euro manage- ment model and the South East Asian manage- ment model. Multiple-dimensions models tend to abstract cultural elements into more cultural facets, such as Hampden-Turner and Trompenaars’ seven dimensions (Singh, 2003) and Hofstede’s ¿YHGLPHQVLRQV+RIVWHGH +RIVWHGH¶V¿YHGLPHQVLRQVKDYHEHHQXVHG in many studies in information systems (Myers 7DQ 7KH ¿YH GLPHQVLRQV DUH SRZHU distance, uncertainty avoidance, individual- ism-collectivism, masculinity-femininity, and long/short-term orientation (i.e., past-oriented or future-oriented). Believing that cultural values and cultural differences between countries have existed for a long time, are stable, and are based on cultural commonalities and similar histories, +RIVWHGH VXJJHVWHG FRXQWULHV FDQ EHFODVVL¿HG into six clusters: the Anglo cluster, Nordic cluster, German cluster, Latin cluster, Asian cluster, and Japan (Robbins & Stylianou, 2001). Virtual Community Types A number of studies have attempted to classify virtual communities. For instance, Armstrong DQG+DJHOLGHQWL¿HGIRXUJURXSVEDVHG on how communities meet different types of consumer needs. The four types of communities are communities of transaction, communities of interest, communities of fantasy, and communities of relationship. Communities of transaction aim to assist the selling and purchasing of products and services, information related to those transac- tions is also provided. Communities of interest involve more active interactions between members RQVSHFL¿FWRSLFV7KHGHJUHHRILQWHUSHUVRQDO communication is much higher compared to the communities of transaction. Communities of fantasy, as the name shows, enable members to create new stories in new environments, or even play imaginary characters. The heart of these kinds of communities is interaction with others. Communities of relationship are for people who want to form some deep personal connections. $ U P V W U RQ J D Q G+ D JHO¶V FO D V V L ¿F D W LR QK D V EH H Q widely used in many later studies. In contrast, Chaudhury et al. (2001) proposed that virtual communities can be divided into three types: ³\RX´³WKH\´DQG³LW´7KLVFDWHJRULVDWLRQZDV developed based on the member’s relationship types (one to one, one to many, or many to many) and organised form (e.g., formal or informal). 1633 An Exploratory Study of the Design Preferences of U.S. and Chinese Virtual Communities Members in each community have their own XQLTXH FKDUDFWHULVWLFV 0HPEHUV LQ WKH ³\RX´ based community are strongly attached to each other, and relationship is therefore their main IRFXV7KHJRDORISHRSOHZKRMRLQWKH³WKH\´ based community is to engage with several other members, to exchange opinions, jokes, and so IRUWKDQGWRVKDUHLQWHUHVW0HPEHUVLQWKH³LW´ based community are mostly task driven, and more interested in getting information or advice that serves their goal. %DVHGRQWKHVHWZRFODVVL¿FDWLRQPHWKRGVD FODVVL¿FDWLRQPRGHOFDQEHGHYHORSHGWRGH¿QH each type of community. Figure 1 shows how PHPEHUVFDQEHFODVVL¿HGLQWRHDFKJURXSEDVHG on the degree of their physical requirements (e.g., requirement for service, transaction, information, etc.) from the communities, and the degree of their interactions with other members (high or low). Web Site Design Web usability is important, as Web sites play an important role in virtual communities; in addition, users view the Web site and the virtual community D V W KH VD P H H Q W LW \D Q GH D FK RI W KH P L Q À XH Q F H V W KH user’s impression of the other (Preece, 2000). Several methods to assess the usability of Web sites can be found in the literature. Agarwal and Venkatesh (2002) present the Microsoft usability guidelines (MUG), which states that design ele- ments can be categorised into (1) content, (2) ease of use, (3) promotion, (4) made-for-the-medium, and (5) emotion. In another study, categories LGHQWL¿HGE\1LHOVHQ¶VUHVHDUFKDUHXVHG7KH\DUH (1) navigation, (2) response time, (3) credibility, (4) and content. In addition, this study added in an extra element, namely (5) media richness (Palmer, 2002). Similarly, content, navigation, )LJXUH&ODVVL¿FDWLRQPRGHO Physical Re q uirements Low High High Communities for Transaction & “It” based Communities C ommun i t i es f or I nterest & “They” Based Communities Communities for Relationship & “You” Based Communities Interaction C ommun i t i es f or F antasy . Tan Auckland University of Technology, New Zealand Helen J. Lin University of Auckland, New Zealand Cathy Urquhart University of Auckland, New Zealand ABSTRACT With the increasing popularity of electronic. similarities and differ- ences of e-mentoring when comparing formal and informal relationships. The traditional mentoring literature has investigated formal and informal programs and found informal. Personnel and Human Resource Management, 22, 39-124. Weisband, S. P., Schneider, S. K., & Connolly, T. (1995). Computer mediated communication and social information: Status salience and status