Can Our Group Survive? An Investigation of the Evolution of Mixed-Mode Groups

Journal of Computer-Mediated Communication

Can Our Group Survive? An Investigationof the Evolution of Mixed-Mode Groups∗

Chih-Hui Lai

School of Communication, the University of Akron, 105C Kolbe Hall, Akron, OH 44325

Applying an ecological and evolutionary perspective, this study examines the evolution and the sus-tainability of “mixed-mode groups,” a type of voluntary association created and organized online tointeract physically in geographically defined ways. Meetup.com is a website that facilitates the creationand coordination of mixed-mode groups. Analysis of interviews with 34 Meetup group organizersand a longitudinal analysis of 100 randomly selected Meetup groups revealed the evolutionary pro-cesses at the group and population level, respectively. Specifically, the ecological factor of populationdensity, the demographic factor of group age, the group’s profit orientation, experience of leadershipchange and shared leadership, and external ties played decisive roles in predicting group survival.Implications of the findings for theoretical and practical contributions are discussed.

Key words: mixed-mode groups, survival, voluntary associations, mixed modality, social network,ecology and evolution.

doi:10.1111/jcc4.12075

People are and always have been oriented towards involvement in voluntary organizations (Anderson1971; Rainie Purcell & Smith 2011). Participation in associational activities has long been linked to posi-tive outcomes at individual and collective levels such as creation of horizontal social networks and socialcapital (Putnam 2000) formation of social ties and occupational diversity (Davis Renzulli & Aldrich2006) and assimilation of democratic values and attitudes (Hooghe 2003). Voluntary associations arecharacterized by volitional involvement and specialization of interest; they are avocational in nature andare of secondary importance to an individual’s daily routine (Warner 1972). To some extent these char-acteristics highlight the challenges voluntary associations face (e.g relatively limited human and physicalresources) for growth and survival over time (Knoke & Prensky 1984).

Interestingly, usage of information and communication technologies (ICTs) has been shown toincrease the likelihood of individuals belonging to traditional local voluntary groups such as a neigh-borhood associations, sports leagues, youth groups, churches, or social clubs (Hampton, Lee, & Her,2011). Technology also contributes to the creation of new forms of voluntary associations, by integratingphysically based and virtual communities of interest (Blanchard & Horan, 1998). The sustainability ofvoluntary associations seems to have bearing on the intersection of online and physical spaces, a topicthat is socially significant but has thus far received little scholarly attention.

∗Accepted by previous editor Maria Bakardjieva

Journal of Computer-Mediated Communication 19 (2014) 839–854 © 2014 International Communication Association 839

Compared to face-to-face voluntary associations, groups created online tend towards a lower levelof participation due to easy entry and penalty-free exit. Existing research has treated the growth andsurvival of online groups, but focus has mostly been on those groups that communicate and organizeactivities online with occasional face-to-face interaction (e.g., Lazar & Preece, 2002; Postmes, Spears,& Lea, 2000). Given the possibility of linking online groups to physical spaces (Blanchard & Horan,1998), and the growing pattern of multimodal interpersonal and group behaviors (Baym, 2009), theinvestigation of voluntary associations that operate across physical and online spaces has become timely.This study aims to shed light on the sustainability of a particular type of voluntary association—groupsthat are created and organized online to interact physically in geographically defined ways. Consideringtheir mixed use of communication modalities (e.g., the Internet, face-to-face), diverse orientation (e.g.,for-profit vs. non-profit, networking, socializing, hobby-based, service), and varying type of structure(e.g., formal vs. informal, small groups and large organizations), these groups are labeled mixed-modegroups.

The term mixed-mode group derives from the concept of mixed-mode relationship (MMR), whichrefers to the pattern of initiating communication online and moving it offline for further action and inter-action (Walther & Parks, 2002). Examples of websites enabling the development of mixed-mode groupsare Facebook, Craigslist, Twitter, and Meeetup.com. Variations do exist among these mixed-mode groupwebsites. For instance, an argument could be made that usage of Facebook and Twitter is diverse as com-pared to Meetup.com, whose primary focus is the creation and organization of groups (based on sharedinterests and locations) that meet in a physical space. A Meetup group that engages in rock climbingactivities in the Boston area might serve as an example. To more precisely examine how mixed-modegroups evolve and traverse online and physical spaces, this study focuses on groups organizedon Meetup.com.

Like traditional voluntary associations, mixed-mode groups are characterized by face-to-face vol-untary involvement, specialization of interest, and low degree of organization. Further, both types ofvoluntary associations tend to be privately organized, avocational in nature, and of secondary impor-tance to an individual’s regular schedule. What distinguishes mixed-mode groups from their traditionalcounterpart is the capacity to organize grouping activities across different modalities, a capacity whichmay help facilitate group outcomes that span online and physical spaces. Additionally, the formation ofmixed-mode groups is driven by a combination of shared interests and locations. In contrast, then, withtraditional online groups, affiliation with which is wholly interest-based, mixed-mode group affiliationis contingent upon both common interests and place of residence.

Not surprisingly, mixed-mode groups inherit the vulnerabilities of both voluntary associations andonline groups. For example, the often transitory nature of mixed-mode groups increases the likeli-hood that they will exert only a minimal impact. Hence, examining the sustainability of mixed-modegroups can help us to identify and formulate solutions to maintain social dynamics through associationalactivities in contemporary society. An ecological and evolutionary framework was chosen to illustratethe evolutionary process of mixed-mode groups, as well as their interaction with their environment(which can take both online and offline forms). The ecological and evolutionary perspective examinesthe process of how groups and organizations pursue the goal of fitness through interacting with othercommunities and populations, by both developing communication infrastructures and by interactingwith the environment (Hannan & Freeman, 1989; Monge, Heiss, & Margolin, 2008).

In this paper, I first provide a review of the existing literature on the ecological and evolutionaryperspective in organizational and voluntary association contexts. This review leads to the development ofseveral hypotheses and one research question. I then describe the methods and procedures for analyzingarchived data and interviews collected from groups on Meetup.com. Finally, I discuss the results withinthe context of advancing evolutionary theories applied to mixed-mode groups.

840 Journal of Computer-Mediated Communication 19 (2014) 839–854 © 2014 International Communication Association

The Ecological and Evolutionary Perspective

Understanding the environment in which a social system is embedded is of paramount importance(Homans, 1950). Towards that goal, one needs to explore how a social organization is influenced bythe surrounding environment (selection), and how it acquires resources to adapt itself to the environ-ment (adaptation). These two lines of inquiry reflect the essence of the ecological and the evolutionaryperspective, respectively, that is, selection and adaptation, which are now seen as complementary to eachother, and which have been integrated in recent research (Baum & Shipilov, 2006).

A combined approach of ecological and evolutionary perspectives helps to explain how social andenvironmental conditions, as well as interaction within and among populations of organizations, influ-ence organizational founding, failure, and change (Baum & Shipilov, 2006). Specifically, the mechanismsof variation, selection, and retention (V-S-R) are integral to organizational change (Aldrich & Ruef, 2006;Campbell, 1965; McKelvey, 1982). Environmental forces and other organizations are potential sources ofvariation that might become challenges and opportunities for the focal organization. Over time, usefulvariations might be selected and retained as part of the organizational practices for survival.

According to Baum and Shipilov’s (2006) review, current ecological and evolutionary theory andresearch address four levels: intraorganizational ecology, demography of organizations, population ecologyof organizations, and community ecology. Intraorganizational ecology focuses on the V-S-R mechanismsenacted within organizations in the forms of strategic actions, rules, and norms, and explains how thesemechanisms influence the evolution and change of organizations. Demography of organization investi-gates the regularity of the rates of organizational founding, change, and failure within populations andexamines how these relate to organizational characteristics. Population ecology looks at the growth anddecline of individual populations and seeks to explain how the vital rates of one population are influ-enced by factors within the population, interactions with other populations, and environmental changes.Community ecology examines how the interaction among a set of populations influences the persistenceand stability of the community as a whole.

The ecological and evolutionary perspective has been applied in the context of traditionalface-to-face voluntary associations. McPherson (1983, 1988) proposes an ecological model of affiliationthat considers the influence of environmental factors (e.g., time, physical location, and sociodemo-graphic variables) on the survival of voluntary organizations. Compared to groups mainly interactingonline, mixed-mode groups are more likely to be subject to influence from outside the group, and tointeract with the social and physical environment external to the group. With its characteristic systemicanalysis of external and internal influences on the evolution of an organization or a group, the ecologicaland evolutionary perspective is highly suitable for providing a systematic understanding of how groups,operating across different media modalities, evolve over time. Building on Baum and Shipilov’s (2006)discussion and the multilevel feature of evolutionary theory, a set of hypotheses and one researchquestion have been developed with the aim of examining the ecology and evolution of mixed-modegroups at group and population levels.

The Ecological Processes of GroupsAt the population level, research has primarily targeted the ecological processes of organizations (e.g.,niche, density dependence) and the demography of organizations (e.g., age, size) (Baum, 1999). In eco-logical process terms, “niche” denotes the notion that organizations and populations possess variedcapacities to acquire resources and exploit these resources from the environment in order to survive(McKelvey, 1982; McPherson, 1983; Popielarz & Neal, 2007). The term “niche width” refers to an organi-zation’s variance in resource utilization; a dichotomy of generalists (with wide niche) and specialists (withnarrow niche) is posited accordingly (Hannan & Freeman, 1977). For example, narrow organizational


niches have been found to be positively correlated with mortality rates (Dobrev, Kim, & Hannan, 2001).A second ecological factor is population density. Density dependence theory explains the relationshipbetween competition and the number of organizations in a population, positing that increased compe-tition may contribute to failure rates at different stages of population development (Hannan & Freeman,1989; Hannan & Carroll, 1992). Indeed, an elevated intensity of competition has been found betweenorganizations with similar resource requirements (Hannan & Freeman, 1989; McPherson 1983). Forexample, intensity of competition rises between organizations located in the same geographic regionand targeting overlapping customers.

It appears that these two ecological factors (niche width and population density) are germane to theevolution of mixed-mode groups. Specifically, one would expect a positive correlation between range ofinterests and the likelihood that a mixed-mode group would survive over time, and a negative correla-tion between competition from other online and mixed-mode groups and the likelihood that it wouldsurvive. Wang, Butler, and Joyce’s (2006) study represents one of the few research efforts concerning thisarea in the online domain. They found a high attrition rate in groups that shared a great deal of con-tent with other groups (cross-posting groups) and that shared a large proportion of their members withother groups (membership overlap rate). These findings suggest that groups may compete with eachother indirectly in the larger online environment, in turn influencing the survival of the focal group.Due to the limited research on the ecology of mixed-mode groups, I made use of existing ecologicaland evolutionary work on formal organizations to develop two hypotheses that address the relationshipbetween these two ecological factors and the survival of mixed-mode groups:

H1: Width of group niche positively affects the survival of mixed-mode groups.

H2: Population density negatively affects the survival of mixed-mode groups such that groups thatexperience more competition will have lower rates of survival.

The Demography of GroupsParallel to the exploration of ecological factors, research has attempted to uncover the influence of dif-ferent organizational traits on organizational survival. For example, the liabilities of smallness (Aldrich& Auster, 1986) is a well-known demographic prediction that small organizations are, due to the dif-ficulty of acquiring necessary resources for growth and survival, predisposed to failure. Context mightplay a role, however; it has been argued that group size has less validity as a predictor of group survivalin the context of mixed-mode groups. On one hand, group size is often examined as a factor influencinggroup success in the online group literature. Rothaermel and Sugiyama (2001), for example, argue thatthe relationship between a virtual community’s size and its success is curvilinear; up to a certain point,the incremental addition of new members is positively related to the aggregate value of the commu-nity. Beyond a certain point, however, this increase dissipates. However, an argument can be made thatbecause online membership is easy to activate it may be, at least to some extent, deceptive. For example,a group of 500 members may only have 10 people attending face-to-face meetings regularly. In sucha situation, the association between group size and group survival is tenuous. Given this concern, theinfluence of group size on the survival of mixed-mode groups is not examined as a specific hypothesisin this study.

The influence of other organizational traits on organizational survival may, however, be applicable tomixed-mode groups. For example, the liability of newness (Freeman, Carroll, & Hannan, 1983) and theliability of adolescence (Fichman & Levinthal, 1991) suggest that younger organizations fail more oftenthan their more-established counterparts due to an inability to build a solid resource base necessary for


growth and survival. Fernandez (2008) studied traditional voluntary associations, and found that themajority of Spanish voluntary associations in Madrid closed due to mission completion and resourceinsufficiency (human and physical). Chambré and Fatt’s (2002) study on nonprofit AIDS organizationsalso found that new organizations closed due to the inability to secure stable funding sources, as well aslack of experience. Wollebæk (2009) reported that not-for-profit voluntary associations are more likelythan for-profit and well-organized organizations to rely on emotional attachment of members and lowcost of continued activity, both of which may prevent easy organizational disbanding. I propose twohypotheses that examine the positive relationships between these two demographic factors (age andnonprofit orientation) and group survival.

H3: Older mixed-mode groups are more likely than younger groups to survive.

H4: Not-for-profit orientation positively affects the survival of mixed-mode groups.

Group survival may also hinge on relational aspects such as leadership and configuration of net-works. Compared to traditional voluntary associations, mixed-mode groups are easier to create andorganize online. Yet in order to survive over time, groups may need a flexible and enduring leadershipstructure that can help them adapt to change, either within or outside the group. Such flexibility and sus-tainability may be represented through shared leadership and leadership change, which have been foundto be positively related to organizational outcomes and organizational survival (see, for example, Mehra,Smith, Dixon, & Robertson, 2006; Rowe, Cannella, Rankin, & Gorman, 2005). Specifically, shared lead-ership reflects the advantage of enhancing member commitment and contributing resources to the group(Carson, Tesluk, & Marrone, 2007) while leadership change is considered an effort by groups to learn howto adapt themselves to the environment (Tushman & Rosenkopf, 1996). The next hypothesis examinesthe positive relationship between these two leadership factors and group survival.

H5: Leadership factors affect the survival of mixed-mode groups such that groups with sharedleadership and the experience of leadership change are more likely to survive than those who donot experience shared leadership and leadership change.

Embeddness and SurvivalSurvival advantages for organizations also accrue from another relational factor: institutional embedded-ness. Embeddedness is the notion that economic actions of individuals and organizations are embeddedin social relations, and that this network of social relations among organizations affects the operationof each organization involved in the network (Granovetter, 1985; Uzzi, 1999). Such ties to the environ-ment can provide organizations with legitimacy and access to resources (Baum & Oliver, 1991, 1992;Baum, Calabrese, & Silverman, 2000). External ties have also been examined in the context of voluntaryassociation. For example, Fernandez (2008) found that those Spanish voluntary associations which wereembedded in collaborative networks of both dense and weak ties to the rest of the nonprofit organiza-tions in the same field (i.e., those possessing social capital) survived longer than those with less socialcapital (i.e., organizations without direct connections to other nonprofits). Similarly, Wollebæk’s (2009)study showed the positive effects of external ties (e.g., linkage with outside funding sources, contact witha municipality, and cooperation with other organizations) on the survival of voluntary organizations. Onthe basis of these few empirical studies on embeddedness and survival of voluntary associations placedin non-U.S. contexts, the last hypothesis is proposed:


H6: External ties positively affect the survival of mixed-mode groups.

In response to the call for identifying V-S-R mechanisms at different levels of analysis (groups, orga-nizations, populations, community) (Monge & Contractor, 2003; Monge & Poole, 2008), I pose a generalresearch question:

RQ: What are the evolutionary processes of mixed-mode groups in the form of V-S-R mechanismsat (a) the group and (b) the population level?

Methods

The research site of this study was Meetup.com, an organization designed to facilitate the formation andcoordination of mixed-mode groups. Meetup.com fits the needs of this study because it is the largestnetwork of local voluntary groups in the world (over 140,000 local groups, 15 million users), and because,unlike similar services such as Craigslist and Facebook, it contains a complete history of group structuresand activities, both online and offline. The data were drawn from a longitudinal analysis of 100 randomMeetup groups over 18 months of observation and in-depth interviews conducted with 34 Meetup grouporganizers. The choice of these two sources of data reflects the cross-level conceptualization enabled inthe ecological and evolutionary perspective. Organizers’ account of their groups provided insight intothe evolution of individual groups while archived data of 100 groups helped explain the change of apopulation of groups over time.

Data Collection and Analysis: Archived Group DataA random sample of 100 Meetup groups was retrieved with the assistance of the research unit ofMeetup.com and was observed over an 18-month follow-up period from 1 August 2009 to 1 February2011.1 On the webpage of each Meetup group, basic information about the group is listed, includinggroup description, group topics, time of creation, membership size, organizer and/or assistant orga-nizers, number and details of group events (e.g., content of activities, locations, cooperating groupsor organizations). Related to RQ(b) and six hypotheses, operationalizations of the key variables aredetailed as follows.

Group niche was measured by member requirements. Referencing Baum and Singh’s (1994) defini-tion of organizational niche based on the ages of children that day care centers are licensed to enroll,member requirements were used to measure the niche of a Meetup group. A group was coded 1 (narrowniche) if it had specific demographic requirements (i.e., gender, age, marital status, ethnicity and race,language), professional orientation (i.e., occupation, professional status) and others (i.e., specific socialroles), and coded 2 (wider niche) if no requirements existed. Efforts were made to review the groupdescription and group events to determine the profit orientation of a group. If the group sold productsassociated with the organizer’s own business (e.g., dancing class, coaching services, PR training services),then this group was coded as for-profit (code= 1). Otherwise, it was coded as not-for-profit (code= 2).

Leadership change was examined on the basis of the bio page of the group organizer. If the timehe/she was listed as organizer differed from the time the group was created, the group was coded asexperiencing leadership change (code= 2). Otherwise, a group was coded as without leadership change(code= 1). Leadership team was measured by going over the information listed under the organizersection of each Meetup group. If only the organizer was listed, then the group was coded as without aleadership team (code= 1). If a number of organizers, assistant organizers and/or event organizers werelisted, it was coded as having a leadership team (code= 2).2


A content analysis of each group event formed the basis of the evaluation of external ties. In the eventsection, if a group mentioned contacts outside of the group, such as other Meetup or non-Meetup groupsas part of the group event, other organizations listed as the sponsor or the recipient of the event, or guestspeakers invited from outside for group event, the group was coded as with external ties (code= 2).Otherwise, it was coded as without external ties (code= 1). These different external ties were furthercoded into 22 types of organizations and groups, which will also be used in the analysis reported later.3

A high degree of interrater reliability was attained for coding these five variables, with Cohen’s Kapparanging from 0.85 to 0.97. Last, population density was obtained by recording the number of Meetupgroups within a radius of 25 miles (Density I) and 10 miles (Density II) using the search function onMeetup.com. These two distances represent the default search parameters on Meetup.com. The two vari-ables were analyzed after being log-normalized to better approximate a normal distribution.

Geographic factors in the forms of urban proximity, residential density, and population change havebeen found to be linked to growth and survival of voluntary associations (see, for example, McPherson,1988; Wollebæk, 2009). Hence, local population size and residential mobility were included as the controlvariables. Using the location in which a Meetup group is listed (e.g., Boston, MA), information about localpopulation size and residential mobility was retrieved from U.S. Census Bureau’s online database (i.e.,2009 estimate and 2005–2009 community survey).4 To test the hypotheses, Cox regression analysis wasused.5 Group survival was the censoring variable that indicates whether the group is still alive at the endof the study (1=No, 0=Yes).

Data Collection and Analysis: InterviewsAmong the 34 participating organizers, 14 group organizers were selected from 100 randomly sam-pled groups, which were provided by the research unit of Meetup.com. All of the organizers of these100 groups were contacted through the contact function of Meetup.com, but only 14 organizers werefollowed up and participated in the interview. In addition to the random sample, interviews were con-ducted with another 20 group organizers who were selected through purposive sampling.6 Interviews,which were semistructured and conducted mainly over the phone, ranged in length from 14 to 114 min-utes (M = 39.67, SD= 22.04). The initial interviews took place from July 2009 through January 2010, but10 organizers were followed up through July 2011 after observing conspicuous group development (e.g.,group closure, spin-off groups).

All of the 30 audio-recorded interviews were transcribed. The transcripts, including the four inter-views that were not audio-recorded, were entered in ATLAS ti and analyzed through a series of codingprocesses (Strauss & Corbin, 1990).7 Note that because interviews were conducted mostly following theorder and structure of the questions as listed in the protocol, the decisions of where to code and whichcodes to apply were relatively straightforward, and so were the comparisons of interviewees’ responsesunder different categories.8 RQ(a) was answered through the query tool provided by the ATLAS. ti com-puter program, which searched the entire corpus for the sentences and paragraphs of quotes that hadbeen coded with the established categories.

Results

The Evolutionary Process of Meetup PopulationAfter 18 months of observation, 46 out of 100 Meetup groups were found to have closed down. That is, 46groups were uncensored (experienced the target event, group closure) while the rest were right-censored(did not experience the target event). This percentage of censoring (54%) was considered acceptablein ensuring reasonable statistical power (Singer & Willett, 1991). Since all of the 100 groups were


Table 1 Results From Cox Analysis

Model 1 Model 2

B Sig. Exp(B) B Sig. Exp(B)

Local Population Size −.077 .615 .926 .025 .908 1.025Residential Mobility .020 .349 1.021 .037 .160 1.037Density I (log)∗ .953 .058 2.592Density II (log) −.724 .120 .485Member Requirements .197 .607 1.218Non-Profit Orientation −1.614 .000 .199External Ties −1.935 .000 .144Leadership Team −1.094 .028 .335Leadership Change (lagged)† −1.455 .001 .233−2 log-likelihood 326.369 257.978G2 68.391 .000

Note. Significant predictors and their coefficients are identified in boldface.The positive B coefficient (with odds ratios above 1) implies an increase in the probability of groupclosure. G2 refers to the value of chi-square change from Model 1 (with locale and residential mobilityonly) to Model 2, in this case, G2 = 68.391, p= .000, R2 = 1 - e^((−68.391) /100)= 0.495, indicating thestrength of association between the set of covariates and survival time (Allison, 1995). Allison, P. D.(1995). Survival analysis using the SAS system: A practical guide. Cary, NC: SAS Institute Inc.∗The relationship between population density and group survival was a directional hypothesis, hencethe coefficient was significant at p= .058 (2-tailed significance).†Leadership change was transformed with a lagged form to avoid the problem of simultaneity.

observed as intact cases, no left-censoring occurred. Among the 46 groups that closed down, 38 groups(82.6%) were aged one year or younger. A significant age difference was found between ongoing groups(M = 40.91, SD= 22.06) and defunct groups (M = 15.04, SD= 11.67) (t(83)= 7.48, p< .001); H3 wasthus supported, suggesting that older groups had a greater likelihood of survival than younger groups.To test the rest of the hypotheses, all the variables were entered in the Cox regression model. Theresults revealed that the number of other Meetup groups existing within a radius of 25 miles (H2)(B= .953, p= .058), with a not-for-profit orientation (H4) (B=−1.614, p< .001), leadership team(B=−1.094, p< .05), the experience of leadership change (H5) (B=−1.455, p< .01), and externalties (H6) (B=−1.935, p< .001) significantly influenced group survival (see Table 1). In other words,proximity to other Meetup groups increased the probability of group closure. On the other hand, anot-for profit orientation, the existence of a leadership team with the experience of leadership change,and possession of external ties reduced the probability of group closure. Member requirement wasnot a significant predictor of survival time (H1) (B= .197, p> .10). Hence, all hypotheses, with thesingle exception of H1, were supported. Due to space limitations, the survival function (a graphicalrepresentation of the cumulative survival distribution) is not shown in the paper. Based on the survivalfunction, at the mean of the predictors, the survival rates of a group at 1-year, 2-year, and 3-yearthresholds were 88%, 73%, and 65%, respectively.

Does, then, the evolutionary process of Meetup groups at the population level reflect the V-S-Rmechanisms (RQb)? The above-noted results suggest that it does. Specifically, variations were observedto occur in different dimensions, including group niche, population density, group age, group type,


Figure 1 Two-mode external networks of survival groups. The red circles are the Meetup groups thatsurvived at the end of observation and the blue boxes represent different types of external ties that sur-viving groups had connections with.

leadership factors, and network configurations. Over time, older and not-for-profit groups livingunder low-population density, surviving with a leadership team with an experience of leadershipchange, and maintaining external ties with other groups or organizations (be they inside or outsidethe population of Meetup groups), were more likely to be selected and retained within the populationof Meetup groups. A visualization was drawn using NetDraw (Figure 1), which illustrated that localbusinesses were the most-cited source of external ties by surviving groups, followed by local nonprofitorganizations, national and international nonprofit organizations, and local voluntary organizations.Within Meetup.com, groups with goals such as socializing, pursuit of hobbies, and sports and recreationwere common targets for collaboration.

The Evolutionary Process of Meetup GroupsAnalysis of interview data revealed the evolutionary processes of groups (RQa). Specifically, the V-S-Rmechanisms were represented in different aspects of internal group processes as well as external inter-action with the environment. When a group was first created, organizers focused mainly on recruitmentand advertising; the strategies they used included a combination of traditional word-of-mouth andunique online search affordances. For example, an organizer of a philosophy group (MDThinkGroup1) described his multimodal advertising efforts:

I know when I talk with them, they, of course, I tell them about my group and a lot of groups and alot of people join, ‘cause we do some cool things. So, just pretty much, other than the Meetup page,I’ve talked to people at other Meetup groups.

As groups developed, the strategies that organizers found initially useful might be selected andretained as part of organizing routines, or subjected to later modifications. The organizer of a walkgroup (MIWalkGroup) mentioned that instead of actively contacting prospective members through


numerous e-mails, she later relied on the search function provided on Meetup.com to do the workfor her to attract members. It appears that the technological affordances of search engines played apivotal role in determining the niche a group could occupy in the population. The organizer of a socialphilosophy group (OHThinkGroup) mentioned the effect of online search engine functionality on thegrowth of the group:

And the bigger we get, the easier it is to search us. Because more and more people talkabout the group, then they find Meetup and they keep using words that will pull outfor a search engine. And that makes it easier for people to then find our group throughthese words that they use. They don’t even realize they’re doing it.

Different organizing structures took shape, depending on the nature of group topic. In groups withfocused activities (e.g., concert going or rock climbing), help from assistant organizers was minimal,since the organizer could easily handle the planning and organizing work. In groups whose activitieswere diverse (e.g., social groups), organizers used the expertise of their assistant organizers in a varietyof ways. If no help was available from inside the group, organizers would solicit help from their per-sonal networks, such as workplace colleagues or friends, at least to generate ideas for events. It is worthmentioning that among the 34 participating organizers, 17 were not the originators of their groups. Yet,thanks to the selected and retained strategies, those groups were able to sustain themselves with routineself-organizing accomplished by several assistant organizers, even when the organizer left.

It seems that the personal relationships that were observed to develop among members might haveserved as a motivation for members to continue participating in group activity. As some organizerspointed out, though, these relationships sometimes led to a shift of communication and activity awayfrom the group level to a smaller and more private level—these members no longer attended group meet-ings. In response to this issue, organizers sometimes created subgroup activities. For example, membersof a women’s social group (ORWSocialGroup) organized among themselves a separate dancing Meetupgroup. The organizer of a language group (CAESLGroup) witnessed this pattern in her group, but shechose to refrain from responding to it.

Organizers reported that they were well received in local venues, and some groups were activelysought out by local businesses. It was not uncommon for local establishments to reserve meeting spacefor groups or provide them with group discounts. An organizer of a new technology group (COTech-Group) had local businesses that reached him through Meetup.com serve as group sponsors. Relation-ships with these businesses varied in nature; depending on the group, the connection might turn out tobe a one-time business transaction, with no deeper ties cultivated.

Certain groups organized joint events with other Meetup groups on the basis of direct mutual ties.That is, if multiple Meetup groups shared organizers or assistant organizers, these individuals wouldeither cross-post events on both groups’ pages or organize events together. Locale and characteristics ofthe group also played a part in the initiation and implementation of joint events. For example, an orga-nizer of a classics book club (MIBookGroup) mentioned that she was welcomed by the local communityand was contacted by local organizations (e.g., the library). Another organizer of an adventure group(MIADGroup) described her personal links with other local cultural groups that facilitated intergrouplinks:

I go to the tabling events that all the clubs and organizations have every year, which ishow I found them. And then because they’re closer to my age and they are just asactive – and basically invited them to some of the meetups, or we do our own thing withthem.


In sum, findings from the interviews suggest that Meetup group organizers engaged in V-S-R pro-cesses at different stages of group development to build and strengthen the fitness of the group. At thegroup-formation stage, online and offline recruitment efforts were made; later, connections for logis-tic arrangements were built both within and outside of the group. In turn, these connections resultedin various advantages and disadvantages: group transition as a result of leadership change, formation ofsubgroup activities and/or spin-off groups due to the development of personal relationships, joint eventswith other groups, and interaction with local communities.

Discussion

Applying an ecological and evolutionary perspective to understand the growth, survival, and disbandingof mixed-mode groups, this study extends the existing evolutionary research, which mainly treats formaland well-structured organizations, to the domain of technology-mediated voluntary associations. Thereare similarities between the ecological and evolutionary processes of mixed-mode groups and those thathave been previously studied. For example, results of age-dependence and group survival are consistentwith the prediction of “liability of newness” as explored in work and traditional face-to-face voluntaryorganizations (e.g., Fernandez, 2008; Hager, Galaskiewicz, & Larson, 2004). The positive effects of sharedleadership and leadership change on survival of mixed-mode groups are also reported in existing studieson work organizations (e.g., Carson et al., 2007; Mehra et al., 2006; Rowe et al., 2005).

Consistent with research demonstrating the usefulness of institutional embeddedness and interor-ganizational linkages for organizational survival (Baum et al., 2000; Selle & Øymyr, 1992), this study’sfindings point to the key role played by external ties in the growth and survival of mixed-mode groupsat group and population levels. Specifically, the network visualization shown in Figure 1 demonstratesthat Meetup groups tend to have interorganizational links with other Meetup groups as well as with localorganizations; these links can provide sources of networking and collaboration and contribute to groupsurvival. Similarly, analysis of the interview data also suggests that group organizers engage in differentways to build and strengthen their fitness over time through cooperation with other Meetup groups, aswell as by interacting with local establishments and the community. This study enriches the ecologicaland evolutionary perspective by considering the technological affordances of mixed-mode commu-nication and organizing. That is, the environment of those Meetup groups can take both online andoffline forms, from which groups build and maintain their communication infrastructures and acquireresources for operation.

In fact, the result of a nonsignificant effect of group niches (measured by member requirementsfor group topics) on survival raises the question of the applicability of the measures used in existingecological and evolutionary research to mixed-mode groups. Niche refers to the varied capacities thatorganizations or populations possess to procure resources and exploit these resources in the environ-ment (McKelvey, 1982; McPherson, 1983; Popielarz & Neal, 2007). Future research is needed to providea more fine-grained conceptual and methodological approach to investigating the multimodal resourceenvironment of mixed-mode groups. For example, search engines were commonly mentioned by inter-viewed organizers as a useful mechanism for deciding how groups attract potential members. It suggeststhat niches of a mixed-mode group may be better measured by group topics as well as the online search-able range within which a group can recruit members.

The advantage of the ecological and evolutionary perspective is its ability to explain phenomenausing the same theoretical process at different levels (Monge et al., 2008). The cross-level conceptual-ization also allows for the investigation of V-S-R processes enacted within and outside the organization(Aldrich & Ruef, 2006; Monge et al., 2011a). Interview data revealed that Meetup group organizers were


involved with different aspects of group development, including recruitment, leadership issues, andchoice and location of activities. In other words, group organizers play a pivotal role in influencing theinternal evolutionary process of the group. Indeed, as Miner (1994) points out, an organizational man-ager’s job is to monitor how the evolutionary processes at the higher level affect the whole organization,and to influence the internal evolutionary process. The behavior of the Meetup group organizers understudy exemplified this description.

In response to a call for more efforts to make the level of analysis as explicit and inclusive as possible(Monge & Contractor, 2003), this study used a mixed approach of interviews and archived group data,which afforded me the ability to articulate which level of the ecosystem is being investigated. Regardinggroup disbanding, cost was a major reason singled out by a number of participating organizers leadingto the decision for group closure. For example, two organizers (NJPRGroup & NMChannelingGroup)explained that they closed their groups on Meetup.com because they did not find a Meetup presencehelped achieve their set goals to recruit new members to their existing business activities. Another orga-nizer of a sports watching group (COSportsGroup) mentioned that her group migrated to Facebook,another population of mixed-mode groups, because it costs nothing, whereas she paid the subscriptionfees to Meetup.com as the single organizer of her group. The traits of these “less fit” individual groupsmay together reflect the niche attributes at the population level of Meetup.com. It can be argued thatMeetup.com is carving out its macropopulation niche and coexists with other free-of-charge populationsof mixed-mode groups, such as Facebook and BigTent, in the larger environment. Further, the selectionevent of group closure on Meetup.com and group creation in another population can be described asa cross-level V-S-R process, because the selection at the lower group level reflects the adaptations andtransformations at the higher level of populations (Monge et al., 2011b).

On the basis of this multilevel conceptualization of evolutionary processes, future research mightexamine how different populations of mixed-mode groups interact with each other in the form of com-mensalism; that is, how organizations or groups from similar populations engage in competition and/orcooperation with one another (Aldrich & Ruef, 2006; Monge & Contractor, 2003). Another avenue ofinquiry might be the phenomenon of group migration among similar (e.g., from Meetup.com to Face-book) or dissimilar populations (i.e. from Meetup.com to a business networking website) as this wouldprovide insight into the evolutionary dynamic at group, population, and community levels.

Conclusion

This study is limited in three ways. First, analyses from interviews and archived data did not differ-entiate the reasons for group decline and closure; caution should thus be used when interpreting theresults. Second, because the study drew on interviews with group organizers using Meetup.com, findingsmay be biased, as the participating organizers were likely to be successful organizers. Extra efforts weremade, however, to prompt the organizers to share their thoughts about the less active groups they orga-nized. Third, the evolution of Meetup groups may not adequately represent the general phenomenon ofmixed-mode groups. Future research would do well to encompass different populations of mixed-modegroups.

Despite these shortcomings, this study makes a major contribution to the understanding of the sus-tainability of mixed-mode groups by viewing the issue through an ecological and evolutionary lens.Overall, the results of this study are convergent with existing research on organizational ecology andevolution, suggesting that factors such as population density, group age, profit orientation, leadership,and external links are vital to predicting the survival of mixed-mode groups. The cross-level conceptu-alization allows for interpretation that the V-S-R processes can take place across group and population


levels. Most importantly, considering technological affordances of mixed-mode communication andorganizing, this study sheds light on the role of technology in facilitating the organization of voluntaryassociations in different phases of evolution, such as the effortless accomplishment of online recruitmentand the initiation of collaboration with other groups and organizations, be they online or offline. Thegrowing use of the Internet for face-to-face and geographically-defined grouping activities demands thatthe phenomenon of mixed-mode groups will both garner attention and spur future research.

Acknowledgements

The author would like to thank James Katz, Marya Doerfel, Jennifer Gibbs, and two anonymous reviewersfor their most helpful comments and invaluable feedback on the earlier drafts of this manuscript

Notes

1 These 100 groups were randomly selected from the database of all the ongoing groups listed underMeetup.com when the request was made.

2 The assumption that groups coded with no leadership team had no leadership team before was basedon a pilot study observing another 12 Meetup groups over 8 months.

3 Groups and organizations involved in group events were defined as external ties. In total, 22 types ofexternal ties were identified, including academic organization, local business,state/national/international business, individuals, media organization, Meetup social group, Meetupart and entertainment group, Meetup business and career group, Meetup cultures and languagesgroup, Meetup education group, Meetup hobbies group, Meetup parenting and family group, Meetupreligion and beliefs group, Meetup sports and recreation group, local non-profit organization, statenon-profit organization, national/international non-profit organization, political organization,public agency, local voluntary organization, state voluntary organization, and national/internationalvoluntary organization.

4 Local population size was further classified based on the four categories of metropolitan statisticalareas (MSAs) (http://www.census.gov/population/www/metroareas/mastand.html), that is, Level AMSAs corresponding with 1 million or more local population, Level B MSAs with 250,000 to999,999, Level C MSAs with 100,000 to 249,999, and Level D MSAs with less than 100,000. Thelocale data related to the 100 random groups represent 42% of Level D MSAs, 18% of Level C, 23%of Level B, and 17% of Level A.

5 External ties, leadership team and leadership change (in lagged form) variables were analyzed ascovariates representing “state” in the Cox regression model. These variables were meant to indicatewhether a group has ever experienced the target event, that is, whether a group has constructed anexternal tie, has shared leadership, or has experienced leadership change over the course of groupdevelopment. Thus they were not recorded at various points in time. Two assumptions related to Coxregression analysis were tested. First, squared multiple correlations (SMC) were conducted to checkfor evidence of multicollinearity. No SMC exceeded the recommended threshold of .90 (Tabachnick& Fidell, 2001); thus it was concluded that the variables under study were nonredundant. Theassumption of proportional hazards required in the Cox regression model was also tested by addingto the model interaction of time with all the variables, and then assessing the effect of theseinteractions (Tabachnick & Fidell, 2001). None of the covariates significantly interacted with time.Hence, it was considered that the assumption of proportionality was not violated. Tabachnick, B. G.,& Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Boston: Allyn & Bacon.


6 Please refer to the author’s other paper for more details about the implementation of purposivesampling and details about these interviewed groups. Lai, C.–H. (2014). Understanding theevolution of bona fide mixed-mode groups: An example of Meetup groups.First Monday, 19(1).Available at: http://firstmonday.org/ojs/index.php/fm/article/view/4681/3810

7 In addition to the 30 interviews, three other interviews were completed via email upon theparticipants’ request, and one face-to-face interview was performed without the use of the recordingdevice due to ambient interruptions.

8 The interview protocol and the coding categories are available upon request.

References

Anderson, R. T. (1971). Voluntary associations in history. American Anthropologist, 73(1), 209–222.Aldrich, H. E., & Auster, E. R. (1986). Even dwarfs started small: Liabilities of age and size and their

strategic implications. Research in Organizational Behavior, 8, 165–198.Aldrich, H. E., & Ruef, M. (2006). Organizations evolving (2nd ed.). London, UK: Sage.Baum, J. A. C. (1999). Organizational ecology. In S. R. Clegg & C. Hardy (Eds.), Studying organization

theory and method (pp. 71–108). London: Sage.Baum, J. A. C., Calabrese, T., & Silverman, B. S. (2000). Don’t go it alone: Alliance network

composition and startups’ performance in Canadian biotechnology. Strategic Management Journal,21(3), 267–294.

Baum, J. A. C., & Oliver, C. (1991). Institutional linkages and organizational mortality, AdministrativeScience Quarterly, 36, 187–218.

Baum, J. A. C., & Oliver, C. (1992). Institutional embeddedness and the dynamics of organizationalpopulations. American Sociological Review, 57(4), 540–559.

Baum, J. A. C., & Shipilov, A. V. (2006). Ecological approaches to organizations. In S. R. Clegg, C.Hardy, W. Nord, & T. Lawrence (Eds.), Sage handbook for organization studies (pp. 55–110).London: Sage Publications

Baum, J. A. C., & Singh, J. V. (1994). Organizational niche overlap and the dynamics of organizationalfounding. Organization Science, 5, 483–501.

Baym, N. K. (2009). A call for grounding in the face of blurred boundaries. Journal ofComputer-Mediated Communication, 14, 720–723.

Blanchard, A., & Horan, T. (1998). Virtual communities and social capital. Social science computerreview, 16(3), 293–307.

Campbell, D. T. (1965). Variation and selective retention in socio-cultural evolution. In H. R.Barringer, G. I. Blanksten, & R. W. Mack (Eds.), Social change in developing areas: Areinterpretation of evolutionary theory (pp. 19–48). Cambridge, MA: Schenkman.

Carson, J. B., Tesluk, P. E., & Marrone, J. A. (2007). Shared leadership in teams: An investigation ofantecedent conditions and performance. Academy of Management Journal, 50, 1217–1234.

Chambré, S. M., & Fatt, N. (2002). Beyond the liability of newness: Nonprofit organizations in anemerging policy domain. Nonprofit and Voluntary Sector Quarterly, 31, 502–524.

Davis, A. E., Renzulli, L. A., & Aldrich, H. E. (2006). Mixing or matching? The influence of voluntaryassociations on the occupational diversity and density of small business owners’ networks. Workand Occupations, 33, 42–72.

Dobrev, S. D., Kim, T.-Y., & Hannan, M. T. (2001). Dynamics of niche width and resource partitioning.The American Journal of Sociology, 106(5), 1299–1337.

Fernandez, J. J. (2008). Causes of dissolutions among Spanish nonprofit associations. Nonprofit andVoluntary Sector Quarterly, 37, 113–137.


Fichman, M., & Levinthal, D. A. (1991). Honeymoons and the liability of adolescence: A newperspective on duration dependence in social and organizational relationships. Academy ofManagement Review, 16, 442–468.

Freeman, J. H., Carroll, G. R., & Hannan, M. T. (1983). The liability of newness: Age dependence inorganizational death rates, American Sociological Review, 48, 692–710.

Granovetter, M. S. (1985). Economic action and social structure: The problem of embeddedness.American Journal of Sociology, 91(3), 481–510.

Hager, M. A., Galaskiewicz, J., & Larson, J. A. (2004). Structural embeddedness and the liability ofnewness among nonprofit organizations. Public Management Review, 6(2), 159–188.

Hampton, K. N., Lee, C-J., & Her, E. J. (2011). How new media affords network diversity: Direct andmediated access to social capital through participation in local social settings. New Media &Society, 13(7), 1031–1049.

Hannan, M.T., & Carroll, G. R. (1992). Dynamics of organizational populations: Density, competition,and legitimation. New York: Oxford University Press.

Hannan, M. T., & Freeman, J. H. (1977). The population ecology of organizations. American Journal ofSociology, 82, 929–64.

Hannan, M. T., & Freeman, J. (1989). Organizational ecology. Cambridge, MA: Harvard UniversityPress.

Homans, G. C. (1950). The human group. New York: Harcourt, Brace.Hooghe, M. (2003). Participation in voluntary associations and value indicators: The effect of current

and previous participation experiences. Nonprofit and Voluntary Sector Quarterly, 32, 47–69.Knoke, D., & Prensky, D. (1984). What relevance do organization theories have for voluntary

associations? Social Science Quarterly, 65, 3–20.Lazar, J., & Preece, J. (2002). Social considerations in online communities: Usability, sociability, and

success factors. In H. van Oostendorp (Ed.), Cognition in a digital world (pp. 127–152 ). Mahwah:NJ: Lawrence Erlbaum Associates Inc. Publisher.

McKelvey, B. (1982). Organizational systematics. Berkeley: University California Press.McPherson, J. M. (1983). An ecology of affiliation. American Sociological Review, 48(4), 519–532.McPherson, J. M. (1988). A theory of voluntary organization. In C. Milofsky (Ed.), Community

organizations: Studies in resource mobilization and exchange (pp. 42–76). New York: OxfordUniversity Press.

Mehra, A., Smith, B., Dixon, A., & Robertson, B. (2006). Distributed leadership in teams: The networkof leadership perceptions and team performance. Leadership Quarterly, 17, 232–245.

Miner, A. S. (1994). Seeking adaptive advantage: Evolutionary theory and managerial action. In J. A. C.Baum & J. V. Singh (Eds.), Evolutionary dynamics of organizations (pp. 76–89). New York, NY:Oxford University Press.

Monge, P. R., & Contractor, N. S. (2003). Theories of communication networks. Oxford: University Press.Monge, P. R., Heiss, B. R., & Margolin, D. (2008). Communication network evolution in organizational

communities. Communication Theory, 18, 449–477.Monge, P., Lee, S., Fulk, J., Frank, L. B., Margolin, D., Schultz, C., . . .Weber, M. (2011a). Evolutionary

and ecological models for organizational communication. In V. Miller, M. S. Poole, D. R. Seibold &Associates (Eds.), Advancing research in organizational communication through qualitativemethodology, Management Communication Quarterly, 25(1), 26–34.

Monge, P., Lee, S., Fulk, J., Weber, M., Shen, C., Schultz, C., . . . Frank, L. B. (2011b). Research methodsfor studying evolutionary and ecological processes in organizational communication. ManagementCommunication Quarterly, 25(2), 211–251.


Monge, P. R., & Poole, M. S. (2008). The evolution of organizational communication. Journal ofCommunication, 58(4), 679–692.

Popielarz, P. A., & Neal, Z. P. (2007). The niche as a theoretical tool. Annual Review of Sociology, 33,65–84.

Postmes, T., Spears, R., & Lea, M. (2000). The formation of group norms in computer-mediatedcommunication. Human Communication Research, 26(3), 341–371.

Putnam, R. D. (2000). Bowling alone: The collapse and revival of American community. New York:Simon & Schuster.

Rainie, L., Purcell, K., & Smith, A. (2011). The social side of the internet. Pew Internet & American LifeProject. Retrieved January 25, 2011, fromhttp://www.pewinternet.org/Reports/2011/The-Social-Side-of-the-Internet.aspx

Rothaermel, F. T., & Sugiyama, S. (2001). Virtual internet communities and commercial success:Individual and community-level theory grounded in the atypical case of TimeZone.com. Journal ofManagement, 27(3), 297–312.

Rowe W., Cannella, A., Rankin, D., & Gorman, D. (2005). Leader succession and organizationalperformance: Integrating the common-sense, ritual scapegoating, and vicious-circle successiontheories. The Leadership Quarterly, 16, 197–219.

Selle, P., & Øymyr, B. (1992). Explaining changes in the population of voluntary organizations: Theroles of aggregate and individual level data. Nonprofit and Voluntary Sector Quarterly, 21(2),147–179.

Singer, J. D., & Willett, J. B. (1991). Modeling the days of our lives: Using survival analysis whendesigning and analyzing longitudinal studies of duration and the timing of events. PsychologicalBulletin, 110, 268–290.

Strauss, A., & Corbin, J. (1990). Basics of qualitative research. Thousand Oaks, CA: Sage.Tushman, M. L., & Rosenkopf, L. (1996). Executive succession, strategic reorientation and performance

growth: A longitudinal study in the US cement industry. Management Science, 42(7), 939–953.Uzzi, B. (1999). Embeddedness in the making of financial capital: How social relations and networks

benefit firms seeking finance. American Sociological Review, 64, 481–505.Walther, J. B., & Parks, M. R. (2002). Cues filtered out, cues filtered in: Computer mediated

communication and relationships. In M. L. Knapp, J. A. Daly & G. R. Miller (Eds.), The handbookof interpersonal communication (3rd ed., pp. 529–563). Thousand Oaks, CA: Sage.

Wang, X., Butler, B., & Joyce, E. (2006). An ecological perspective on online communities. InProceedings of Academy of Management (pp. I1–I6). New York: Academy of Management.

Warner, W. K. (1972). Major conceptual elements of voluntary associations. In D. H. Smith, R. D.Reddy, & B. R. Baldwin (Ed.), Voluntary action research: 1972 (pp. 71–80). Lexington, Mass:Lexington Books.

Wollebæk, D. (2009). Survival in local voluntary associations. Nonprofit Management and Leadership,19, 267–284.

About the Author

Chih-Hui Lai (PhD, Rutgers University) is an Assistant Professor in the School of Communication at theUniversity of Akron. Her research interests focus on the intersection of technology use, organizationalcommunication, and voluntary groups.Address: School of Communication, the University of Akron, 105C Kolbe Hall, Akron, OH 44325.E-mail: [email protected]


Can Our Group Survive? An Investigation of the Evolution of Mixed-Mode Groups

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