Networks, Disrupted: Media Use as an Organizing Mechanism for Rebuilding

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DOI: 10.1177/1461444813505362

published online 24 September 2013New Media SocietyMarya L Doerfel and Müge Haseki

Networks, disrupted: Media use as an organizing mechanism for rebuilding

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Networks, disrupted: Media use as an organizing mechanism for rebuilding

Marya L Doerfel and Müge HasekiRutgers University, USA

AbstractLongitudinal interorganizational relationships in New Orleans are used to assess the ways in which organizations employed information and communication technologies to (re)connect to their social networks and with what impact regarding post-disruption capacity building. Findings reveal tensions in old and new media use and that using multiple media is an organizing mechanism that improves rebuilding efficiency and effectiveness. Specifically, using mixed media, more so than any one old or new media, facilitated bridging and bonding social capital to expand network capacity. An Organizational Media Spectrum model integrates media intimacy, familiarity, and network capacity to illustrate the relationship between media strategies and organizing processes for building capacity in social networks.

KeywordsDisaster, interorganizational networks, network disruption, old and new media, social capital

As new information and communication technologies (ICTs) emerge, established modes are not necessarily replaced; however, tensions between the established and new media may arise (Dimmick et al., 2011). The tensions between old and new technologies and their impacts on communication patterns among individuals is an ongoing source of new media theorizing (cf., Marvin, 1988). At the organization level, where evolving relation-ships are built and maintained through collaborative endeavors, potential tensions and impacts on relationships are of similar concern – organizational partners’ interdependence

Corresponding author:Marya L Doerfel, School of Communication and Information, Rutgers University, 4 Huntington Street, New Brunswick, NJ 08901, USA. Email: mdoerfel@rutgers.edu

505362 NMS0010.1177/1461444813505362Doerfel and Hasekinew media & societyresearch-article2013

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necessitates that ICT use be a shared and social contract about how to stay in touch. In broader interorganizational relationships (IORs), then, system-level patterns may be influenced by the established and new technologies, much like tensions Marvin and others articulated when individuals’ social practices simultaneously adopt and adapt with ICTs.

One way tensions get amplified is during network disruptions. In the time immedi-ately following the 9/11 attacks in the US, for example, mobile phone use became a source for accessing information when other ICTs failed (Katz and Rice, 2002). Similarly, following the US Gulf coast’s Hurricane Katrina, texting emerged as a source of information sharing when voice-based technologies failed (Doerfel et al., 2010). Layered on top of reaching out through various ICTs to gain information and support during such urgencies, individuals reach out to their strong ties and familial relationships for various forms of support and usually use rich media, such as phones, to do so (Ling, 2008). This tension between media and an interdependent system within which new and old media coexist has the potential to impact social patterns. This study considers new and old media use as part of IORs and the media strategies organiza-tions use to (re)connect to their social networks after routines were disrupted by Hurricane Katrina.

When it comes to new technologies, communicating partners jointly negotiate the adaptability of the technologies to maintain relationships (Dunbar-Hester, 2009). Moreover, technologies range in terms of their utility, given unique context-based factors (Bouwman and Van De Wijngaert, 2002; Dimmick et al., 2011). For example, in post-hurricane conditions, widespread power outages make land-based computer use futile. Regardless of routine and non-routine contexts, organizations have adapted communica-tion strategies to integrate new media, yet in interorganizational domains, the efficacy of new media in maintaining and expanding/building social networks is largely ignored. For example, one valuable aspect of an organization’s communications management is its collaborations with other organizations (Berry et al., 2004; Taylor and Doerfel, 2011). Being engaged in broader community relationships and with other organizations facili-tates capacity building, which provides a form of necessary infrastructure (Kent and Taylor, 2002). One way to build and manage such relationships is through conventional networking practices (e.g., attend professional conferences), but new technologies allow for adapting organization-level networking, so long as partners jointly adopt alternative forms of staying in touch. Aside from descriptions of how organizations use social media (e.g., Perry et al., 2003), little is known about old and new media uses to build and man-age interorganizational networks.

Despite the growing popularity of ICTs in general, and interest in how ICTs are adopted and adapted by individuals, only a handful of studies explore organizations’ ICT use to build and maintain relationships (e.g., Bortree and Seltzer, 2009; Kent, 2008). They emphasize the increasing importance of social media channels in public relations (PR) and provide insight into building relationships using social media (e.g., Briones et al., 2011). New media, however, have been portrayed in contradictory ways in the litera-ture (Rice, 1999; Wellman et al., 1996). They are seen as decreasing social involve-ment or as integrative, connecting disparate others (Constant et al., 1996) and consolidating existing connections (Lind and Zmud, 1995). The next section considers these oppositional views.

Doerfel and Haseki 3

New media and relationship management

In terms of building and maintaining individual-level networks, Ellison et al. (2007) reported that college students who use social networking sites build social capital by enabling people to maintain and form new friendships. Online communication can also promote face-to-face contact (Bargh and McKenna, 2004). More broadly, Internet use can overcome contextual neighborhood effects in concentrated disadvantaged areas that would otherwise limit opportunities for local tie formation (Hampton, 2010). A growing body of evidence shows that new media helps individuals maintain relationships over geographic distances (Boase et al., 2006; Van Den Berg et al., 2012) enhance social capi-tal, or access those resources (friendship, information) that are embedded in face-to-face and mediated social networks (Dutta-Bergman, 2004; Lin and Erickson, 2008).

Drawbacks regarding social media use include a decline in offline interpersonal rela-tionships (Nie, 2001; Tillema et al., 2010) and weakened existing social ties with family and friends from the loss of face-to-face contact (Putnam, 2000). Losing face-to-face contact echoes the underlying point of media richness theory, which asserts that media range in terms of the robustness of information that the media carries (Daft and Lengel, 1984). Channels range from lean to rich, where equivocality of information is of greater concern at the lean end. For example, a bulletin leaves no room for clarity compared with channels like telephones and face-to-face, the foundation of Kraut et al. (1998) and Putnam’s (2000) views of friendship. From this view, lean media are not ideal for uncer-tainty reduction. In terms of general media use, most people employ mobile phones to keep in contact with fewer than six strong ties (Ling, 2008), which may reduce the need to maintain larger and more diverse networks (Gergen, 2008). We discuss individual uses of ICTs and media richness theory briefly, since some practices and outcomes involve individuals who network on behalf of their organizations and lean and rich channels sup-port information sharing differently (Daft et al., 1987).

At the organization level, the ways specific communication modes are used to stay in touch with their networks is less researched, although IORs and building capacity in interorganizational networks are emerging as essential components for an organization’s communication strategy (Kent and Taylor, 2002; Taylor and Doerfel, 2003). Capacity building refers to the strengthening of existing and expanding to new relationships in order to manage uncertainty in the broader IORs and stakeholder environments. Such a view of PR is embedded in systems theory (Broom et al., 1997), and it is because organi-zations need others for resources, specialized services and expertise, and through coex-istence in a competitive field that organizations include IORs as part of their capacity building tactics (Van De Ven, 1976; Van De Ven and Walker, 1984). The Internet pro-vides an opportunity to create IORs through dialogic components allowing input by and communication with publics (Kent and Taylor, 2002). Not all organizations, however, use the Internet in a dialogic manner (Bortree and Seltzer, 2009; Taylor et al., 2001), despite arguments that blogs offer more opportunities than traditional websites for two-way dialog for organizations (Seltzer and Mitrook, 2007). Use of various media is a way organizations can manage their interdependent relationships across the broader system.

In his recent study, Kent (2008) focused on relationship building and proposed that blogs provide organizations benefits such as “issue framing, relationship building, fostering trust,

and identification” (p. 37). In terms of the media relations function of PR, Waters et al. (2010) discovered “media catching,” where organizations are contacted by journalists as a result of the journalists following the organizations’ social media, as opposed to the conven-tions of practitioners reaching out to journalists. While Waters et al. suggest new media are a way for organizations to be available for adding new network relationships, Howard’s (2002) view asserts that new media do not enhance network centrality so much as the addi-tional media choices facilitate access to one’s network. Howard’s thesis complements Kent’s view that organizations use new media to enhance relationship quality.

Practitioners believe social media enable organizations to respond quickly to ques-tions and concerns from their publics and help them build relationships with strategic publics (Wright and Hinson, 2008). This suggests relationship building opportunities, but Eyrich et al. (2008) found that among 18 social media tools only about six tools are used and that professionals are more inclined to use more traditional tools (e.g., email) as opposed to more technologically complicated channels (e.g., text messaging, social net-working sites). Similarly, organizations have yet to fully adopt new technologies (e.g., blogs) for professional use (Porter et al., 2009). These findings echo the assertion made above, that new media do not necessarily supplant old media, although tensions may arise. In this case, simultaneous uses of old and new media may put pressure on organiza-tions to adapt their ICT repertoires.

In short, research on organizations’ ICT use to maintain and build relationships is generally limited to PR functions in terms of outreach. One notable driver beyond merely a PR function is when external factors driven by resource needs result in adopting social media (Nah and Saxton, 2012). Related to this, disasters put stress on systems in terms of creating uncertainty, emotional distress, and financial loss. Like individual victims, organizations need resources and support to manage the increase in these stressors and to facilitate recovery. Support ranges from intangibles, such as information and emotional support, to material support, such as loans and financial gifts. Tapping into one’s network is a way of gleaning critical resources that support survival and recovery. Indeed, after disaster, some have found such material support flows through networks and is not just given to strangers (Doerfel et al., 2010; Murphy, 2007). Thus, in disaster contexts, when there is a spike in the need for organizations to access a host of resources and when man-datory evacuations and land-based communications thwart conventional access (e.g., face-to-face, phone) to social networks, new media and innovative uses of accessible media are ways in which organizations may negotiate system constraints to (re)connect. We consider the ways organizations use established media (e.g., email, phone) versus more modern options reflective of relatively unfamiliar media (e.g., in 2005, text mes-sages and blogs were unfamiliar and thus considered complicated) to reconnect to and tap into organizations’ networks. We thus ask:

RQ1: How do disaster-struck organizations use ICTs to reconnect and tap needed resources?

Given an interest in the use of ICTs to (re)connect to interorganizational networks, we next consider organization and social network theory.

Interorganizational relationships, networks, and (re)connecting with information and communication technologies

An underlying assumption of organizational media use is that these communication strat-egies are a part of managing environmental uncertainty. Uncertainty management and, relatedly, organizational survival in the broader environment, is a function of internal organizational capacity, interorganizational resource dependencies, and evolving prac-tices that remain effective over time (Hannan and Freeman, 1984). Simply put, some organizational research grapples with the extent to which organizations select, change, and adapt their routines and repertoires over time or are relatively stable and predictable. Scholars such as March (1981) suggest that organizations are constantly changing and adapt routines easily and creatively; yet Hannan and Freeman assert that change is actu-ally relative to organizational responses to environmental conditions. “Slow” response to rapidly changing conditions suggests a high level of structural inertia because the organi-zation’s response or change necessitated by the conditions does not keep up (Aldrich and Ruef, 2006). Assuming IORs are an important component of an organization’s strategies to manage uncertainty, we next turn to social capital, which is about being embedded in networks that facilitate access to various forms of resources.

Social capital, density, and diversity

The effective flow of communication across organizational boundaries is critical for an organization to build relationships in a dynamic (Hannan and Freeman, 1977) and, specifically, a disaster environment (Doerfel et al., 2010, 2013). Social capital refers to the resources embedded in relationships and can vary in terms of bridging and bonding forms. Bridging refers to accessing diverse information gained through weak ties, while bonding refers to building up cohesion between communication partners that have invested the time necessary for deep trust. Bridging and bonding social capital are particularly salient in disaster contexts when both uncertainty and a need for trusted information are high. Communicating with other organizations facilitates better deci-sions about how to proceed to achieve their goals of restoring their functionality (Comfort, 1999; Runyan, 2006). Inadequate communication patterns such as disjointed information flows inhibit social capital with implications explained by network den-sity and diversity.

Dense networks have been defined in terms of how many connections a focal organi-zation has relative to the total possible links (Hannan and Freeman, 1977). A common assumption is that organizations embedded in dense networks have high levels of social capital (Brown and Ashman, 1996). Salient to disaster contexts is that communities (at individual- and organizational-level foci) with strong relationships (high density) func-tion better in emergency situations because of increased trust (Chewning et al., 2012; Doerfel et al., 2010; Kapucu, 2006). Related to this, organizational density and diversity are facets of an organization’s and broader community’s growth and survival (Saxton and Benson, 2005). One drawback of locally dense networks, however, is whether there is time to build out diversity in the network, too.

Diverse social networks are created by heterogeneity as opposed to homogeneity. Diverse interpersonal networks include a wider range of ethnicities, religion, age groups, and professional backgrounds (Hampton, 2010). Organization-level diversity includes organizations that represent various sectors, competitors, profit, non-profit, government entities, etc. (Doerfel et al., 2010). Diverse networks are associated with a range of posi-tive outcomes since diverse resources flow through diverse networks. For example, non-profit organizations benefit from having corporate, government, and community-located IORs (Nah and Saxton, 2012; Saxton and Benson, 2005). Diversity is thusly viewed as a direct measure of the resources accessible through networks (Lin and Erickson, 2008). Similar to advantages of high density, the potential for social capital is maximized in social settings where the diversity of others is highest.

In terms of building social capital through dense and diverse networks, ICTs have their merits, but face-to-face communication cannot be ignored. Public places such as public parks, voluntary associations, and professional clubs that allow access to people from different social groups are most likely to provide exposure to diversity (Lofland, 1998). Participation in these types of venues is defined by face-to-face communication and the various spaces would have a greater potential to support diverse networks. Other than face-to-face communication, technologies that afford interaction with large num-bers of others are likely to have direct effects on network diversity (Hampton et al., 2011). These technologies include Internet use such as web surfing and email and social networking sites. Technologies that primarily afford interaction with a small number of strong ties such as mobile phones, however, are likely to have no relationship to diversity (Ling, 2008). For example, bloggers are likely to be very similar (Adamic and Glance, 2005), but they may be more likely to participate in a variety of activities to feed their blogs (Marlow, 2005). Despite the modes of connection, face-to-face and ICTs impact network density and diversity. Yet in the context of disaster, access to social networks is often difficult, even if possible, both on- and offline.

In terms of network theory, density and diversity are a source of tension. On one hand, bonding social capital (i.e., dense networks) implies exchanges of favors that provide mutual benefits, building trust, and positive reputations in the broader community (Taylor and Doerfel, 2003). In this way, the network emerges as stable and predictable because of institutionalized ties among a set of reliable, known partners (Hannan and Freeman, 1984). On the other hand, bridging social capital (diversity) affords unique access because diverse ties suggest complementary information and resources. Yet driv-ing more diverse networks are relationships that are weaker in terms of familiarity and frequency of contact. Indeed, Hales (2002) and Hannan and Freeman (1984) suggest that organizations can undermine the advantages of loose structures and networked forms by routinizing partnerships that can result in something similar to a stable, rigid bureau-cracy. Over time, what could be a dynamic network instead becomes relatively inert, taking on an institutional quality. Simply put, organizations returning to the same, famil-iar ties build network stability but with a finite and known knowledge set.

On the other hand, organizations that turn to weak or unknown ties take risks when the relatively unfamiliar partner fails to deliver (Vangen and Huxham, 2003). But new partners might offer unique solutions and plausible alternatives for an organization suffering the impacts of a disaster. So a tension arises in that organizations partner with

reliable, trusted others but also network to build out access to unique information and resources vis-à-vis diverse ties. As an added complication for the disaster-struck organization, the network is an important resource, but accessing it over physical dis-tances due to evacuation and downed communications infrastructures can be difficult.

Communicating after network disruptions

When actors in dispersed locations require immediate access to each other, they must overcome the constraints of traditional communication (Dutta-Bergman, 2004; Rice, 1999). Some have asserted that the implementation of new technologies in emergency management should improve communication speed and quality in response operations (Comfort, 1999; Quarantelli, 1997). ICT use, however, may only be as good as the intact network. Kapucu (2006) explored the contribution of ICTs to communication among first responders during September 11, 2001, and found that building up a strong interor-ganizational network before disaster facilitates the ability to take advantage of ICTs. These arguments, along with organization theorists’ arguments discussed above, suggest that a multi-pronged ICT strategy would give organizations an edge in reconnecting to their disrupted networks.

These assertions rest on the underlying assumption that IORs rely on and are more swiftly reconnected using ICTs. Indeed, this argument underscores the key components argued in this paper. Strategic communication involves IORs that give access to informa-tion flows, dense and diverse networks, and a host of communication channels through which connections are made and retained. Strong relationships marked by dense net-works and weak ties that access diverse networks build up social capital that can be mobilized after disaster (Doerfel et al., 2010, 2013). The ability to reach those networks through ICTs means swift access to partners, resources, and information necessary to the victimized organization. But the underlying presumption remains largely untested in the IOR context, so we ask:

RQ2: How do ICTs facilitate the rebuilding of disrupted networks?

Method

Open-ended interviews were conducted with organizational leaders using convenience and snowball sampling. Recruiting included 16 field visits resulting in 90 interviews with 56 leaders. For this research, interviews from a first wave of data collection were used. Participants represented New Orleans industries including restaurants/bars, media, non-profit agencies, cultural venues, banks, professional firms, and retail establishments. Because structured communication channels may not work in emergencies, boundary spanners can play a significant role in effective communication in emergency and crisis management. Boundary spanners are organizational members who link their organiza-tion with the external environment. We thus asked participants to be informants as organ-izational boundary spanners. In their leadership role they were privy to critical decision making regarding rebuilding. Included were small (less than 20 employees), medium

(21–100 employees), and large entities (more than 100 employees). Interviews ranged from 21 to 105 minutes and were conducted in person and by telephone, with no signifi-cant differences between face-to-face (n = 39; M = 53.82, SD = 17.65 minutes) versus telephone (n = 17; M = 54.29, SD = 15.77 minutes).

As part of the larger research project, over 1500 pages of interviews were assessed over a two-year period by a team of seven coders using AtlasTi, a data analysis program that allows for review of data in a variety of ways, including as a whole document, by code, or by quotation. Codes were compared within and among documents, including by quantity, association with other codes, and similarity and differences among stories. Among the resulting multi-page list of codes and subcodes, this paper focuses on codes about communication media and network measures of density and diversity.1

Variables

Media use. ICT media uses included face-to-face, landline phone, mobile texting, mobile talking, email, blog/website, phone, and one way (e.g., mass communicated announce-ment that would not enable feedback through the same medium). These media were then categorized, reflective of the relative familiarity these modes had in 2005, during the disaster. For example, some 200 million cell phone users (http://www.infoplease.com/ipa/A0933563.html) existed in the United States in 2005 and underlying participants’ assumptions was the ubiquitous nature of talking on mobile phones. For participants, however, texting was seen as new and innovative, and staying in touch with blogs or two-way websites was limited to those who reported “tech savvy” employees or a pen-chant for new technologies.

Four categories emerged in terms of communication modes used: (a) established – face-to-face communication and landlines; (b) common – mobile phone talking and email; (c) innovative – mobile text and blog/website use; and (d) mixed – use of all communica-tion media. Each organization was assigned one of these categories based on frequency of use. For instance, if a participant suggested face-to-face and landline dominated their organization’s use over any other media then the organization was assigned to established. If all media were used at varying degrees, with none dominating over others, then the organization was coded as mixed. Six were assigned to established, 16 to common, 6 to innovative, 24 to mixed and four lacked sufficient information to be coded. Organizations generally had “pet” approaches reflective of these four categories, so two independent coders noted no discrepancies. To provide equally weighted samples for the analyses, all six of the organizations coded in the established and innovative categories and subsam-ples of six sets of observations for density and diversity were randomly selected from the 16 common and 24 mixed categories. Analyses were repeated with different randomly selected subsamples of common and mixed to ensure that each network was included in the analysis and that results remained consistent across different subsamples.

Phases over time. To capture longitudinality, ATLAS.ti queries were made for codes repre-senting timing of contact. Phases spanned from before the storm, while evacuated, imme-diately after returning, to settled-in, marked by a stable routine of work. Although interviews were based on recall, research shows that “salient events are more likely to be recalled than

nonsalient events, where saliency is a function of the unusualness of an event, its economic and social costs and benefits, and its continuing consequences” (Pearson et al., 1992: 88).2

Network ties. To capture all salient alters (with whom an organization reports having links) named by organizational leaders, ATLAS.ti queries were used to search for discus-sions about sources of emotional, informational, and financial support and to establish that such a contact was for professional reasons and was deemed useful.3

Alter type. An alter refers to another organization named by a participating organization. When an alter was named, that unique alter (an organization, the organization of the indi-vidual named when the individual represented the organization, or an individual) was categorized using one of 49 codes so that across-case comparisons could be made. Each organization represented was assigned its own row, populated by the number of times a particular organizational type was named for each of the four over time phases. The total number of links identified by all participants was 923,4 ranging from a low of 3 (the par-ticipating organization was relatively isolated) to a high of 49 (the participating organiza-tion’s network was relatively connected) (m = 24.7, SD = 9.1). Organizations discussed in a negative light (e.g., ineffective) or identified but not reachable were assigned a value of zero. Each row’s cells for each of the four over time phases were divided by the total number of alters named by ego, across all points in time. A resulting two-mode (n × m) matrix represents the organizations’ reported alter ties. Matrices are valued, rectangular, and represent the extent to which ego, n, named alter types, m, as links used at the four stages. Four n × m networks (one for each point in time) were constructed and these matri-ces were used to extract sub-matrices to represent the variables density and diversity.

Density. Density indicates information flows and, in its simplest form, is a proportion of actual links divided by total possible links. Row totals from the “alter type” matrices described above were used to calculate density for each participating organization. In those matrices, cells were proportional values of connections each participant reported having relative to their total connections over the four phases of time. Each valued cell is a percentage of an organization’s links relative to the total alter organizations named by that organization across all points in time. Density values ranged from .32 to 1.0 (m = .64, SD = .18) before the storm (T1), from 0 to 1.0 (m = .37, SD = .24) while evacuated (T2), from 0 to 1.0 (m = .49, SD = .25) immediately after returning (T3), and from .16 to 1 (m = .63, SD = .20) in the settled-in stage (T4). Some businesses whose density con-tracted included restaurants and tourism companies; some whose density expanded included professional firms and media companies.

Diversity. Diversity accounts for the number of organizations identified from different sectors than the participating organization’s sector, and ranges from 2 to 17 (m = 6.57, SD = 2.59) before the storm (T1), from 0 to 9 (m = 4.48, SD = 2.29) while evacuated (T2), from 0 to 11 (m = 5.64, SD = 2.63) immediately after the storm (T3), and from 1 to 14 (m = 6.5, SD = 2.7) in the settled-in stage (T4). Examples of organizations whose diversity contracted were restaurants and tourism, while some professional firms and media companies’ expanded.

Results

RQ1 asked about how disaster-struck organizations use ICTs to reconnect and tap into needed resources. Based on the interview data 27% of all organizations used face-to-face communication, 19% used a blog/website, 15% used email, 11% used mobile phone, 5% used landlines, and 4% used mobile texting to connect with their networks. Overall, established media was predominant. Additional queries assessed how organi-zations used the various media categories. More interpersonal modes of communication (i.e., face-to-face, talking on the phone) were used for connecting with other organiza-tions and sources of support. Websites and blogs were used more passively in terms of information gathering (e.g., one named alter began a blog to post information, much like a bulletin board). Texting was “discovered” by some but several participants noted the challenge with texting – it worked, but oftentimes their interlocutor did not know how to use it. Thus, tensions on social patterns related to old and new media simultaneously existing but not necessarily adopted and/or adapted could be ascribed.RQ2 asked how ICTs facilitate the rebuilding of disrupted networks. We used facto-rial repeated-measures analysis of variance (ANOVA) to test the relationship between scores of the same subjects at different time points. We tested if the variances of the differences between conditions are equal using Mauchly’s test. The first set of analy-ses includes within-subject, between-subject, and contrasts to understand the relation-ship between density and media use. The results of within-subject effects show that density was significantly affected by the disaster phase, F (2.15, 43.20) = 29.06, p = .00 (Table 1). In other words, there is a significant difference in interorganizational densities between some phases of the disaster. Table 2 shows the pairwise compari-sons for the main effect of the disaster phase corrected using a Bonferroni adjustment. This table indicates significant differences between T2 and T1, T3, T4, meaning that there was a significant drop in density when the Katrina hit and an increase in density during the disaster periods immediately following the storm (T3 and T4). Figure 1 illustrates the changes in density over the four disaster phases. Regardless of the com-munication media used, density decreased during the disaster, started increasing at varying degrees after the disaster, and the original density levels were maintained or improved at the end of the two-year period.

Secondly, between-subjects analysis was tested to understand if media use had any effect on the density across the four disaster phases. There was a significant effect of media type on the density over time, F (3, 20) = 1.63, p = .03. That is, type of frequently used media affected density. To break down this interaction, contrasts were performed comparing all disaster phases and media categories (Table 2). Contrasts revealed signifi-cant interactions when comparing phases 1and 2 and phases 3 and 4. Figure 1 shows that the density of established and mixed-media users have similar patterns as well as similar rates of change over time, and show different patterns and rates of change to common and innovative media users.

The second set of analyses, including within-subject, between-subject, and con-trasts, were done to understand the relationship between diversity and media use.

Within-subject effects show that diversity was significantly affected by the disaster phase, F (2.35, 47.06) = 13.67, p = .00 (Table 3). That is, there is a significant differ-ence in diversity between some phases of the disaster – there was a significant drop in diversity from pre-Katrina to during Katrina periods and a major increase in

Table 1. Test of within-subject effects for interorganizational density.

Source Type III sum of squares

Df Mean square

F Sig.

Disaster_phases Sphericity assumed

2.312 3 .771 29.096 0.000*

Greenhouse-Geisser

2.312 2.151 1.075 29.096 0.000*

Huynh-Feldt 2.312 2.780 .832 29.096 0.000* Lower-bound 2.312 1.000 2.312 29.096 0.000*Disaster_phases * Media_use

Sphericity assumed

.605 9 .067 2.537 0.015*

Greenhouse-Geisser

.605 6.453 .094 2.537 0.031*

Huynh-Feldt .605 8.341 .073 2.537 0.018* Lower-bound .605 3.000 .202 2.537 0.086*Error(Disaster_phases)

Sphericity assumed

1.589 60 .026

Greenhouse-Geisser

1.589 43.020 .037

Huynh-Feldt 1.589 55.604 .029 Lower-bound 1.589 20.000 .079

*p<.05

Table 2. Tests of within-subjects contrasts of interorganizational density.

Source Disaster_phases

Type III sum of squares

df Mean square

F Sig.

Disaster_phases T1 vs. T2 2.669 1 2.669 139.754 0.000* T2 vs. T3 1.100 1 1.100 15.834 0.001* T3 vs. T4 .933 1 .933 14.381 0.001*Disaster_phases * Media_use

T1 vs. T2 .583 3 .194 10.171 0.000*T2 vs. T3 .031 3 .010 .149 0.929T3 vs. T4 .297 3 .099 1.526 0.238

Error(Disaster_phases)

T1 vs. T2 .382 20 .019 T2 vs. T3 1.390 20 .069 T3 vs. T4 1.297 20 .065

*p<.05

Pre-Katrina During Katrina Right after Katrina

Settled in

Established Common Innovative Mixed

Figure 1. Interorganizational density during four phases of disaster and media use.

diversity as organizations returned to a settled-in state. Diversity changed similarly to patterns observed for density, except diversity differed prior to and after the disaster. In other words, organizations’ original network before the disaster changed signifi-cantly after the disaster: they built new diverse relationships. Figure 2 illustrates these changes. Regardless of the communication media used, diversity decreased during the disaster, started increasing after the disaster, and significantly changed by the settled-in phase. Specifically, users of established and the mixed-media modes (re)built their

Table 3. Tests of within-subjects effects of interorganizational diversity.

Source Type III sum of squares

df Mean square F Sig.

Disaster Phases

Sphericity assumed 75.917 3 25.306 13.668 .000Greenhouse-Geisser 75.917 2.353 32.263 13.668 .000Huynh-Feldt 75.917 3.000 25.306 13.668 .000Lower-bound 75.917 1.000 75.917 13.668 .001

Disaster_phases * Media_use

Sphericity assumed 29.500 9 3.278 1.770 .093Greenhouse-Geisser 29.500 7.059 4.179 1.770 .115Huynh-Feldt 29.500 9.000 3.278 1.770 .093Lower-bound 29.500 3.000 9.833 1.770 .185

Error (Disaster_phases)

Sphericity assumed 111.083 60 1.851 Greenhouse-Geisser 111.083 47.062 2.360 Huynh-Feldt 111.083 60.000 1.851 Lower-bound 111.083 20.000 5.554

*p<.05

diversity at a much faster rate and were also able to diversify beyond pre-disaster levels compared to common and innovative users.

Table 4 shows the pairwise comparisons for the main effect of media use corrected using a Bonferroni adjustment. This table indicates that the main factor reflects a signifi-cant difference between innovative and mixed modes. Innovative and mixed

media allowed organizations to build significantly different numbers of diverse rela-tionships. Next, contrasts were performed comparing all disaster phases and all media categories. Contrasts revealed significant interactions when comparing right after Katrina and once settled-in (Table 5).

Overall, data showed that networks broke up in terms of density during the disaster and organizations that relied on established and mixed media to reconnect were more efficient at rebuilding a network that was similarly dense prior to Katrina. These media users also (re)built diverse networks at a faster rate and expanded diversity in the long run relative to pre-disaster levels. Meanwhile, common and innovative media users’ (re)networking was slower and, in the long run, these users’ networks were less dense and diverse. Based on qualitative aspects of the data, innovative media users engaged the media for information seeking rather than relationship building and ultimately did not experience growth in terms of density and diversity.

Discussion

This study identified old and new media use by organizations to (re)connect to disrupted networks after Katrina and with what effect on social patterns. Results suggest considera-tions about old and new media tensions as IORs get rebuilt. Although 2005 ICTs were different than today, coding categories reflected two dimensions of ICTs that withstand

1.52.02.53.03.54.04.55.05.56.06.57.07.58.08.5

Pre-Katrina During Katrina Right after Katrina Settled in

Established Common Innovative Mixed

Figure 2. Interorganizational diversity during four phases of disaster and media use.

the test of time – ones that range in terms of rich interpersonal interaction and informa-tion-getting capacities (Daft and Lengel, 1984), and those that are routinely used versus unfamiliar or new (Dimmick et al., 2011; Marvin, 1988). Contributions regarding ICTs for networking and the dynamics of IORs are discussed.

The media spectrum and interorganizational networking

Mediated communication channels are an option for organizations, but the ways in which organizations use available ICTs have implications for their social networks in general and rebuilding them, in particular. In general, organizations that used various media

Table 4. Pairwise comparisons of media use of interorganizational diversity.

(I) Media use (J) Media use Mean difference (I–J)

Std. error Sig.a 95% Confidence interval for differenceb

Lower boundUpper bound

Established Common 1.833 .901 .332 −.805 4.471Innovative 2.292 .901 .116 −.346 4.930Mixed −.125 .901 1.000 −2.763 2.513

Common Established −1.833 .901 .332 −4.471 .805Innovative .458 .901 1.000 −2.180 3.096Mixed −1.958 .901 .252 −4.596 .680

Innovative Established −2.292 .901 .116 −4.930 .346Common −.458 .901 1.000 −3.096 2.180Mixed −2.417 .901 .086* −5.055 .221

aBased on estimated marginal means.bAdjustment for multiple comparisons: Bonferroni.*p<.05

Table 5. Tests of within-subjects contrasts of interorganizational diversity.

Source Disaster phases

Type III sum of squares

df Mean square F Sig.

Disaster_phases T1 vs. T2 63.375 1 63.375 23.400 .000 T2 vs. T3 60.167 1 60.167 11.108 .003 T3 vs. T4 18.375 1 18.375 5.554 .029Disaster_phases * Media_use

T1 vs. T2 17.458 3 5.819 2.149 .126T2 vs. T3 9.500 3 3.167 .585 .632T3 vs. T4 26.458 3 8.819 2.666 .076*

Error(Disaster_phases)

T1 vs. T2 54.167 20 2.708 T2 vs. T3 108.333 20 5.417 T3 vs. T4 66.167 20 3.308

*p<.05

simultaneously had higher levels of density and diversity and rebuilt and expanded their networks more swiftly. Conversely, lean media meant slower (re)networking. These results demonstrate an additional advantage to Kent (2008), advocating for organizations to use modern media in their strategies to manage their environments. The mixed use of media served as a rebuilding catalyst. The combined use of rich and lean with old and new media channels was fundamental to reconnecting and drawing on social capital. In addi-tion, with mixed media, organizations accomplished this more efficiently and effectively. These analyses complement Dutta-Bergman’s (2004) findings about individuals’ channel complementarity after 9/11. Face-to-face interactions and phone calls remain a necessary component to IORs after disaster. Yet, in the ever-evolving new media landscape, organi-zations that use face-to-face, as well as a mix of new media, reap the benefits tied to diversity, density, and in a more efficient manner than those who use solely established, rich media. These findings also extend the thesis that tensions amid old and new media used together may impact social patterns in unique ways (Marvin, 1988).

The data inform the ways media and organizational theories work together and are illustrated in the Organizational Media Spectrum depicted in Figure 3. The first dimen-sion reflects the intimacy levels ranging from interpersonal-to-public nature of commu-nication over mediated channels. The second dimension categorizes the channels as ones ranging from very familiar (known) and thus conventional to unfamiliar/new. Also depicted in the figure are rich and lean media coupled with bonding (density) and bridg-ing (diversity) social capital. Density is more commonly built up in face-to-face interac-tions, while social media enable capacity building in terms of diversity (Bortree and Seltzer, 2009; Kent, 2008).

The overlap of the channels in Figure 3’s Venn diagram shows that face-to-face com-munication is necessary, but integrating mediated forms of communication give organi-zations the same edge without the presumed time involved to communicate solely through rich media. In other words, the center circle in the media spectrum offers organi-zations an efficient approach that is reflective of the more interpersonal part of relation-ship building. Indeed, those organizations that did not integrate conventional media as prominently in their networking suffered a delay in their return to pre-disaster networks and, for those relying solely on innovative media, suffered a small setback in terms of density and diversity compared to their pre-disaster levels. In short, organizations still relationship-build with other organizations using more rich and conventional media choices. Future research can expand the Organizational Media Spectrum model by con-sidering new ICTs and their use with other channels to (re)build networks at individual and organizational levels of analyses. As ICTs evolve, we propose that ones that support more personal dynamics and swift networking will be more useful to IOR building after network disruption, which ties in with theory about IOR management: trust is an impor-tant factor (Vangen and Huxham, 2003) and even more so in emergency contexts (Kapucu, 2006).

The dynamics of interorganizational networks

Adaptive networking strategies support survival in an interdependent system (Broom et al., 1997; Van De Ven, 1976; Van De Ven and Walker, 1984) that has experienced

change due to a major environmental jolt (Aldrich and Ruef, 2006; Hannan and Freeman, 1984). The disaster was an event where, coupled with media choices, some organizations broke out of past routines by not merely revitalizing old ties (a trend towards structural inertia), but by expanding and enhancing their network; they enjoyed increased levels of social capital. After disaster, tensions of density and diversity were evident. Organizations that used mixed media increased both aspects of networking, a pattern likely reflective of the urgency and elevated needs for information. They doubled-down on reaching out to both types of ties. This finding complements Doerfel et al. (2010), who reported quali-tative evidence that organizations found the disruption a time that organizations deep-ened existing ties (bonding social capital) and expanded their networks (bridging social capital). Given the growing body of disaster research, disaster is a time when change, not

Figure 3. The Organizational Media Spectrum. Information and communication technologies (ICTs) used to reconnect interorganizational networks are depicted in terms of (a) communication intimacy dimension, ranging from personal interactions to public communication; (b) familiarity with communication technologies dimension ranging from types that were coded as commonly known and used to those that were seen as new/unfamiliar; and (c) a third dimension depicting network capacity and the tensions of density versus diversity. Circumference size represents broader potential reach to others using ICTs. Communication strategies that range from focused to diffused as well as necessary and sufficient conditions observed in the data are noted with dotted lines and the size of the circles suggests relative quantities of alters the focal organization could communicate with through the various ICT approaches.

structural inertia, occurs for some organizations. Whether this is by design or necessity is unclear, although this study demonstrates the value of mixed media for facilitating such change in networks.

Those organizations whose practices were with the common and innovative media that tended to be at the public end of the Media Spectrum (Figure 3) returned to the same structural qualities as before (Figures 2 and 3). Curiously, why would organiza-tions that use new ICTs be stuck in old organizing practices? The dimensions in Figure 3 amplify the discovery that their media strategy lacks relationship building at the personal level. For organizations recovering from a disaster, media presence is not suf-ficient. Disaster is an event that affords the opportunity to break free from structural inertia through adaptation, but media strategies including a personal dimension drive that potential of the inert network to actively grow (diversity) and intensify (density). Organizations should thus consider this theoretical advance in their disaster plans: media is an organizing mechanism of survival. The communication function after dis-aster is not simply about announcing a reopening, a return, or a reconnection. The communication plan is about adapting with a media mix that supports revitalizing old and building new connections that support social capital access and thus survival.

Limitations and implications

These findings are not generalizable because the convenience sample included only rela-tively successful organizations. Related to this, a small sample meant that subsamples had to be used for balanced analyses, compromising effect size. These data, however, were based on a highly salient event with data that offer unique insights into organiza-tions and their communicative actions for managing a fundamental rebuilding compo-nent to surviving the disruption of their network: mediating IORs. Organizational strategic planners should resist the ease of ICTs, recognizing that on their own, they are not sufficient to maintaining, rebuilding, or expanding social networks. On the other hand, relying solely on the more interpersonal end of relationships misses “media catch-ing” opportunities by not attending to a broader reaching web presence (Waters et al., 2010) as well as expanding their networks.

Conclusion

This study considered social networks as one part of disaster management and how ICTs play a role in mobilizing interorganizational social networks. The Media Spectrum (Figure 3) illustrates results of the network tensions, relationship dimensions, and com-munication technology familiarity. Organizations varied in their attempts and patterns of rebuilding, showing that ICTs are sufficient, but more personal means were necessary for post-disaster rebuilding. Extending organization theory to disaster, organizations using face-to-face and interpersonally rich ICTs broke through an aspect of structural inertia with more dense and diverse networks in the long run. By viewing the organizations’ challenges within the system of interdependent relationships, this study also extended media theory in terms of the tensions old and new media wrought during a time when adapting to new com-munication repertoires facilitated swifter access to social capital and survival.

FundingThis research was supported by a grant to the first author from the National Science Foundation, Award BCS-0554959. An earlier version of this paper was awarded a “Top-2 Paper in Public Relations” by the Public Relations division of the National Communication Association.

1. See Doerfel et al. (2010) for coding details.2. Doerfel et al. (2010) also confirmed the reliability and validity in capturing the sequencing of

events over time for these data.3. These categories are part of a larger project coding scheme and Doerfel et al. (2010) report

procedures for assessing inter-coder reliabilities are reported.4. Nine hundred and twenty three equals the total number of unique organizations; not organi-

zational types (49 different organizational types were named). Within those categories, com-peting organizations are counted to represent the total number of unique organizations for calculating density.

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Author biographies

Marya L Doerfel (PhD, University at Buffalo, 1996) is an associate professor in the School of Communication and Information at Rutgers University. Her research focuses on networked forms of organizing with interest in network disruptions and the communication relationships that sup-port network maintenance and rebuilding.

Müge Haseki (MA, University of Wisconsin, Milwaukee, 2008) is a doctoral candidate in the School of Communication and Information at Rutgers University. Her research focuses on the use of new communication technologies in organizations and social networks.

Networks, Disrupted: Media Use as an Organizing Mechanism for Rebuilding

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