Networks, Disrupted 1

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

Marya L. Doerfel (Lead Author)

mdoerfel@rutgers.edu

and

Müge Haseki

Rutgers University, School of Communication and Information

4 Huntington Street

New Brunswick, NJ 08901

Paper accepted for publication in New Media & Society, online first 2013.

DOI: 10.1177/1461444813505362

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 support 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.

Acknowledgments: This research was supported by a grant to the first author from the National

Science Foundation, Award BCS-0554959.

Networks, Disrupted 2

Abstract

Longitudinal interorganizational relationships (IORs) in New Orleans are used to assess

the ways in which organizations employed information and communication technologies (ICTs)

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.

Keywords

Interorganizational networks, old and new media, social capital, disaster, network disruption.

Networks, Disrupted 3

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

As new information and communication technologies (ICT) 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 (c.f.,

Marvin, 1988). At the organization level, where evolving relationships are built and maintained

through collaborative endeavors, potential tensions and impacts on relationships are of similar

concern- organizational partners’ interdependence 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 immediately

following the 911 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 like

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 organizations use to (re)connect

to their social networks after routines were disrupted by Hurricane Katrina.

Networks, Disrupted 4

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 communication 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 & Doerfel, 2011). Being engaged in broader community relationships and

with other organizations facilitates 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

manage interorganizational networks.

Despite the growing popularity of ICTs in general, and interests 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 literature (Rice, 1999; Wellman et al., 1996). They

Networks, Disrupted 5

are seen as decreasing social involvement 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.

New Media and Relationship Management

In terms of building and maintaining individual-level networks, Ellison, Steinfeld, and

Lampe (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 capital, 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

relationships (Nie, 2001; Tillema and Schwanen, 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 Kraus et al. and Putnam’s views of friendship. From this view,

lean media are not ideal for uncertainty reduction. In terms of general media use, most people

Networks, Disrupted 6

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

support information sharing differently (Daft et al.).

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 (Taylor & Doerfel, 2003; Kent and Taylor, 2002). 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 organizations need others for resources,

specialized services and expertise, and through coexistence 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 provides 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,

Kent and White, 2001), despite arguments that blogs offer more opportunities than traditional

Web sites 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

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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 conventions 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 additional 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 questions

and concerns from their publics and help them build relationships with strategic publics (Wright

and Hinson, 2008). This suggests relationship building opportunities, but Eyrich, Padman, and

Sweetser (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 networking sites). Similarly,

organizations have yet to fully adopt new technologies (e.g., blogs) for professional use (Porter,

Sweetser, and Chung, 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 organizations 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, disasters put stress on systems in terms of creating uncertainty,

emotional distress, and financial loss. Like individual victims, organizations need resources and

Networks, Disrupted 8

support to manage the increase in these stressors and to facilitate recovery. Support ranges from

intangibles like information and emotional support to material support like 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

mandatory 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 messages 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 ICTs

An underlying assumption of organizational media use is that these communication

strategies 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 practices 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

Networks, Disrupted 9

and repertoires over time or are relatively stable and predictable. Scholars like March (1981)

suggest that organizations are constantly changing and adapt routines easily and creatively; yet

Hannan and Freeman assert that change is actually relative to organizational responses to

environmental conditions. “Slow” response to rapidly changing conditions suggests a high level

of structural inertia because the organization’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 decisions 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 density and diversity.

Dense networks have been defined in terms of how many connections a focal

organization 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

Networks, Disrupted 10

(Brown and Ashman, 1996). Salient to disaster contexts is that communities (at individual- and

organizational- level foci) with strong relationships (high density) function better in emergency

situations because of increased trust (Chewning et al., 2012; Doerfel et al., 2010; Kapucu, 2006).

Related, 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, nonprofit, and government entities, etc.

(Doerfel et al., 2010). Diverse networks are associated with a range of positive outcomes since

diverse resources flow through diverse networks. For example, nonprofit 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 which allow access to people from different social

groups are most likely to provide exposure to diversity (Lofland, 1998). Participation in these

types of venues are 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 numbers of others are likely to have direct effects

Networks, Disrupted 11

on network diversity (Hampton et al., 2010). These technologies include Internet use such as

web surfing and email and social-networking sites. Technologies which 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 off-line.

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 & 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 driving 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 which can result in something similar

to a stable, rigid bureaucracy. Over time, what could be a dynamic network instead becomes

relatively inert, taking on an institutional quality. Simply put, organizations returning to the

same, familiar 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

Networks, Disrupted 12

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 distances 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; Quaratelli, 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 interorganizational 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 information flows, dense

and diverse networks, and a host of communication channels through which connections are

made and retained. Strong relationships marked by dense networks and weak ties that access

diverse networks build up social capital that can be mobilized after disaster (Doerfel et al., 2010,

Networks, Disrupted 13

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 organization with the external environment. We thus

asked participants to be informants as organizational 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 21-105 minutes and were conducted in person and by telephone, with no

significant 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 1,500 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

Networks, Disrupted 14

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 diversity1.

Variables

Media use. ICT media uses included face-to-face, landline phone, mobile texting, mobile

talking, e-mail, blog/website, phone, one way (e.g., mass communicated announcement 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 2-way websites was limited to those who reported “tech

savvy” employees or a penchant 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 communication 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

Networks, Disrupted 15

samples for the analyses, all six of the organizations coded in the established and innovative

categories and subsamples 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

representing timing of contact. Phases spanned from before the storm, while evacuated,

immediately 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, Ross, and Dawes,

1992, p. 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 discussions

about sources of emotional, informational, and financial support and that such a contact was for

professional reasons and was deemed useful3.

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 individual

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 9234 ranging from a low of 3 (the participating organization was relatively

Networks, Disrupted 16

isolated) to a high of 49 (the participating organization’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 2-mode (n x 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 x m networks (one for each point in time) were constructed and these

matrices 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 .32-1.0 (m=.64, SD=.18) before the storm (T1), 0-1.0 (m=.37,

SD=.24) while evacuated (T2), 0-1.0 (m=.49, SD=.25) immediately after returning (T3), and .16-

1 (m=.63, SD=.20) in the settled in-stage (T4). Some businesses whose density contracted

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 2-17 (m=6.57, SD=2.59)

before the storm (T1), from 0-9 (m=4.48, SD=2.29) while evacuated (T2), from 0-11 (m=5.64,

SD=2.63) immediately after the storm (T3), and from 1-14 (m=6.5, SD=2.7) in the settled-in

Networks, Disrupted 17

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 blog/website, 15% used email, 11% used mobile phone, 5% used

landline, and 4% used mobile texting to connect with their networks. Overall, established media

was predominant. Additional queries assessed how organizations 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 organizations 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 factorial

repeated-measures 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 analyses includes within-subject, between-subject, and

contrasts to understand the relationship 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 comparisons for the

Networks, Disrupted 18

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 communication 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.

Second, 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 significant interactions when comparing

phases 1and 2 and phases 3 and 4. Figure 1 shows 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 than common and innovative media users.

The second set of analyses including within-subject, between-subject, and contrasts 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 difference 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 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 significantly after the

Networks, Disrupted 19

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 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 significant difference

between innovative and mixed modes. Innovative and mixed media allowed organizations to

build significantly different numbers of diverse relationships. 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 considerations

about old and new media tensions as IORs get rebuilt. Although 2005 ICTs were different than

Networks, Disrupted 20

today, coding categories reflected two dimensions of ICTs that withstand the test of time- ones

that range in terms of rich interpersonal interaction and information-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 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 and colleagues’ (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. And with mixed media, organizations

accomplished this more efficiently and effectively. These analyses complement Dutta-Bergman’s

(2004) findings about individuals’ channel complementarity after 911. Face-to-face interactions

and phone calls remain a necessary component to IORs after disaster. Yet, in the ever-evolving

new media landscape, organizations 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).

Networks, Disrupted 21

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 dimension

reflects the intimacy levels ranging from interpersonal-to-public nature of communication 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 bridging (diversity) social capital. Density is

more commonly built up in face-to-face interactions 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

communication is necessary, but integrating mediated forms of communication give

organizations 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 organizations an

efficient approach that is reflective of the more interpersonal part of relationship 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 considering 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

Networks, Disrupted 22

important 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 qualitative evidence that organizations found the disruption a

time that organizations deepened 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 structural inertia, occurs for some organizations. Whether this is by design or

necessity is unclear, though 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 organizations 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

Networks, Disrupted 23

from a disaster, media presence is not sufficient. 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 disaster 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

relatively successful organizations. Related, 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 organizations and their

communicative actions for managing a fundamental rebuilding component to surviving the

disruption of their network: mediating interorganizational relationships. 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 catching” 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 communication

Networks, Disrupted 24

technology familiarity. Organizations varied in their attempts and patterns of rebuilding showed

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 communication repertoires facilitated swifter

access to social capital and survival.

Endnotes

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. 923 equals the total number of unique organizations; not organizational types (49 different organizational types

were named). Within those categories, competing organizations are counted to represent the total number of unique

organizations for calculating density.

Networks, Disrupted 25

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Table 1: Test of Within-Subject Effects for Inter-organizational 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_pha

ses)

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

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 0.929

T3 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

Networks, Disrupted 33

Table 3: Tests of Within-Subjects Effects of Inter-organizational Diversity

Source Type III Sum

of Squares df

Mean

Square F Sig.

Disaster

Phases

Sphericity Assumed 75.917 3 25.306 13.668 .000

Greenhouse-Geisser 75.917 2.353 32.263 13.668 .000

Huynh-Feldt 75.917 3.000 25.306 13.668 .000

Lower-bound 75.917 1.000 75.917 13.668 .001

Disaster

Phases *

Media Use

Sphericity Assumed 29.500 9 3.278 1.770 .093

Greenhouse-Geisser 29.500 7.059 4.179 1.770 .115

Huynh-Feldt 29.500 9.000 3.278 1.770 .093

Lower-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

Table 4: Pairwise Comparisons of Media Use of Inter-organizational Diversity

(I) Media

Use

(J) Media Use Mean

Difference

(I-J)

Std. Error Sig.a 95% Confidence Interval

for Differencea

Lower Bound Upper

Bound

Established

Common 1.833 .901 .332 -.805 4.471

Innovative 2.292 .901 .116 -.346 4.930

Mixed -.125 .901 1.000 -2.763 2.513

Common

Established -1.833 .901 .332 -4.471 .805

Innovative .458 .901 1.000 -2.180 3.096

Mixed -1.958 .901 .252 -4.596 .680

Innovative

Established -2.292 .901 .116 -4.930 .346

Common -.458 .901 1.000 -3.096 2.180

Mixed -2.417 .901 .086* -5.055 .221 a. Based on estimated marginal means.

b. Adjustment for multiple comparisons: Bonferroni.

Networks, Disrupted 34

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 .029

Disaster_Phases *

Media_Use

T1 vs. T2 17.458 3 5.819 2.149 .126

T2 vs. T3 9.500 3 3.167 .585 .632

T3 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

Networks, Disrupted 35

Figure 1. Inter-organizational density during 4 phases of disaster and media use.

Figure 2. Inter-organizational diversity during 4 phases of disaster and media use.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Pre-Katrina During Katrina Right afterKatrina

Settled in

Established Common Innovative Mixed

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

Networks, Disrupted 36

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.