Humanitarian inter-organisational collaboration ... - Inderscience Online

Int. J. Services Technology and Management, Vol. 19, Nos. 1/2/3, 2013

Humanitarian inter-organisational collaboration network: investigating the impact of network structure and information and communication technology on organisation performance Louis-Marie Ngamassi Tchouakeu* College of Business, Prairie View A&M University, P.O. Box 519, MS 2310, Prairie View, TX 77446, USA E-mail: [email protected] *Corresponding author

Carleen Maitland, Andrea Tapia and Lynette Kvasny College of Information Sciences and Technology, The Pennsylvania State University, University Park, PA 16802, USA E-mail: [email protected] E-mail: [email protected] E-mail: [email protected] Abstract: In this paper, we report on a study that empirically investigates the impact of information and communication technology (ICT) resources and network structure on performance in humanitarian organisations that respond to natural disasters. We combine two theoretical lenses, resource-based view (RBV) and social network, to analyse data collected through multiple sources including web search, surveys and semi-structured interviews among members of the GlobalSympoNet, a community of interest of organisations engaged in humanitarian information management and exchange. Our findings suggest that organisations that possess a greater variety of ICT and greater network centrality experience superior levels organisational performance. Higher levels of network density also enhance the organisational performance of these organisations. Keywords: inter-organisational network; humanitarian organisations; social network; information and communication technology; ICT; organisation performance. Reference to this paper should be made as follows: Tchouakeu, L-M.N., Maitland, C., Tapia, A. and Kvasny, L. (2013) ‘Humanitarian inter-organisational collaboration network: investigating the impact of network structure and information and communication technology on organisation performance’, Int. J. Services Technology and Management, Vol. 19, Nos. 1/2/3, pp.19–42.

Copyright © 2013 Inderscience Enterprises Ltd.

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L-M.N. Tchouakeu et al. Biographical notes: Louis-Marie Ngamassi Tchouakeu received his PhD in 2011 from the College of Information Sciences and Technology, Penn State University. He is currently an Assistant Professor of Management Information Systems at the College of Business, Prairie View A&M University. His research focuses on information and communication technology (ICT) use for inter-organisational coordination and social networks among humanitarian organisations. Carleen Maitland is an Associate Professor at Penn State University’s College of Information Sciences and Technology. Her research examines the international and inter-organisational context of information technology use. Her recent studies have analysed coordination of information technology and information management across humanitarian relief organisations, including the United Nations Office of Coordination for Humanitarian Affairs. She also studies international telecommunications policy coordination. In 2010–2012, she served as a Program Manager at the US National Science Foundations Office of International Science and Engineering. Andrea Tapia is an Associate Professor at Penn State University’s College of Information Sciences and Technology. Her research focuses on the functional and structural elements of organisations engaging in technological change and coordination across boundaries. Lynette Kvasny is an Associate Professor at the College of Information Sciences and Technology, Pennsylvania State University. Her research explores the ways in which race, gender and class identities shape the appropriation of information and communication technologies.

1

Introduction

Humanitarian organisations are increasingly facing complex challenges due to the high frequency of natural disasters and the growing number of actors in the humanitarian relief sector. In an attempt to mitigate these challenges, these organisations are increasingly collaborating through inter-organisational networks (Stephenson, 2005, 2006; Saab et al., 2008; Ngamassi et al., 2011). International relief efforts after major natural disasters such as the South Asian Tsunami in 2004, the Hurricane Katrina in 2005 and the Haiti earthquake in 2010 have highlighted the importance of collaboration and coordination in these inter-organisational networks. Such networks provide a venue where humanitarian organisations interact to strengthen established relationships and to create new relationships. Through inter-organisational networks, humanitarian organisations can provide disaster response that would be beyond the scope of any single organisation (Stephenson, 2005, 2006). However, the effectiveness of these networks has not been established empirically. Despite more than a decade old call (O’Toole, 1997; Provan and Milward, 1995) for better understanding of the performance and effectiveness of inter-organisational networks in the non-profit context, limited research has been conducted (Provan et al., 2007; Van de Walle et al., 2009). Evaluating the performance of humanitarian inter-organisational networks is critical for understanding whether these networks are effective in meeting the goals of the network as a whole and those of the individual network members. Perhaps most importantly, little is known about the extent to which the needs of the affected people have been met by the humanitarian relief

Humanitarian inter-organisational collaboration network

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organisations. Ideally, an effective humanitarian inter-organisational collaboration network would enhance the quality of service provided to its clients while optimising use of resource by reducing redundancies. Humanitarian organisations are increasingly adopting and using information and communication technology (ICT) to support their disaster relief operations (Van de Walle et al., 2009). A rich body of literature points to the critical role that ICT plays in complex inter-organisational disaster response plans (Comfort, 1993; Comfort et al., 2001; Moss and Townsend, 2006). Comfort (1993) identifies three main roles of ICT in managing humanitarian disaster including. First, ICT enables disaster relief managers to create interactive networks that facilitate communication and focus the network’s attention on problem solving. ICT allows the representation of information in graphic form. This simplifies complex data for human comprehension, and increases the speed and accuracy of communication. Third, ICT enables and facilitates the development of databases for storing relevant information about the community and its population, and assists managers in quickly formulating alternative solutions for assistance. Wentz (2006) presents the best practices for creating a collaborative, civilian-military information environment to support data collection, communication, collaboration, and information sharing in disaster situations and complex emergencies. Additionally, the convergence of ICT and the growth of the mobile internet contribute significantly to humanitarian organisations’ ability to collaborate more efficiently in disaster relief around the globe. Research on social media highlights the important role that these technologies play in humanitarian assistance and disaster relief (Palen et al., 2007a, 2007b; Palen and Liu 2007c; Sutton et al., 2008; Hughes et al., 2008; Liu et al., 2008; Vieweg et al., 2008). However, the use of ICT for humanitarian inter-organisational coordination and collaboration also gives rise to many challenges. These challenges are related to the inter-organisational context, to the non-profit sector and to the emergency response context (Saab et al., 2008; Van Gorp et al., 2008; Maitland et al., 2009). These challenges originate not only from the general organisational characteristics but also from those of ICT. The purpose of our study is to empirically investigate the impact of ICT resources and network structure on performance in humanitarian organisations that respond to natural disasters. The research question that guides this study is “to what extent does the interaction of ICT and network structural characteristics impact organizational performance?” We combine two theoretical lenses including resource-based view (RBV) (Barney, 1991; Prahalad and Hamel, 1990) and social network (Wasserman and Faust, 1994; Kilduff and Tsai, 2003) to analyse data collected through multiple sources including web search, surveys and semi-structured interviews among members of the GlobalSympoNet, a community of interest of organisations engaged in humanitarian information management (IM) and exchange. Network structural characteristics (e.g., density, degree centrality, clique and clique overlap) have been found to have direct impacts on performance (Ahuja and Carley, 1999; Tsai and Ghoshal, 1998; Tsai, 2000; Provan et al., 2007). Similarly, the embeddedness of organisations in networks of external relationships with other organisations positively influences performance (Granovetter, 1985; Uzzi, 1996, 1997, 1999). RBV explains performance exclusively through internal resources such as ICT (Barney, 1991; Prahalad and Hamel, 1990). ICT has also been shown to play a critical role in mitigating some informational related issues for inter-organisational humanitarian response such as creating a collaborative

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L-M.N. Tchouakeu et al.

environment to support data collection, communications, and information-sharing (Comfort, 1990; Graves, 2004; Comfort and Kapucu, 2006; Moss and Townsend, 2006). Organisation performance was measured as the number of humanitarian relief related funded projects. Our findings suggest that organisations that possess wider varieties of ICT benefit more from high network degree centrality. Both wider variety of ICT use and network degree centrality enhance organisational performance. The rest of this paper is organised as follow: in the following section we briefly present the theoretical foundations and hypotheses of our study. We then present a brief discussion of our methodology followed by an analysis and a discussion of our findings then a conclusion.

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Theoretical foundations and hypotheses

Inter-organisational researchers have devoted considerable time investigating the driving factors, the implications and impacts of collaboration. They have employed a wide range of approaches and theories to explain what motivates organisations to work together (Sowa, 2009). The literature on inter-organisational collaboration shows that resource dependence theory (Pfeffer and Salancik, 1978), inter-organisational relations theory (Kogut and Singh, 1988; Alexander, 1995) and transaction cost theory (Williamson, 1991) have been the most widely used theories to explain collaborative relationships. Despite their popularity in inter-organisational research, these theoretical perspectives have weaknesses that have been documented in the literature. They have, for example, been criticised for not paying sufficient attention to environmental constraints as well as other contextual and organisational process factors (Galaskiewicz, 1985; Oliver, 1990; Cigler, 1999). Such oversight is even more problematic in the humanitarian collaboration context where the environment can be very dynamic and often involves both for-profit and non-profit organisations. In this study, we combined two theoretical lenses including social network and RBV. Social network theories investigate the patterns of relationships among network members and the structural network attributes (Wasserman and Faust, 1994). A large body of literature applies social network theories to the study of inter-organisational networks and performance. Network structural characteristics (density, centrality, clique and clique overlap) have been found to have implications on performance (Ahuja and Carley, 1999; Tsai and Ghoshal, 1998; Tsai, 2000; Nohria and Garcia-Pont, 1991; Provan et al., 2007). Similarly, the embeddedness of organisations in networks of external relationships with other organisations holds significant implications for organisation performance (Granovetter, 1985; Uzzi, 1996, 1997, 1999; Gulati et al., 2000). RBV explains performance exclusively through internal resources (Barney, 1991; Prahalad and Hamel, 1990). RBV theory conceptualises organisations as heterogeneous entities consisting of bundles of idiosyncratic resources (Penrose, 1959; Rumelt, 1984; Wernerfelt, 1984). The RBV theory posits that organisations possess two types of resources, those that enable them to achieve competitive advantage and those that lead to superior long-term performance. Barney (1991) identifies two preconditions for competitive advantage including resource heterogeneity and imperfect mobility.


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2.1 ICT and organisation performance ICT describes any technology that helps to produce, manipulate process, store, communicate, and/or disseminate information (William and Sawyar, 2005). Research has shown that ICT contributes significantly to the improvement of organisational performance (Mukhopadhyay et al., 1995; Brynjolfsson and Hitt, 1996; Kohli and Devaraj, 2003; Melville et al., 2004). For example, Melville et al. (2004) found that ICT is valuable to organisations, offering potential benefits ranging from flexibility and quality improvement to cost reduction and productivity enhancement. Research has also revealed that the dimensions and extent of ICT value depend on a variety of factors, such as the type of ICT, management practices, and organisational structure (Dewan and Kraemer, 2000; Cooper et al., 2000). Some other studies have shown that the use of ICT may have a positive impact on inter-organisational collaboration and coordination (Malone and Crowston, 1994; Kumar and Van Dissel, 1996). According to Kumar and Van Dissel (1996), ICT plays two important roles on inter-organisational collaboration. First, ICT enables collaboration by providing the necessary tools that make collaboration feasible. Second, ICT provides support to sustained collaborative inter-organisational relationships by reducing transaction costs. However, the use of ICT for humanitarian inter-organisational coordination and collaboration gives rise to many novel challenges such as problems of information standard and information overload. These challenges originate not only from the general organisational characteristics but also from those of ICT. Challenges are also related to the inter-organisational context, to the non-profit sector and to the emergency response context. Researchers have explored coordination related issues in humanitarian NGOs networks. Saab et al. (2008) investigate the extent to which organisational characteristics such as structure, number of members and funding influence outcomes as well as what organisations see as the critical priorities for facilitating coordination. Van Gorp et al. (2008) investigate how and in which situation coordination occurs within a humanitarian coordination network. The study also explores the benefits and constraints for coordination of very small aperture terminal (VSAT) deployment for development and relief purposes. Maitland et al. (2009) identify similarities and differences between IM and ICT challenges to inter-organisational coordination. They also identify requirements for resolving these challenges. In our investigation, we found it difficult to assess the actual use of ICT resources among members of the GlobalSympoNet. Instead, we considered the variety of ICT available in an organisation. We distinguished three major categories of ICT resources – communication, collaboration and community – based on their functionality (Clearinghouse, 2008a, 2008b, 2008c). Our hypothesis is the following: Hypothesis H#1 The greater the variety of ICT available in an organisation, the higher its performance.

2.2 Network characteristics and organisation performance We investigated three networks in the GlobalSympoNet community. We use four network structural characteristics including:

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1

degree centrality

2

structural holes

3

density

4

cliques.

2.2.1 Degree centrality Degree centrality measures capture the actors with the most ties to other actors in the network (Freeman, 1979; Wasserman and Faust, 1994; Kilduff and Tsai, 2003). The higher an actor’s degree centrality value the more direct links that actor has with other actors in the network (Wasserman and Faust, 1994; Kilduff and Tsai, 2003). The degree centrality of a network member may be seen as an indicator of its potential communication activity (Freeman, 1979). In the literature, centrally located network members are assumed to be most important, while peripheral network members are least important (Knoke, 1990; Wasserman and Faust, 1994; Stevenson and Greenberg, 2000; Kilduff and Tsai, 2006). The centrally located members are enabled by their position to accomplish their purposes, but the peripheral members are constrained by their position to powerlessness (Stevenson and Greenberg, 2000). Centrally located network members are likely to have advantages of information and resources compared with those on the periphery since information and other resources are assumed to flow more within the centrally located positions of a network (Knoke, 1990). Most network researchers assume that peripheral network members are somehow disadvantaged as compared with the centrally located members. However, peripheral members may want to stay in peripheral positions. For example, peripheral actors have minimal obligations to others.

2.2.2 Structural holes Structural holes theory (Burt, 1992; Wasserman and Faust, 1994; Kilduff and Tsai, 2003) highlights the benefits associated with making contacts that offer links to additional resources without the costs associated with having more contacts than needed. According to Burt (2000), an organisation can obtain important performance advantages when exploiting indirect relationships with partners. The absence of direct relationships among an organisation’s partners (the presence of structural holes) indicates that these partners are located in different parts of a network, that they are connected to heterogeneous sources of information, and that their invitations to interact present the focal organisation with access to diverse opportunities (McEvily and Zaheer, 1999). Network researchers have investigated the effect of structural holes on network members. Members bridging structural holes have been frequently shown to perform better than other members of the network (e.g., Finlay and Coverdill, 2000; Hargadon and Sutton, 1997). Studies have also shown negative performance effects for firms maintaining positions in open networks (e.g., Ahuja, 2000; Dyer and Nobeoka, 2000).

2.2.3 Density Kilduff and Tsai (2003) define density as the number of links between members of the network compared to the maximum possible number of links that could exist in the network. Researchers have used the concept of density in a number of


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inter-organisational network studies and in various contexts (e.g., Brown and Ashman 1996; Provan and Sebastian, 1998; Krackhardt, 1999; Sparrowe et al., 2001; Reagans and Zuckerman, 2001). For instance, findings from Brown and Ashman (1996) suggest that dense networks of local organisations indicate high levels of social capital. Some other studies produced counter-intuitive results. For instance, Provan and Sebastian’s (1998) study of the networks of mental health agencies operating in three cities showed that the city with the lowest network-wide density of ties among agencies had the highest effectiveness, whereas the city with the highest density of ties among its agencies had the lowest effectiveness.

2.2.4 Cliques A network clique consists of actors who all are interconnected but have no common links with anyone else in the network (Wasserman and Faust, 1994; Kilduff and Tsai, 2003). In an inter-organisational network, cliques may form on the basis of shared demographic characteristics (Mehra et al., 1998). Cliques can also be created based on the provision of a certain set of services (Morrissey et al., 1994; Provan and Sebastian, 1998). Studies on cliques in inter-organisational networks have found that they can play important roles in the creation of positive outcomes (Provan and Sebastian, 1998; Lerch et al., 2006). Provan and Sebastian (1998), for example, found that network performance can be explained through the intensive integration via network cliques. The following two hypotheses are meant to assess the impact of the interaction of ICT and network structural characteristics on organisation performance. Hypothesis H#2 Organisations that possess a wide variety of ICT will benefit more from high network degree centrality to enhance their performance than those that do not. Hypothesis H#3 Organisations that possess a wide variety of ICT will benefit more from high network density to enhance their performance than those that do not.

3

Research method

3.1 Research site We studied organisations members of the GlobalSympoNet, a community of interest spearheaded by the United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA, 2002, 2007a, 2007b). The GlobalSympoNet began its activities in 2002 as a meeting of humanitarian IM professionals. This community of interest is made up of about 300 information technology (IT) and IM professionals from roughly 120 international and national organisations in the field of humanitarian assistance. The goals of the GlobalSympoNet include: 1

to foster collaboration among members on humanitarian IM related projects

2

to disseminate best practices of information exchange

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3

to sensitise its members on the critical aspect of humanitarian IM preparedness

4

to facilitate headquarter-field partnerships and to advocate for more funding from donors for humanitarian IM related projects.

While the issues confronting the humanitarian community are global in scope, there are clearly regional differences in both the types of problems as well as the appropriate solutions. Since the Geneva 2002 Global Symposium, a total of three regional humanitarian information network workshops were held in Bangkok 2003, Panama City 2005, and Nairobi 2006 that focused on the regional dimensions of the humanitarian IM. According to UNOCHA (2007b), the goals of these workshops are: 1

to bring together regional IM professionals in order to strengthen the professional community of practice

2

to discuss the principles and best practices in IM, especially those which have been developed at the regional level

3

to deepen understanding of the regional issues and priorities that will help build a plan for improving information exchange in the region.

Figure 1

Global symposium project collaboration sub-networks


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The recommendations from these workshops reinforced the need for attention to the promotion of standards, user requirements, quality of information, appropriate responses, tools and technology, and strong partnerships. The research participants were representative of organisations member of the GlobalSympoNet who attended to at least one of the five GlobalSympoNet meetings. UNOCHA provided us with the list of all the attendees of the various Global Symposium meetings. They were almost all high ranked senior staff (e.g., CEO, CIO, and IT Director) in their organisations. For theoretical reasons, we subdivided the GlobalSympoNet community into different sub-networks. Although the members of the GlobalSympoNet are all interested in humanitarian relief and especially humanitarian IM and exchange, they theoretical differ on a number of characteristics including their missions and goals, their sources of funding and their mode of governance. We identified three sub-networks (Figure 1) including the non-governmental organisations (NGO) subnet, the United Nations agencies (UNA) subnet, and the governmental organisation (GO) subnet. Separating members of a network into subnets and analysing how they overlap can be an important means for understanding how the network as a whole is likely to facilitate or constrain certain actions of these members (Sydow and Windeler 1998).

3.2 Data collection We collected data through multiple sources including surveys, interviews and online database search. However, a survey instrument containing network-related questions was our main data collection source. We conducted a series of three surveys during October 2007, May 2008 and July 2009. Survey questions included the following four categories: 1

respondent’s organisation information

2

the GlobalSympoNet+5 on humanitarian IM community issues

3

GlobalSympoNet+5 collaborative benefits and effectiveness

4

the community inter-organisational networks.

For questions concerning the inter-organisational network, survey participants were provided with the list of members of the GlobalSympoNet community and were asked to identify: 1

those with which they had collaborated on humanitarian projects

2

those with which they had advice relationships.

We used the answers to this question to generate the GlobalSympoNet collaboration networks. Overall, representatives from 56 organisations answered the survey questions. From September to December 2009, we conducted 19 phone-based semi-structured interviews with organisational members of the GlobalSympoNet. Interview participants were asked to state the factors that influence their organisation’s decision to engage in collaboration with other organisations on humanitarian IM projects. A subsequent question focusing on the implications of ICTs was also asked. Our intent was to supplement the quantitative survey data with a more detailed description and explanation of activities in the GlobalSympoNet community. Each interview lasted between three

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quarter and one and half hours. The majority of questions were taken directly from the survey with the intent to maintain a semblance for comparison between the surveys and interviews. The interviews were transcribed manually and coded both deductively and inductively (Epstein and Martin, 2004). Our third data source was the ReliefWeb Financial Tracking Service (FTS). FTS is an online database which records all reported international humanitarian organisations receiving financial assistance (OCHA, 2010). We collected data related to the number of funded projects for organisations in the Global Symposium community. Data from the FTS database has been used in a number of academic manuscripts and reports to donors (e.g., Walker et al., 2005; Tomaszewski and Czárán, 2009).

3.3 Measures 3.3.1 Performance We used the number of funded projects in humanitarian relief as a measure for assessing organisation performance. The number of funded projects also indicates the level of activity, which is an important performance factor in humanitarian disaster assistance. We considered that the more an organisation is involved funded projects, the higher its performance. In choosing this measure, we considered the opinion of research subjects. For instance, during interviews, we asked research subjects about an appropriate measure of performance in the humanitarian inter-organisational community. We present below some quotes from their answers. Subject# 10: I think you need to look at the level of coordination and funding. How much of funding have organizations successfully secured to work in this area? The extent to which there are working with other partners or coordinating. Subject# 11: It is probably easier to use the money which has been given because that will at least express a certain level of satisfaction of what we are doing. Because we are funded by volunteering contribution from donors. So at least I would say that if we get a lot of money for one of the other projects that at least indicate the level of satisfaction from our stakeholders. So maybe that is a better one.

3.3.2 ICT resources As mentioned earlier, we found it difficult to assess the actual use of ICT resources among member of the GlobalSympoNet. We considered the variety of ICT available in an organisation. We distinguished three major categories of ICT resources – communication, collaboration and community – based on their functionality. A survey item was included to group and count these resources for each of the organisations.

3.3.3 Network structural characteristics We used the UCINET software (Borgatti et al., 1999) to compute network structural characteristics. These characteristics include: 1

degree centrality

2

density

Humanitarian inter-organisational collaboration network 3

structural hole

4

cliques.

4

Data analysis

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We used the multiple linear regression method to investigate the relationships between three organisational internal characteristics (size, range of service provided and ICT), ego-network characteristics, network structural characteristics and performance in a network of international humanitarian organisations. In order to examine separately the influence of each category of the independent variables on the dependent variable, we developed four models as described in Table 1. In this paper, we focus our analysis on ICT and the interaction effect of ICT and network characteristics on performance. Table 1

Organisational performance variables

Variable level

Variable

Organisation

Size Service Com_Med

Ego-network

Size of the organisation Range of services provided by the organisation Varieties of communication media (e.g., internet, Website)

Coll_SM

Varieties of collaboration social software (e.g., wiki, shared db)

Cty_SM

Varieties of community social software (e.g., Facebook)

Centrality

Network Interaction

Definition

Degree centrality of the organisation in the network

Bridge

Structural hole value of the organisation in the network

Cliques

Number of distinct cliques to which organisation is a member

Density

Density of the network to which organisation is a member

Com_Med × Density

Interaction between communication media and density

Com_Med × Centrality

Interaction between communication media and centrality

4.1 Models building As a first step in the model building process, we computed basic statistics to check the correlation between the variables. Table 2 reports the descriptive statistics and correlations between the variables. All of the correlations between the independent variables and the dependent variables were positive. This was an indication that organisations that have higher numbers on these variables would tend to display higher performance level.

2.37

1.71

2.08

45.55

21.98

0.53

0.09

69.46

0.21

253.01

Service

Com_Med

Coll_SM

Cty_SM

Clique

Centrality

Bridge

Density

Com_Medxcentrlity

Com_Medxdensity

Funded_Projects

1.6

523

0.17

124

0.04

0.37

31

116

0.79

0.65

1.2

2.3

0.264*

0.231

0.179

0.283

0.108

0.200

0.221

0.142

–0.0.56

0.106

0.483**

1

0.107

0.022

0.079

–0.081

–0.016

0.057

0.088

0.183

–0.016

0.176

2

Notes: N = 56 **correlation is significant at the 0.01 level (2-tailed) *correlation is significant at the 0.05 level (2-tailed)

3.35

3.10

Size

SD

.393**

0.668**

0.565**

–0.022

0.383**

0.46**

0.384**

0.691**

0.674**

3

0.209

0.427**

0.396**

–0.047

0.328**

0.365**

0.261*

0.753**

4

0.274**

0.376**

0.406**

–0.122

0.262*

0.384**

0.312*

5

0.627**

0.526**

0.888**

0.256

0.407**

0.875**

6

0.699**

0.524**

0.958**

0.214

0.601**

7

0.336*

0.379**

0.524**

0.094

8

0.351

0.636**

0.215

9

0.770**

0.613**

10

0.643**

11

0.724**

12

Table 2

M

30 L-M.N. Tchouakeu et al.

Descriptive statistics and correlations

0.259

Cty. media

0.176 0.052

P

Adjusted R2

56 0724

0.129

56

1.79†

–2.31*

0.37

–0.69

0.92

t

0.734

1.62†

–7.89**

–4.34**

10.81**

0.000

–1.214

–0.406

1.910

Notes: †p < 0.1; *p < 0.05; **p < 0.01. Standardised coefficient and t statistics are reported.

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N

ComM × Density

ComM × Centrality

Interaction

Density

–7.62**

–4.31**

10.64**

0.219

1.45†

0.040

–0.059

0.082

β

–0.276

0.39

–1.06

1.58

t

Model 3

–2.12*

0.000

–1.183

Clique

Network

–0.410

Bridge

0.176

–0.257

0.042

–0.089

0.133

β

1.913

1.16

–0.74

1.01

–1.05

1.46

t

Model 2

Centrality

Ego-network

0.195

–0.165

Coll. media

Service

Com. media

0.223

–0.162

Size

β

Model 1

0.667

0.120

56

–0.87

–0.77

1.17

t

0.751

2.08*

1.56†

–8.37**

–0.433

1.959

0.237

–0.277

–0.268

–0.040

0.091

β

0.465 56

–1.60

–0.50

0.757

2.34*

–1.09

–8.59**

–4.81**

11.52**

2.02*

–2.43*

0.000

–0.157

t 1.07

B (density)

–0.1307

Model 4

–3.75**

4.61**

2.24*

–2.37*

0.000

–1.335

–0.352

1.392

0.271

–0.274

–0.111

–0.063

0.101

β

A (centrality)

Table 3

Organisation

Variable

Humanitarian inter-organisational collaboration network 31

Regression analysis on performance measured as the level of collaboration

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We then built four models to investigate the independent and interaction effects of the organisation and network level variables on organisational performance. We built these various models using a linear combination of the dependent variables. We checked the non-linear approach and found no improvement in fit of the models. In Model 1, our baseline model, we modelled performance as a function of the variables of the organisation category. This model shows the regression results for the effects of organisational characteristics only, on performance. In Model 2, we added the independent variables of the ego-net category. Model 3 included the independent variables of the network category. Finally, in Model 4 (the full model) we used all the independent variables including the interaction terms. We build separately a full model for each of the two interaction terms. We examined all the models for collinearity issues. We used the variation inflation factor (VIF) for this endeavour. The VIF values for the variables in all four models were not higher than 8. These values indicated the possibility of collinearity but we decided to keep all of the variables in the models. In Table 3, we provide a summary of the four models. We found six variables that were important predictors of performance. These include two variables of the organisation category (collaboration social software and community social software, the three variables of the ego-net category (degree centrality, bridging structural hole, number of cliques), and the network category variable (network density). The relationship between these variables and performance was consistently either positive or negative across models. The two interaction terms were also found to significantly contribute to explain performance. The explanatory power (adjusted R2) of the models gradually increased ranging from approximately 5% for the baseline model to nearly 76% for the full model. In the full model, the variables in the organisation category accounted for approximately 5.2% of the variance while those of the ego-net category explained 67.2%. The network category variable accounted for 1% of the variance while the interaction term explained 1.7% (Model 4a) and 2.3% (Model 4b).

5

Discussion

We begin this discussion section by restating that previous studies that used the theoretical lenses of RBV primarily focused on characteristics internal to the organisations to predict performance and performance. Most of these studies were conducted in the for-profit sector, conceptualising organisations as independent profitseeking entities (Arya and Lin, 2007). Subsequent research on organisation performance and performance highlighted the importance of viewing organisations as embedded in a web of inter-organisational relationships which may serve both as resources themselves and as mediums for accessing external resources (Baum and Dutton, 1996; Portes, 1998; Gulati et al., 2000; Shiplov, 2006). However, most studies that apply social network approach to explore organisational performance tend to focus on the characteristics of network structure, without paying much attention to the attributes of the organisations that comprise the network. In our study, we draw on both the RBV and the social network theories to investigate how organisations’ attributes, especially ICT resources, combined with network structural characteristics influence organisational performance. Summarising our hypotheses testing, while our results partially supported our first hypothesis (‘The greater the variety of ICT available in an organisation, the higher its


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performance’), we found full support for our second and third hypotheses (‘Organisations that possess a wide variety of ICT will benefit from high network degree centrality and network density to enhance their performance’). In the following section, we discuss our findings with regards to: 1

the relationship between organisation internal characteristics and organisational performance

2

the impact of the interaction between ICT and network structural characteristics on organisational performance.

5.1 Impact of organisation internal characteristics and performance Our research showed the importance of considering the characteristics internal to organisations when explaining performance. When using only the organisational internal resources as independent variables to predict effectiveness, the regression model showed that the linear combination of these variables was significantly related to effectiveness. Taken alone, organisations internal characteristics explained only approximately 5% of the variances in organisational performance. This finding is consistent with previous studies that used the RBV to assess organisational performance (e.g., Zaheer and Bell, 2005; Arya and Lin, 2007). Moreover, the findings of our investigation suggest that among humanitarian organisations engaged in IM and exchange, ICT would be one of the most important internal characteristics that would more accurately predict effectiveness. Previous research has shown an increase in the adoption and use of ICT for disaster relief among humanitarian organisations (Comfort, 1993; Quarantelli, 1997). For these organisations, ICT plays a vital role in disasters relief. Research has shown, for instance, that the use of ICT may have a positive impact on inter-organisational collaboration and coordination (Malone and Crowston, 1994). Studies have also highlighted the importance of the use of social media in humanitarian disaster relief and crisis management (Palen et al., 2007a, 2007b; Palen and Liu, 2007c; Sutton et al., 2008; Vieweg et al., 2008; Hughes et al., 2008; Liu et al., 2008). Although most of these studies investigated the use of social media at the individual user level of analysis, the positive impact of these tools for disaster relief should also be measured at the organisational level and the network level. In our study, all three categories of ICT variables (communication, collaboration and community) were found to significantly contribute to explain organisational performance. However, not all of these ICT related variables were positively related to organisational media were found to be positively associated with performance, we found a negative relationship between collaboration social software (e.g., wiki, shared database) and performance.

5.2 Inter-action effect of ICT and network structural characteristics on performance One of the important findings of our study is related to the catalytic role of ICT on organisational performance in humanitarian inter-organisational networks. For instance, our findings suggest that organisations that possess a wide variety of different types of communication ICT resources (e.g., internet – available to the majority of staff, website –

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regularly updated, blogs, etc…) will benefit more from high network degree centrality to enhance their performance than those that do not. These organisations will also benefit more from high network density than those that do not possess these technologies. These findings are illustrated by the interaction plots presented in Figure 2 and Figure 3. Figure 2

Inter-action effect of technology and degree centrality on performance as measured by the level of collaboration

An examination of these interaction plots highlights the significant boost of communication ICT resources on the performance of organisations that are centrally located in the humanitarian IM networks. As mentioned earlier, these plots also show that organisations that possess a wide variety of different types of communication ICT resources will benefit more when they belong to high network density than when they are member of loosely connected networks. These results of our statistical analysis concerning the interaction effect of ICT and network structural characteristics on humanitarian organisations performance were somewhat supported by the findings from the qualitative data gathered through interviews. As mentioned earlier, interview participants were asked to give their opinion on the implications of ICT on inter-organisational collaboration among members of the GlobalSympoNet and the contribution of these technologies in helping to meet organisational goal. Approximately 70% (68.42%) of the interviewees shared their opinion on this issue. We registered a wide range of diverse point of views. While some participants had a very positive opinion about the implications and especially the catalytic role that ICT plays in fostering humanitarian inter-organisational, others expressed mixed feelings.

Humanitarian inter-organisational collaboration network Figure 3

35

Inter-action effect of technology and network density on performance as measured by the level of collaboration

The participants who expressed a positive opinion about the catalytic role of ICT in humanitarian inter-organisational collaboration represented roughly 31% (30.77%) of those who answered the question. Almost all of these participants were from centrally located organisations in the network. For these, ICT served as an important catalyst for inter-organisational collaboration in the GlobalSympoNet community. They argued that without ICT effective communication is difficult and collaboration would be more difficult. Participant number five, for example, reported that: Subject#5: I think that information technology is extremely important because we basically need to communicate to all these different communities in as many different ways as possible.

Participants also believed that the use of ICT is instrumental in quickly gather analyse and disseminate humanitarian information leading to effective disaster response. Below, we illustrate this point of view with quotes from three participants, number six, seven and 11. Subject#6: You cannot do it without information technology. Gathering information, managing information, analyzing information, distributing information, really you cannot do all this without information technology. So I think the question is kind of obvious. Subject#7: Information technology essentially supports what we do. It helps in sharing information, mainly transporting information around, maintaining our communication. Subject#11: I think the information technology is key of cause, because without proper systems in place, you will not be able to do that.

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Most of these participants who had positive opinions about the implications of ICT in fostering collaboration among humanitarian organisations also believed that ICT was instrumental for their organisations in meeting their goals and thus contributed to increasing organisational performance. The participants who expressed mixed feelings about the role of ICT in inter-organisational collaboration were mostly from organisations at the peripheral of the networks. These participants gave a number of reasons related mainly to the ICT infrastructure. Participants argued that more often, organisations in the field do not have the necessary technology tools either because they were destroyed by the disaster or because they never existed. They also talked about differences in infrastructure between organisations based in developed countries and those in the developing countries. They argued that people in developed countries often enjoy the latest technologies but the reality in developing countries, scenes of most humanitarian disasters, is quite different. Participant number 12, for example, reported that: Subject#12: when you get out on the fields you see that the most basic important tool is paper map and a pencil. And I think we have got to really recognize that fact. […]You know we do this information technology that we love where they follow the latest systems and the fastest processor and stuff like that and we really like to paddle ourselves on the back on what we are able to do here in Washington DC. And then you get out on the fields and everyone is using paper maps and a pencil.

Finally they talked about the fast pace of change in technology, which makes it difficult for organisations to hire and retain a technical staff that possesses adequate knowledge to make use of these new technologies. Subject#6: as the technology changes, it is hard to find the people that have skills that are up to date.

6

Conclusions

Our findings suggest that organisational performance is affected by different organisational and network attributes in humanitarian IM networks. More broadly, our findings pointed to a need in inter-organisational social network studies to go beyond a structuralist view and take into consideration the characteristics of individual organisations, as predicted by the RBV, in assessing performance. Our study also suggests that organisational level network studies that tend to overlook resources internal to organisations may be missing a large source of variance in effectiveness. Finally our study highlights the important role of communication media in organisational performance among humanitarian organisations. One practical implication of this study is that using social network analysis to explore networks of humanitarian organisations engaged in IM and exchange provides a significant benefit to the international community. The network diagrams depicting project collaboration and advice relationships among humanitarian organisations demonstrate the reach accomplished in humanitarian IM and exchange. Linking these network structures and organisational characteristics to performance helps to highlight important determinants of effectiveness among organisations in the humanitarian relief field. This provides the opportunity for humanitarian organisations and especially UNOCHA to consider weaknesses and strengths of the Global Symposium in increasing


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network effectiveness in managing and exchanging humanitarian information. Identifying the ICT tools that the Global Symposium community needs for better humanitarian information exchanged would be an extension of this study worthy of consideration. The results of this study should be considered in light of several limitations. Of particular concern, is the potential sampling bias due to the fact the survey participants were not selected through any scientific sampling technique. Rather, the survey was conducted on a sample defined by UNOCHA thereby generating an organisational bias. Another limitation to the study concerns the source of information. The network data was constructed based on information provided by individuals. Although most of our survey participants were high ranked senior staff in their respective organisations, they might not always have complete information about the organisation’s relationships and the motivations for these relationships. Third, due to the low response rate relative to the number of potential collaboration partners, connections in the network are not necessarily reciprocal. That is, if only one of the two organisations indicated a relationship, we count this connection. Thus, the analysis favours inclusion over validity. Finally the most obvious and probably the most serious shortcoming of the research is the small sample size, which is, unfortunately, a common problem when the unit of analysis is an organisational network. Although we had 56 organisations, our study involved only three networks. This can create an important problem with regards to generalising our findings. The results of our research point to some suggestions for future research. For instance, much previous research has highlighted the important impact that alter characteristics have on organisational effectiveness (Arya and Lin, 2007). In our research design, we did not include any of these characteristics. Future research in the humanitarian relief field may consider building models that would help to assess the effect of alter capabilities organisational effectiveness. For example, current literature suggests that the exchange of humanitarian information between organisations is highly challenging. Understanding how and why beneficial network structure captures alter organisation capabilities may help to better understand the inter-organisational humanitarian IM and exchange.

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