2016 Effect of the Information Use Environment on

Effect of the Information Use Environment on Social Capital in a SocioReligious Community in Singapore

Masturah Binte Abdul Aziz

Wee Kim Wee School of Communication and Information

A thesis submitted to the Nanyang Technological University in partial fulfilment of the requirement for the degree of Master of Science (Information Studies)

2016

Abstract This study aims to explore the relationship between the information use environment (IUE) and social capital of a socio-religious community in Singapore. The IUE framework is defined by Taylor (1991) as the set of elements which affect the availability of, access to and use of information by a group. Social capital is one of the major constituents of social cohesion (Berger-Schmidt, 2002) and has received much interest in the research field, especially in community studies. In the information science field, social capital is becoming an important consideration and an emergent research front in information behaviour studies (Fisher, Erdelez, and McKechnie, 2005). This is particularly relevant in the context of socio-religious institutions like mosques and churches, which can be identified as information producing institutions (Lievrouw, 2000) and where strong social capital is needed to build cohesiveness and generate productive output within the community (Uslaner, 2012). The hypothesis is that a strong IUE is a significant enabler in fostering social capital within a socio-religious community in an information society such as Singapore. Survey research was used, with constructs drawn from the IUE framework, and social capital indicators. Data was collected through purposive sampling from three mosques in Singapore and 210 participants respectively. Descriptive statistics and regression analysis were used to study the interactive effects between the IUE and social capital. Findings showed that information practices and uses of information interact with each other to influence social capital. Information use for civic engagement was found to be the overall significant predictor of social capital, as well as the information retrieval system of the mosque and system-user interactions. However, differences in information practices attributed to the digital divide in the mosque community, as well as information availability from the mosque may negatively affect social capital. Implications from the findings are discussed in the context of how the elements of the IUE can be channelled to build social capital for social- or community-based organizations, as well as further efforts into more in-depth research in this promising area of social capital in information behaviour studies.

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Acknowledgements Bismillahir-Rahmanir-Raheem In the name of Allah, the Most Compassionate, the Most Merciful. He who has opened this journey to me, guided me through the obstacles, uplifted me when I almost gave up, and blessed me with the circle of special people who mentored, guided and supported me from the start right through to the end. All Praises is to Him. I dedicate this dissertation to my supervisor, Professor Joanna Sin Sei Ching, with whom without her I would not have been able to complete this dissertation, nor progressed so far. Her expertise, understanding, and patience inspired me to be my best, uncovered hope in myself, and made my graduate experience an extremely meaningful one. I am immensely grateful and indebted to her; her dedication, support and guidance is beyond what words could describe. I am privileged to have had the best mentor and supervisor a student could ever have. My sincere thanks go to my wonderful ‘research assistants’, my cousins Afiqa Md. Elias and Umairah Abu Bakar who helped me extensively and whole-heartedly through the data collection and writing process. It was a daunting process moving across mosques to engage patrons to participate in the survey and keep track of all the survey returns, and I wouldn’t have been able to complete the data collection on task amidst all the challenges had it not been for Umairah’s support and help. It was an equally challenging task to organize all the data into Excel sheets, format the numerous statistical output tables and preparing the manuscript according to the proper formatting styles and guidelines, and I owe my gratitude to Afiqa for her tremendous support while I was juggling work, data analysis and writing. I would like to also thank my parents and siblings for their continuous support, and for letting me camp out indefinitely at the dining table with all my books, papers and laptop cluttering the space for what seems like an indefinable amount of time. These apparent or hidden gestures of support are not lost on me nor forgotten. My heartfelt thanks go out to my mom, Fatimah Beeve bte Abdul Karim, and my aunt, Zaubidah bte Mohammad for their precious support in the data collection as well. I would also like to extend my gratitude to all who had encouraged and supported me as I embarked on this journey; and to my friends Choo Li Lin and Ysa Marie Cayabyab for cheering me on, supporting me and being there for me. And my deep appreciation goes to the

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respondents of the survey, who were so rich at heart, and without whom I would not have been able to complete my dissertation. I reserve special thanks to my loving husband, Ahmad Mazrhulnizam, for his never-ending patience as I missed out on numerous family outings, spent all of my weekends, leave from work and free time on this dissertation, and many long nights immersed in my writing. Thank you for selflessly giving me the space and time at the expense of time to be with you and with family. And I would like to dedicate my love to Yara and Kira, for their company through the long nights writing. The warmth of their fur as I was working was such a comfort and blessing, and their

amusing

antics,

while

distracting,

refreshed

and

cheered

me

on.

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Table of Contents Abstract…… ................................................................................................................... i Acknowledgements ....................................................................................................... ii List of Tables and Figures ........................................................................................... vi Chapter 1

Introduction ............................................................................................. 1

1.1.

Background of Study........................................................................................ 1

1.2.

Research Objectives ......................................................................................... 1

1.3.

Context of Study............................................................................................... 3

Chapter 2

Literature Review ................................................................................... 5

2.1.

Terminologies in Information Behaviour Research ......................................... 5

2.2.

User Studies in Information Behaviour Research ............................................ 6

2.3.

Context in Information Behaviour Research .................................................... 8

2.3.1. Defining

the

Boundaries

of

Context:

Organisational

and

Non-

Organisational Settings ................................................................................ 9 2.4.

The Information Use Environment (IUE) ...................................................... 11

2.4.1. The Information Use Environment in the Mosque .................................... 12 2.5.

The Concept of Social Capital ....................................................................... 20

2.6.

Social Capital in Community Social Organisations ....................................... 23

2.7.

Social Capital in Information Studies Research ............................................. 25

2.8.

Uses and Gratifications Paradigm .................................................................. 27

Chapter 3

Methodology .......................................................................................... 29

3.1.

Research Method ............................................................................................ 29

3.2.

Research Design ............................................................................................. 29

3.2.1. Data Collection Procedures..................................................................... 29 3.3.

Sampling......................................................................................................... 30 iii

3.3.1. Study Population ..................................................................................... 30 3.3.2. Sampling Frame ...................................................................................... 30 3.3.3. Survey Instrument & Measures .............................................................. 33 3.4.

Study Constructs ............................................................................................ 34

3.4.1. Independent Variables ............................................................................ 34 3.4.2. Dependent Variables ............................................................................... 34 Chapter 4

Results and Analysis ............................................................................. 36

4.1.

Demographics................................................................................................. 36

4.2.

Information Practices and the IUE of the Mosque Community ..................... 37

4.2.1. Characteristics of the “Set of People” within the Mosque IUE ................. 37 4.3.

The Interaction between “Setting” and “Sets of People”: Social Networks as a Medium of Information Transfer within the Mosque IUE ............................. 43

4.3.1. “Problems” and “Problem Resolution”: Information Use of the Mosque Community Members within the IUE Framework .................................... 45 4.4.

Interactions between IUE and Social Capital ................................................. 49

4.4.1. Descriptive Statistics for IUE and Social Capital Variables Examined ... 50 4.4.2. Linear Regression Analysis ...................................................................... 51 4.4.3. Stepwise Regression Analysis .................................................................. 55 Chapter 5 5.1.

Discussion............................................................................................... 67

The Importance of Individual Information Practices in Influencing Social Capital of the Mosque Community ................................................................ 67

5.2.

The Importance of Institutional Factors in Influencing Social Capital in the Mosque Community ....................................................................................... 69

5.3.

The Importance of Information Use in Building Social Capital in the Mosque Community ..................................................................................................... 71

Chapter 6 6.1.

Conclusion ............................................................................................. 73

Summary of This Study.................................................................................. 73 iv

6.2.

Contributions of This Study ........................................................................... 73

6.3.

Limitations of This Study............................................................................... 74

6.4.

Future Research Directions ............................................................................ 75

References… ................................................................................................................ 77 Appendix A... ............................................................................................................... 85 Appendix B.. .............................................................................................................. 105 Appendix C.. .............................................................................................................. 110

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List of Tables and Figures Table 2.1 ....................................................................................................................... 15 Table 3.1 ....................................................................................................................... 31 Table 4.1 ....................................................................................................................... 36 Table 4.2 ....................................................................................................................... 39 Table 4.3 ....................................................................................................................... 39 Table 4.4 ....................................................................................................................... 41 Table 4.5 ....................................................................................................................... 41 Table 4.6 ....................................................................................................................... 42 Table 4.7 ....................................................................................................................... 43 Table 4.8 ....................................................................................................................... 45 Table 4.9 ....................................................................................................................... 47 Table 4.10 ..................................................................................................................... 47 Table 4.11 ..................................................................................................................... 51 Table 4.12 ..................................................................................................................... 52 Table 4.13 ..................................................................................................................... 52 Table 4.14 ..................................................................................................................... 52 Table 4.15 ..................................................................................................................... 53 Table 4.16 ..................................................................................................................... 53 Table 4.17 ..................................................................................................................... 53 Table 4.18 ..................................................................................................................... 53 Table 4.19 ..................................................................................................................... 54 Table 4.20 ..................................................................................................................... 54 Table 4.21 ..................................................................................................................... 54 Table 4.22 ..................................................................................................................... 54 vi

Table 4.23 ..................................................................................................................... 56 Table 4.24 ..................................................................................................................... 56 Table 4.25 ..................................................................................................................... 57 Table 4.26 ..................................................................................................................... 57 Table 4.27 ..................................................................................................................... 58 Table 4.28 ..................................................................................................................... 59 Table 4.29 ..................................................................................................................... 60 Table 4.30 ..................................................................................................................... 60 Table 4.31 ..................................................................................................................... 61 Table 4.32 ..................................................................................................................... 62 Table 4.33 ..................................................................................................................... 62 Table 4.34 ..................................................................................................................... 63 Table 4.35 ..................................................................................................................... 64 Table 4.36 ..................................................................................................................... 65 Table 4.37 ..................................................................................................................... 65 Table 4.38 ..................................................................................................................... 66

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Chapter 1

Introduction

1.1. Background of Study In recent times, there is a culmination of interest in research on the central importance of social capital in community empowerment, sustainability and action (Bordieu, 1986; Lochner, Kawachi, & Kennedy, 1999; Putnam, 1995). The concept of social capital, defined as resources consisting of and embedded within a network of social relationships (Bourdieu, 1986), initially appeared in community studies, and is a dominant factor in the broader concepts of social cohesion, social quality and in studies of “quality of life”, which is now seen as the dominant goal of societal development (Berger-Schmitt, 2002; Putnam, 1995; Schuller & Field, 1998). Currently, it is widely used as a theoretical framework to assess the social environments of communities in terms of the resources of information, norms and social relations which enable people to coordinate collective action and to achieve common goals. The applications and use of social capital theory in research is diverse, spanning across fields such as health, religion, organisational and management studies, and communication research (see Forbes & Zampelli, 2013; Lochner, Kawachi, & Kennedy, 1999; Nahapiet & Ghoshal, 1998; Shah, McLeod, & Yoon, 2001). Complementary to the increasing attention being given to studies on social capital is the growing research in the role of information as central in fostering social capital. Within the theme of social capital in information science research, particularly in information behaviour studies, one of the main areas of investigation is the development and growth of various forms of communities through sharing of information and knowledge (Choo, 1996; Durrance, Walker, Souden, & Fisher, 2005; Nahapiet & Ghoshal, 1998; Widen-Wulff & Ginman, 2004). The assumption is that information is a key resource in knowledge creation and sharing, and that social capital is the main driver of collaborative information behaviour through its various dimensions such as trust, norms, obligations and social relations (Nahapiet & Ghoshal, 1998; Widen-Wulff & Ginman, 2004). However, while the mutual relationship between social and informative aspects is commonly studied, Widen-Wulff & Ginman (2004) observed that empirical research on the relation between information behaviour and social capital pertaining to organisations and communities is not as prevalent.

1.2. Research Objectives This study aims to explore the relationship between information behaviour and social capital through examining the information use environment (IUE) of a socio-religious community in Singapore. The goal is to provide theoretical insights and empirical research findings that

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contribute towards conceptual or practical methods of fostering community engagement and building social capital through the study of information behaviour. In exploring the IUE in fostering social capital, this study also considers the context and viewpoint of Singapore as an Information Society, where the creation, distribution, use, integration and harnessing of information and information and communication technologies (ICT) will thus consequently have an impact on the social environment and building of social capital within communities in Singapore. This dissertation explores empirically how institutional and community information is transferred and used by members in a socio-religious community in ways that influence social capital within the community. The socio-religious community in this context pertains to the Islamic community in Singapore, and the focus of the study is specifically on the mosque as a socio-religious institution. Main Research Question (RQ): How do institutional factors and individual information needs and use influence social capital within the socio-religious community of Singapore mosques? Sub RQ: 1) What is the Information Use Environment of the mosque? 2) How do institutional aspects influence the use of information to build social capital in the mosque community? 3) How do technology- and systemic-user interactions influence the formation of social capital in the mosque community? 4) What are the different uses of information that build social capital in the mosque community? Currently, there exist few studies, especially empirical research, on the relationship between the social capital and information environment, as well as in-depth studies of the Islamic community in Singapore. The present study aims to contribute towards this emergent research front, by providing empirical and indigenized insights, through information science perspectives, into the phenomenon of social capital in Singapore using an in-depth study of one of the major socio-religious communities that make up its society. Thus, this study may be able to contribute findings which shed light on 1) The significance of the IUE as an indicator in measuring social capital

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2) The differences in information use within the community in relation to the sociostructural and demographic factors that shape the community 3) The effect of community information on social capital 4) The role of the information environment in influencing the different elements of social capital 5) Insights and recommendations of future research relating to information behaviour studies and community groups

1.3. Context of Study As one of Southeast Asia’s most economically prosperous and dynamic regions, Singapore remains a highly religious society, with 85% of Singaporeans having an affiliation with one of the main religious traditions within the country, which include Buddhism, Taoism, Christianity, Islam, Hinduism, and traditional Chinese religions (Singapore Department of Statistics, 2010a). Indeed, one of the most interesting aspects of Singapore’s modernisation is that the drive for economic and technological modernisation has not been accompanied by a decline in personal religious beliefs and practices (Pereira, 2005). With Singapore continuing to be a highly religious society, religious institutions have to ensure that they keep pace with the times (Kluver & Cheong, 2007). For one, in response to the “informatisation” of the Singaporean society, religious leaders have sought to remain faithful to their religious traditions while also incorporating technology into an overall programme of religious recruitment, teaching, mobilisation, and encouragement (Kluver & Cheong, 2007). According to the Mosque Convention 2011 (MC11) report, “Change is the only constant in the world. So must our mosques respond to the imperative for change and confront the challenges around them” (MUIS, 2011a, p. 40). The mosque is seen as the heart of the Muslim community, a key institution in the religious life of Muslims. According to the Islamic Religious Authority of Singapore (MUIS) Annual Report 2014, “mosques not only serve as a place of worship but are modern hubs of the socioreligious life of the community. The modern mosque is not only equipped with the latest technology and facilities that cater to the diverse needs of the community, but also retains its character as a welcome solace for congregants of all ages looking for a centre of worship, spiritual renewal and a conducive place for Islamic learning” (p. 23). With its accessibility to the Muslim community, mosques are able to be more responsive to local needs, such as through the creation of demographic-specific programmes or customisation of its services (MUIS, 2011a). These are initiated through youth, family and community friendly schemes,

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providing support and guidance as well as inviting collaboration and volunteerism. The mosque is thus a driving force of social capital within the Muslim community. This is in fact, not a phenomenon exclusive to mosques alone. According to Greeley (1997), religious structures are a strong resource for generating social capital not only for its own religious projects but for diverse other secular voluntary efforts as well. In a study by Hodgkinson et al. (1996) on American civic participation, it was found that religious structures themselves lead to the act of volunteering, with 52% of over 5000 respondents indicating that they have volunteered, and the largest proportion of the volunteers attributed religious structures such as the church, synagogue, or temple as reason for their volunteering. Even in studying drop-out rates of Catholic and other religious schools as compared to public and nonreligious private schools, Coleman (1988) found that these religious structures generated substantial social capital which mediated drop-out rates. While religion is related to high stocks of social capital, it is also acknowledged that religious institutions themselves require considerable social capital to function and sustain its activities. The relationship between the institution and the people it is serving needs to be strengthened in order to bring the greatest value to the community (Taylor & Chatters, 1988). Engagement, interaction and consultation with members of the community are key elements in developing community building and involvement amongst individuals in the community. In that light, many efforts have been put in place to strengthen this relationship, be they in respect of institutional management, systems, infrastructure and programmes. According to the MC11 report (MUIS, 2011a), “Mosques, like every other institution, must adapt and reposition their role within this new complex reality of modern life. The mosque must square up with the realities of modern life. Only then can the institution remain relevant to the everyday lives of people, as it once did in the past.” (p. 9). Through this lens, the information science perspective is valuable in studying how the mosque, as an information-producing institution, generates social capital through information flow, exchange and information use. This is particularly because within social worlds such as the mosque community, the use of information by its members will influence their actions. Furthermore, this information use (or non-use) is dependent not only on the subject matter, but on other contextual elements within the social world. In this respect, the IUE model provides a useful framework for investigating the information environment and its role in generating social capital in the mosque as it takes into account the attributes of information users, which are the members of the mosque community, as well as the structural, organisational and social settings in which these users are situated.

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Chapter 2

Literature Review

This chapter starts by reviewing the terminologies in information behaviour research. User studies and contexts in information behaviour research is then reviewed. This is followed by a discussion on the Information Use Environment as well as its application in the mosque context. The concept of social capital, the role of social capital in community organisations and social capital in information behaviour research are then discussed. Lastly, the Uses and Gratifications theory is discussed as a theoretical backing to empirically measure the information needs and retrieval as a function of users’ motivations to seek and use information within the context of the study.

2.1. Terminologies in Information Behaviour Research In information science, the term “information behaviour” typically refers to the study of information needs, seeking and use (INSU) (Wilson, 2000). However, various researchers have coined different terms to refer to INSU research, such as “information practices” and “information activities”, in part due to conceived epistemological and ontological differences associated with the term “behaviour” (Kari & Savolainen, 2003; McKenzie, 2003; Dervin & Nilan, 1986). Conceptually, however, Taylor (1991) defines information behaviour to be the sum of activities through which information becomes useful. Thus, for the purposes of this study, the term “information behaviour” will be primarily used, and interchangeable with “information practices” and “information activities” in recognition of the diverse set of information-related activities which converge into information use. For the intent of this study, it is also important to further define and identify the distinct elements of information seeking, information needs and information use. The term “information seeking” is often applied to a wide range of activities beginning with an information need. In the context of this study, information seeking is viewed as a process which is iterative and variable over time and context (e.g., Kuhlthau, 1991, 1993; Taylor, 1968). According to Bates (2002), information seeking must be considered “with respect to all the information that comes to a human being during a lifetime, not just in those moments when a person actively seeks information” (p. 3). Bates (1989) had highlighted in an earlier work the value and nature of both undirected and semi-directed browsing as part of a group of information seeking activities which is not part of a systematic process but rather, involves the pursuance of leads as they emerge. Therefore, in the information seeking process, this study notes that there is also a tendency to encounter useful information without consciously searching for it and that this phenomenon may vary according to the seeker’s knowledge,

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problems, state of mind, availability of a rich information environment, and other factors (Erdelez, 1996, 1997; McKenzie, 2003; Williamson, 1998). This study also notes that while there is a strong emphasis on the role of information needs, the identification or discovery of a need may not be a necessary precursor to information seeking, and on the other hand, it could also be imposed on the seeker by a third party (Gross, 1999, 2001; Wilson, 2000). It is also important to further note that, especially in user-focused studies, information seeking may never progress to information use or “information searching”, which defines the ‘micro-level’ behaviour of a seeker in interacting with information systems of all kinds, be it human computer interaction or information retrieval (Wilson, 2000). In a final point to note on INSU research, information that is sought or encountered may not ultimately be used (Audunson, 1999; Frohmann, 2004; Hjorland, 2000; Lievrouw, 2001; Taylor, 1991). In summary, current literature on INSU highlights that in the information needs, seeking and use process, the usefulness or value of information is based not only on subject matter or how well the information content matches the user’s problem or need, but also on the requirements, norms and expectations that arise from the user’s interactions within contexts. This approach to information needs, seeking and use process is important to clarify in this research as it ultimately impacts the information use environment (IUE).

2.2. User Studies in Information Behaviour Research In the field of library and information science (LIS), INSU studies make up a small percentage of approximately eight percent (Julien & Duggan, 2000). Initially, a large focus of INSU research was on the use of systems and services, labelled “systems based studies” or “traditional user studies”. These systems-based studies focus on the “information system”, in which the use of information was seen to be primarily dependent on how well the system could respond to users’ information needs through precision and recall. A smaller number of studies concentrated on what users say they need. Gradually, researchers found that systems-based studies could not effectively account for the actual use of information or contribute towards the design or operation of information providing systems due to a limited understanding of users gained from this approach (Courtright, 2007; Rosenbaum, 1996; Taylor, 1986). Together with the radical transformation of information services brought upon through the use of new technologies, this led to a paradigm shift in the approach to a “user-centred approach” or user studies as we know it today (Pettigrew, Fidel, & Bruce, 2001). This shift was first characterised and described by Dervin & Nilan (1986) as a move-away from the study of people interacting directly with information systems to the study of the people themselves and

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how they seek and use information. User studies emphasise not only on the understanding of information practices from the human standpoint but also to view them as a process that takes place within specified situations and contexts (Vakkari, Savolainen, & Dervin, 1997; Wilson & Allen, 1999). A key difference between user-based studies and systems-based studies lies in the assumptions about the contexts and situations in which the user seeks and uses information. In a systemsbased approach, user actions such as information seeking and use are largely determined by structural features, such as the information systems with which they interact; whereas in a user-centred approach, the information problems and needs of the users are used to explain their information seeking and use activities, thus taking on an action-oriented stance (Dervin & Nilan, 1986; Savolainen, 1993; Taylor, 1986). With this shift of focus from systems to users, information needs become something more ambiguous and occurs in problems or incomplete states of knowledge where users attempt to make sense in particular situations which are definite but dynamic (Dervin, 1982). Information uses are regarded as interactions and actions in which individuals construct sense and resolve problems as they navigate situations and contexts (Choo, 2006; Rosenbaum, 1996). However, even with the focus on a user-centred approach, researchers in the information science field have acknowledged that there is still little progress in understanding actual use of information or much impact in the improvement of information services. Some researchers question the adequacy of descriptive user studies in that they do not provide enough information for system designers and policy makers, and push for a new genre of user studies that goes beyond these descriptions (Hewins, 1990; Mick, Lindsay, & Callahan, 1980). One of the reasons for this could be due to the inability of one particular approach, be it systems-based or user-based, to account for both structure and action adequately. Rosenbaum (1996) puts forth the argument that a system-based approach uses a “top-down strategy” to explain the relationship between structure and action; focusing on the organisational structure of the social world but rather disregarding individual actions and social interactions. On the other hand, a user-based approach uses a “bottom-up strategy” which starts from social interactions, the premise being social worlds, institutions, and structures exist only because of the social interactions of individuals. The importance of the issue and the difficulties that arise in resolving it lies in the question of how, and in what ways, the action of individuals is related to the structural features of the social worlds they are connected to (Dervin & Nilan, 1986; Rosenbaum, 1996).

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Researchers have since advocated for user studies that generate models of information utilization which addresses systemic elements while putting a focus on the user (Dervin & Nilan, 1986; Mick, Lindsay, & Callahan, 1980; Paisley, 1968; Palmer, 1991; Rathswohl, 1983; Wersig & Windel, 1985). This emphasis on an integrated approach in user studies produced new models of information seeking and use. Examples of such models are the Anomalous State of Knowledge (ASK) by Belkin, Oddy, and Brooks (1982), Sense Making by Dervin (1982), Information Seeking Process (ISP) by Kulthau (1993) and the Information Use Environment (IUE) by Taylor (1986, 1991). Of these models, Taylor's work on the IUE offers promising grounds to bridge the gap between structural and action-oriented approaches within a single conceptual framework. The IUE not only focuses on the study of information in its social contexts but also puts the user at the centre of the framework. It is also a framework which has sound conceptual underpinnings (Durrance, Walker, Fisher, & Souden, 2005; Francis, 1998) and the ability to “generate propositions concerning [information] channel selection, amount of seeking, effects on productivity of information quality, quantity, currency and diversity” (Paisley, 1968, p. 3). This study thus adopts the Information Use Environment as the main driving theoretical framework based on these arguments as presented above as well as its strong emphasis on context.

2.3. Context in Information Behaviour Research Context, in information behaviour research, is generally defined to be a “frame of reference” for information practices (Vakkari, Savolainen, & Dervin, 1997). Several terms in information science are also related to context, such as “setting” (Pettigrew, 2000), “environment” (Lamb, King & Kling, 2003; Taylor, 1991), “information world” or “life-world” (Chatman, 1996; Lievrouw, 2001; Meyers, Fisher, & Marcoux, 2009; Talja, 1997) and “information grounds” (Fisher, Durrance, & Hinton, 2004; McKenzie, 2003; Savolainen, 2009). These alternate terms for context pertain to different usage of the concept, mainly arising from factors such as the different constructions of the particular context, the position and roles of the individuals within the context, as well as the boundaries that define the context. Further to that, there is little consensus within the literature as to how such a context is established or how it operates with regards to information practices (Courtright, 2007). This leads to multiple theories or propositions as to how contexts influence or are influenced by information practices, and consequently, how researchers should study information needs, seeking and use from a usercentred perspective within such a context. The challenge thus lie in conceptualising context in empirical research, especially its role in the study of information needs (Courtright, 2007; Dervin, 1997; Johnson, 2003).

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The following sections will discuss some of the overlying considerations in conceptualising contexts relevant to this study.

2.3.1. Defining the Boundaries of Context: Organisational and NonOrganisational Settings Traditionally, context is conceptualised in terms of spatial and temporal factors that indicate where and when information seeking occurs (Savolainen, 2006). Such conceptualisations draw on the assumption that context is a kind of a time–space “container” where phenomena reside and activities take place, constrained by the boundaries of the context. The container model leads to the thought that context is a set of stable, delineated entities that can be conceptualised independently of the activities of their participants. However, scholars such as Dervin (1997) criticised such conceptions and suggested that context should be approached as something that changes over time; constructed and reconstructed through human action and interaction. Dourish (2004) contends that context is not something that describes a stable setting; but something that people do, thus it is embedded in action and practices. Numerous scholars have suggested that it may be easier to identify context for information practices within the boundaries of organisational settings rather than in everyday life activities (Fidel & Pejtersen, 2004; Johnson, 2003; Savolainen, 1998; Taylor, 1991). This could be due to the greater stability and clarity of the physical context in which the members of the organisation are part of (Johnson, 2003; Savolainen, 1998). According to Johnson (2003), organisational settings “involve recurring contacts with an interpersonal network of managers and co-workers…[is] regularly exposed to the same mediated communication channels…[as well as] stabilise an individual’s information field and in large part determines the nature of information individuals are exposed to on a regular basis” (Johnson, 2003, p. 750). Organisations thus seem to provide natural boundaries that delineate the purposive activities taking place within them (Aldrich & Herker, 1977; Kreiner, Hollensbe, & Sheep, 2006). In open organisational systems, the boundaries of context can also be widened or narrowed depending on the plausibility of the explanations for organisational behaviour obtained through selective bounding (Scott, 1987). Lamb, King, and Kling (2003), for example, widened the scope of contextual boundaries using Scott’s (1987) open organisational systems model to include extra-organisational factors such as regulations, industry-wide infrastructures and client expectations in studying intra-organisational information practices. Literature which expound on organisational settings thus suggest that identifiable structures or systemic features are integral in defining boundaries of a context in information behaviour research.

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In non-organisational settings, Johnson (2003) posits that context is more difficult to define. However, such conceptual models of context do exist, especially in more recent research, where researchers rationalise and define the contextual boundaries and information practices are studied within the set boundaries. These contextual models, while mostly grounded in sociological theories, exhibit boundaries which closely resemble that of organisations (Courtright, 2007). Nardi and O’day (1999), for example, stressed on the diverse array of human activity that is bound within a closed setting in their model of “information ecologies”. Davenport, Higgins & Somerville (2000) views the home as a micro-organisation, and Fisher and colleagues (Fisher et al., 2005; Fisher, Durrance, & Hinton, 2004; Pettigrew, 1999) developed a contextual model called an “information ground”, which is an “environment temporarily created when people come together for a singular purpose but from whose behaviour emerges a social atmosphere that fosters the spontaneous and serendipitous sharing of information” (Pettigrew, 1999, p. 811). In “people [coming] together for a singular purpose” (Pettigrew, 1999, p. 811), another important bounding element for context which can be derived across the literature on both organisational and non-organisational settings is the “sense of purpose” or common goal/direction of the set of people being bounded by the context. These models thus emphasise on social interactions as important in defining contexts surrounding information practices as well as sources. Sociological concepts such as “way of life” and psychological concepts such as “mastery of life” also constitute important bounding factors of contexts. The literature on context in information behaviour research highlights the importance of human, social, and structural aspects of the environment on behaviour. It is thus important to examine the effects of these contextual elements on information seeking and use. This present study draws upon structural or systemic settings, as well as on social interactions and sociological and psychological concepts to define the contexts and situations in the IUE. According to Taylor (1986, p. 15), “the environment, in many complex ways, determines what information is acceptable (i.e., has value) for clarification, solution, or alteration of a problem, or for the accomplishment of a task.” A study of an IUE thus focuses on "organisations, people, and problems in ways that are useful to the design of information systems and to the understanding of the interface between system and human user" (Taylor, 1986, p. 220). By exploring systemic and user perspectives as contextual elements in the IUE, the present study is an attempt to contribute to a new building block in user studies and information behaviour research in general.

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2.4. The Information Use Environment (IUE) Taylor’s (1991) Information Use Environment (IUE) centralizes on the process of information transfer, due to its approach which focuses on “users and the uses of information, and the contexts within which those users make choices about what is useful information to them at particular times” (p. 218). Taylor’s framework is highly influenced by the work of Dervin (1983), one of the key figures in developing a “social theory” of information seeking that focuses on the importance of context. Dervin’s (1983) Sense-Making Approach posits that it is context which links an individual’s information seeking process to information problems arising from a particular situation. In Taylor’s (1991) IUE, the framework is defined as “the set of those elements that (a) affect the flow and use of information messages into, within, and out of any definable entity; and (b) determine the criteria by which the value of information messages will be judged” (p. 280). The IUE is thus a framework for understanding the users and analysing the contexts within which they make choices about what information is useful to them in resolving their problems or needs. In his research, Taylor (1991) had also demonstrated, in information terms, how a particular set of people can be defined (information characteristics); the types of problems that they encounter within a particular context (information problems); the kinds of solutions which best resolves these problems (information use); and the environmental factors that facilitate or constrain their problem solving (information seeking process). While the information environment is identified as a factor that influences people’s behaviour, the focus is more on the behaviour of a particular group rather than individual-level differences (Sin, 2009). Taylor (1991) explicates that "each group has different kinds of problems over varying time frames, different ways of resolving those problems, and consequently differing information seeking behaviours" (p. 220). Therefore, the underlying premise of the IUE is that different sets of people exhibit different information behaviours pertaining to their common needs; for example, the information behaviour of doctors will be different from that of engineers. While Taylor had applied this framework in the context of professional groups in the work environment, specifically engineers, doctors, and legislators, Taylor (1991) had expressed a hope that the IUE framework can be applied in studies outside of these contexts, for groups such as the general public, consumers and the information poor. Indeed, there are information behaviour studies which utilise the IUE in studying social groups in various settings. For example, Agada (1999) used the IUE to study the information behaviour of 20 gatekeepers or “information intermediaries” in an African inner-city community. In another study by Hersberger, Murray, & Sokoloff (2006) the IUE was used to study the information behaviour of maltreated children who have been sent to foster care programs. Other

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information behaviour scientists have also incorporated the IUE model into their research (e.g. Choo 2006; Durrance, Walker, Fisher, & Souden, 2005; Jones, 2008; Luo, 2008; White, 2003). While the literature has shown that the IUE is recognised by various scholars as a powerful framework for organising, describing, and predicting the information behaviours of different groups in different contexts (e.g. Courtright, 2007; Pettigrew, Fidel, & Bruce, 2001), there is still a lack of empirical research which applies the IUE framework in studying information behaviour, particularly in contexts which are outside of professional or workplace settings. This present study aims to contribute to this scope of IUE-related research by investigating how the IUE influences social capital in an under-researched population—a socio-religious ethnic community—and in an under-researched setting— the mosque as a socio-religious institution. In applying the IUE framework to the mosque and exploring its influence on the generation of social capital, this study also takes a dynamic and holistic view of context, in which the purposes, processes and effects of information use are seen as inextricable from the structural and environmental factors that mediate such use. The next section will discuss the elements in IUE framework and how it is applied in this study.

2.4.1. The Information Use Environment in the Mosque The IUE framework consists of 4 components, (1) Sets of People, (2) Problems (3) Setting and (4) Problem Resolution. In considering these elements, the discussion of the IUE revolves around the flow of information and the choices people make in the use of information. It is the argument of this chapter that “members of the mosque community” can be seen as a group with similar characteristics in terms of their information problems and the information use (or non-use) to resolve their problems. Therefore, a unique information seeking behaviour that can be described particular to this group. The components in the IUE framework are discussed in the context of the mosque community below:

2.4.1.1. Sets of People “Sets of people” are defined as a group of individuals who share similar characteristics or are part of a pre-defined setting. According to Taylor (1991), "though individuals have specific idiosyncrasies, there are real similarities among, for example, managers, whether they are in Seattle, Miami, or Boston” (pp. 219-220). It can be inferred that in the IUE, sets of people are groups categorised by a common identity, based on demographic and contextual factors that bind particular groups of people together, for example, professional education, occupation, or even shared values and beliefs.

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In this study, the challenge is then to define what the “set of people” constitutes in the particular setting of the mosque. What defines the common identity of the people affiliated to the mosque? In his research, Taylor (1991) categorised people into 4 classes of division, which may not be mutually exclusive to each other: the “professions” such as engineers, lawyers, scientists, teachers, and managers; the “entrepreneurs” such as farmers and business men; “special interest groups” such as consumers, citizen groups, and ethnic cultural groups; and “special socioeconomic groups” such as the information-poor, the disabled, elderly and minority groups (p. 222). In reference to Taylor’s 4 classes of division, the mosque community is likely to be identified as a socio-religious group under the “special interest” division. While the term “mosque community” may sound synonymous to “Muslim community”, it suggests a stronger focus to the context of the mosque as a socio-religious institution. Other studies pertaining to socio-religious institutions affirm this. In a study on information literacies of a church community, for example, it was found that information is sought and used to grow faith, grow relationships, manage the church, as well as to respond to spiritual knowledge gained in the church through action (Gunton, 2011). Thus, in defining the common identity of this set of people, it is the Muslim community who identify themselves with the mosque, seek to meet their spiritual needs through mosque programmes, and participate and/or benefit from community ties, activities, services and programmes generated by the mosque. Taylor (1991) also emphasised that in the IUE, the information practices of a set of people can be pre-determined by (1) demographic variables and (2) non-demographic characteristics which are shaped by socio-cultural factors, such as common assumptions and attitudes about certain phenomena and preferences for various media, information channels and social networks. Demographically, Taylor focuses only on those variables which can help define the information environment and behaviour of the group under study (pp. 222-223). Taylor found that certain variables, such as age, sex or marital status, may have little to do with the IUE of professionals such as engineers and physicians, although these variables may have an effect on individual information behaviours. He also found education to have the most appreciable effect on the information behaviour of professionals (p. 223). In outlining the non-demographic characteristics, Taylor identified media use, social networks, and attitudes toward new technology, risk taking and innovation. He illustrated how these characteristics vary with different professionals through relevant literature which discuss the information characteristics of the respective professions. For example, the studies that he drew upon points to scientists as being print-oriented and regular readers of periodical literature; engineers as using trade journals and textbooks more than professional journals; and managers as preferring face-to-face meetings or phone calls over any other communication channels. He

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also distinguished the ways and reasons in which these different sets of people utilise networks, as well as analysed their attitudes toward new technology, education, risk taking, and innovation. Ultimately, in Taylor’s exploration of the three IUEs in his research, it can be seen that these variables heavily influence the IUE and are inherently connected to three aspects of information behaviour; information use, information seeking process and information storage and transfer. In the context of the mosque community, there is a lack of research which shows how and to what extent demographic and non-demographic variables significantly affect the IUE in the mosque. However, non-demographic characteristics such as media use, social networks and attitudes towards new technology, are identified to be some of the key characteristics which shape the information practices in socio-religious institutions (see Cheong & Poon, 2009; Cheong, Poon, Huang, & Casas, 2009; Robinson, 1993; Taylor & Chatters, 1998). Also, in information behaviour literature concerning community studies and socio-religious settings, certain demographic variables has been shown to account for collective information practices. This may have an effect on the IUE of “special interest groups”. For example, gender roles and responsibilities within a particular culture or religion may be different, and different age groups within a particular social community may have different interests to pursue; hence there will be different ways of seeking and using information (for a comprehensive overview of how demographic variables affect different IUEs in non-professional settings, see, for examples, Agada, 1999; Bishop, Tidline, Shoemaker, & Salela, 1999; Caidi & MacDonald, 2008; Chatman, 1991; Kluver & Cheong, 2007; Pettigrew, 1999; Shah, McLeod, & Yoon, 2001; Singh, 2001). In conclusion, Taylor observes that “it is the organisation and conceptual structure that a set of people bring to a particular context that determines the value or usefulness of information” (Knott & Wildavsky, 1980, p. 558 as cited in Taylor, 1991, p. 223). Thus, both types of variables will be studied in how they shape the mosque IUE as well as in how the IUE can contribute to increasing social capital within the mosque.

2.4.1.2. Problems From a user perspective, Taylor (1991) acknowledges that problems are areas of doubts or uncertainties in which a user seeks to obtain clarity through information. This could be through recalling previous experiences in the form of analogies, obtaining new or affirming knowledge which influences the problem-solving, or finding out that there may be no resolution. In describing problems in the IUE, Taylor highlights three considerations. The first is that problems are not static but rather, they evolve with new information and perspectives, and thus require different information responses at different intervals. The second is to recognise that

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each IUE has a unique set of problems which are based on the setting and the requirements of the set of people. The last is related to the problem dimensions, which may have an impact on the relevance of the information responses at the user’s end. In that sense, problems influence the information seeking process as well as information storage and transfer. The IUE thus contrives that the problems focused on by a set of people greatly affect how they gauge different types of information to be useful to them. In the mosque context, information problems faced by members of the mosque community are related to the process of managing their socio-religious affairs and developing as a community. This process was measured through a study on mosque effectiveness by MUIS in 2014, using a Mosque Perception Survey which rated Muslims’ experiences with and perceptions of the mosque. The Mosque Perception Survey was distributed among a sample of about 1000 participants from various mosques in Singapore, and included non-Malay-Muslims as well as Muslims who rarely visit the mosque (The Straits Times, 2014). This inaugural survey is grouped according to the three core functions of the mosque; Enhancing Spirituality, Guiding Community and Changing Lives. A representation of some of the key questions/indicators in the survey is indicated in Table 2.1. Table 2.1 Key questions/indicators from Mosque Perception Survey conducted by MUIS Enhancing Spirituality

Number of mosque goers who have attended Islamic classes in the mosque Language medium preferred for Islamic learning Guiding Community Perceived ease in obtaining assistance on religious matters from the mosque Number of mosque goers who have contacted mosque staff pertaining to various matters Perceived transparency in managing the collection of funds Perception of the mosque as inclusive in engaging different groups in the mosque community such as the elderly, disabled, youth, women and the poor and needy Changing Lives Number of mosque goers who have volunteered at the mosque Perception that the mosque promotes volunteerism Perception that the mosque is innovative in rolling out new programs and activities Perception that the mosque reaches out to non-mosque goers Perception that the mosque encourages community participation Note: These indicators were presented orally and through visual slides during a Mosque Leaders Meeting in 2015

These indicators reflect the current information flow in mosque community, and are the contexts which will impact the information seeking and use (or non-use) of members, as well as their resultant actions. Through the Mosque Perception Survey findings, this present study thus elicited the information problems of the mosque community to be as below:

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•

How do I know what programmes and activities are offered in the mosque? How are these programs relevant to my needs?

•

Where and how can I get help or contribute help in the mosque?

•

What are the programmes available which offers spiritual knowledge that addresses my particular needs?

•

How do I participate in mosque activities?

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How do I connect with people who have the same interests as me?

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How do I participate in community-building in the mosque?

•

What specialised services can I get from the mosque?

Overall, more empirical evidence is needed to concretely identify mosque community problems, through an understanding of members' motivations in seeking information as well as how they plan to use the information they uncovered. It is currently also unclear what dimensions these problems fall under and how it will impact relevance of information. As there is an apparent lack of research on information problems faced by groups such as the mosque community, this study thus hopes to contribute in this area by seeking a better understanding of the types of problems faced by the mosque community and the information relevant in solving their problems.

2.4.1.3. Setting For Taylor (1991), the setting is "concerned with physical context and with ways of describing the context in which a specific class of people usually works and lives, and which affects the way they seek and make use of information" (p. 226). Taylor acknowledged that the nature, attributes and infrastructure of different institutions and organisations will influence the information behaviour of different classes of their users. This includes how information is disseminated and organised, as well as the availability and accessibility of information resources. Taylor also postulates that the information sources, information relevance, information transfer and exchange within a group is influenced by the functions of an organisation, as well as the history and experience that grows with the organisation as it handles complex tasks and the management of information more effectively. In the mosque setting, there are several elements in the setting that can influence these information processes. One element is the nature and role of the institution, i.e. the reason for the existence of the institution. In the context of this study, the core functions of the mosque as a socio-religious institution are to increase faith of the community through knowledge, provide guidance and service to those in need and change lives -through community and social development (MUIS, 2011a).

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Based on the MC11 report, “While mosques have made considerable progress in implementing socio-religious programmes for the Muslim community over the last 5 years, their fundamental role in contributing effectively to the development of a Singaporean Muslim community can be further strengthened by ensuring that they remain anchored to core Islamic values. To do so, mosques must not only be a place for performing congregational prayers and disseminating religious knowledge but also a centre for enhancing the community’s spirituality…” (p. 44). Another aspect of the mosque setting that may influence information processes and behaviour of its members is the initiatives set in place to achieve its goals. This is outlined in the strategic intents of the mosque to sustain its core functions, which is by developing strong networks of relationships and interactions within the mosque community and become central in the lives of the Muslim community: “Tied to unique historical contexts, mosques have been the focal point not only for worship but also for all facets of life….It is with respect to this rich history and experience that we should revisit the role that our mosques should play – within our current context – and determine how best we can create this space which is not only for worship but one that can organically engage the community, create opportunities for progress and truly change lives. The mosque has to regain this spirit of interaction with the community so that Muslims will feel a strong attachment to the mosque. Only with this interaction can the mosque have a greater impact in changing the lives of Muslims. To locate it in our context, mosques’ efforts should aim to become effective touch points by enhancing its outreach, establishing strong support bases within its congregation, increasing efforts to increase participation in the programmes and work towards addressing the socio-religious development of the community as a whole” (MUIS, 2011a, p. 64). The final characteristic of the mosque setting that may influence information processes is the infrastructure of the mosque, which includes its use of technology for information dissemination, storage and transfer. In a Singaporean study by Kluver & Cheong (2007) on the Internet and religion, findings show that religious leaders, including Muslim leaders, view the Internet as a positive tool for the religion, and find it valuable for disseminating information and contributing positively to their religious communities. The religious leaders also believed that the Internet was something that religious congregations, temples, or organisations should use. In understanding the IUE of the mosque, it is thus important to consider these characteristics and how they influence the information behaviour and information processes of the mosque community. This study views the mosque as an “information producing” institution, and therefore playing a direct role in information creation, dissemination and storage within the mosque community. These elements will thus be discussed in terms of the systemic elements

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of setting in the IUE. The focus will be on understanding how the systemic functions and user contexts of the IUE interact with each other in the IUE in problem resolution of the mosque community and consequently how it will affect the generation of social capital.

2.4.1.4. Resolution The fourth and final dimension of the IUE is concerned with the ways in which a set of people solve or gain control of the problem they face and the kinds of information that they use to do so. According to Taylor (1991), the questions typically asked in the problem resolution aspect of the IUE is, “What constitutes for a given set of people, resolution of a typical problem? What kinds of information (amount, degree of relevance, quality, format, etc.) do people in a particular set anticipate? What filtering mechanisms exist? What are the attitudes towards the benefits and costs of information use? What are the criteria of information choice? What does information do for people in specific settings?” (p. 228). The focus of the problem resolution dimension is thus information use, and information use in turn is based on the criteria for selection of useful information. The criteria people use to choose information have been studied by various scholars, spanning from user appreciation to user perception of information value (Francis, 1998). These studies found reliability, quality, format quality and timeliness to be such selection criteria. Taylor (1986) also surfaced evaluative criteria he classified as six "criteria of choice": (1) ease of use, (2) noise reduction, (3) quality, (4) adaptability, (5) time saving and (6) cost saving (p. 50). However, Taylor also ascribed values to these criteria which he observed underpin the evaluation of information. For example, the “quality” criterion is linked to user-conceived values such as accuracy, comprehensiveness, reliability and validity (Taylor, 1986, p. 229). In this sense, the IUE also emphasises that attitudes and approaches to problem resolution influence information seeking and use. In Taylor’s words, information use is controlled by “the ways a given set of people view their problems and what they anticipate as resolution" (p. 229). Various literature also show that users’ decisions on which information to select is not only based on a set of identifiable criteria, but also on a set of values that underpin the choice of these criteria. Halpern and Nilan (1988), for example, found through the Sense-Making approach that some criteria centred upon affective values, such as trust or sense of self. The relevance of information is also critical in problem resolution. Literature has highlighted the importance of situational variables in influencing user perceptions of information relevance (Wilson, 1973). Cuadra & Katter (1967) found that the characteristics of the information medium, the level of difficulty and style, relevant knowledge level of users, and background and attitudes affected relevance. Judgement conditions, such as time available to make

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judgements, are also important (Barry; 1994; Cuadra & Katter; 1967). The researchers also found that these variables relate to the situation of the user, such as their needs, bias, as well as their familiarity with the information they were receiving. Also, problems are usually not as straight-forward as being resolved by a single question and answer. They require different types of information deemed necessary in the process of resolution, and hence, different uses of information.

Taylor proposed eight classes of

information use which are created by the needs of users in specific situations. These are information use for (1) enlightenment; (2) problem understanding; (3) instrumental; (4) factual; (5) confirmational; (6) projective; (7) motivational; and (8) personal/political. Taylor (1991) has specified that there is a strong need for more studies in the IUE of different populations working in varying contexts, how individuals in these populations perceive their information problems, and how the use (or non-use) of information affects their concerns. These eight classes will be discussed further in the results section in informing how members of the mosque community use (or not use) information to resolve their problems, and consequently how it influences the generation of social capital in the community. Taylor (1991) also surfaced problem resolution as being content-oriented, where there are identifiable traits inherent in information beyond subject matter that can be related to the dimensions of problems and to the needs of people. He cited the work of MacMullin and Taylor (1984) in identifying several of these information traits such as quantitative continuum, data continuum, temporal continuum, solution continuum, focus continuum, specificity of use continuum, aggregation continuum and causal, diagnostic continuum. The kinds of information within these traits might include descriptions, graphics, images, facts, guides, practical information, or even idea generation. Each of this kind of information may bear characteristics such as being relevant, timely, credible, or obsolete, and can be acquired through various sources, be it print, non-print, or through human interaction. For example, social networks of peers or relatives are a source for specific and reliable information. Moreover, such networks or interactions could act as a crucial catalyst in translating information use into action, which has direct relations to the concept of social capital as well as its generation (see Hazleton & Kennan, 2000; Johnson, 2007; Kahema, Kashiha, Mbote, & Mhando, 2014; Miller, 2014; Nahapiet & Ghoshal, 1998; Widen-Wulff et al., 2008). The subsequent sections of the literature review will thus examine the concept of social capital, its importance in problem resolution and community development, and how IUE characteristics and contexts specific to the mosque community may have a direct influence in its generation.

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2.5. The Concept of Social Capital The social capital theory is a promising social scientific approach that has garnered wide interest and a significant body of research in multiple disciplines (e.g. Durrance, Walker, Fisher, & Souden, 2005; Lochner, Kawachi, & Kennedy, 1999; Miller, 2014; Nahapiet & Ghoshal, 1998; Schuller & Field, 1998; Stanton-Salazar & Dornbusch, 1995; Widen-Wulff & Ginman, 2004). According to De Souza Briggs (1997), social capital is a term that emerged forty years ago to describe resources that are neither in the traditional forms such as money or economic assets nor ascribed to human capital in terms of skills or talent, but stored in connections among people (see also Jacobs, 1961). In early conceptions of social capital, its value lies in the development of an individual through the set of resources residing within family relations and community social organisations within the individual’s sphere of influence (Loury, 1977). Social capital has, in more recent times, been broadly defined as a “resource-for-action” which functions at various levels of social institutions such as the family, neighbourhood, city and society (Coleman, 1988; De Souza Briggs, 1997; Putnam, 1993). It is becoming a widelyapplied concept in the study of social phenomena, particularly in the development of human capital (Coleman, 1988; Loury, 1977, 1987). As such, social capital is now becoming increasingly popular in the study of organisations and social systems, where it is valued as a “collective good” driving organisations and communities to function better (De Souza Briggs, 1997; Putnam, 1993). For example, a plethora of studies conducted has shown social capital to be a strong factor in improving the economic performance of firms by facilitating inter-unit resource exchange and product innovation (Tsai & Ghoshal, 1998), strengthening interorganisational learning (Kilpatrick, Bell, & Falk, 1999; Kraatz, 1998) and supporting the creation of intellectual capital (Nahapiet & Ghoshal, 1998). Social capital is also influential in economic studies across geographic regions (Putnam, 1993, 1995) and nations (see Fukuyama, 1995). Contributing the first pioneer work in social capital theory, Bordieu (1986) conceptualised social capital to be “the aggregate of the actual or potential resources which are linked to possession of a durable network of more or less institutionalised relationships of mutual acquaintance and recognition—or in other words, to membership in a group—which provides each of its members with the backing of the collectivity-owned capital, a “credential” which entitles them to credit, in the various senses of the word” (p. 281). He posited that some of the resources, whether physical or intangible, are available to members of a group through a web of networks consisting of contacts or connections. For example, through “weak ties” and

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“friends of friends”, network members can gain access to information, knowledge and to various forms of opportunities. He also theorised that some resources within social capital are generated through sense of obligations arising from feelings of gratitude, respect and friendship within social interactions, as well as from the rights and norms that come with social institutions one is affiliated to – such as a family, a class, a religion or a school. According to Portes (2000), Bourdieu’s definition thus highlights two different elements which forms social capital, one being the social networks which allows access to resources, and the other being the amount and quality of the resources itself. While Bourdieu’s pioneering work conceptualised social capital as resources which are socially maintained and accessed within relationships, Coleman (1988), whose independent work was published shortly after, defined social capital by its function, which is primarily its ability to aid members in that particular group to achieve specific ends (Coleman, 1988). Coleman (1990b) states, “My aim ... is to import the economists' principle of rational action for use in the analysis of social systems proper …and to do so without discarding social organisation in the process. The concept of social capital is a toil in aid in this” (p. 98). According to Greeley (1997), Coleman outlined the elements of social structures that can generate social capital. This is as summarized below: 1) Obligations, expectations, and trustworthiness of structures 2) Informational channels and networks 3) Norms and effective sanctions, such as those pertaining to social justice 4) Closure of social networks, in which all actors interact with each other 5) Multiplex relationships in which resources of one relationship can be appropriated for use in a second relationship (for example, parents of students in mosque madrasahs are also volunteers in the mosque) He viewed social capital as a type of resource which is embedded within a social structure, able to facilitate actions of individuals, whether as independent persons or as corporate members within the structure (Coleman, 1990a). He further specified that changes in relations between individuals leads to the production of social capital, accomplished through communications (Coleman, 1988). Coleman’s work sparked a great interest in social capital theory amongst scholars in the various disciplines, and subsequently in more recent times, Robert Putnam, who drew upon the work of Coleman, published a series of influential work (1993, 1995) on American civil society which garnered a renewed interest, particularly in areas of social cohesion, civic-

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engagement and community-based studies (Brehm & Rahn, 1997; De Souza Briggs, 2007; Johnson, 2007). Putnam (1993) redefined social capital as a key characteristic of communities rather than of individuals and regards networks of civic engagement to be at the very core of social capital. The premise is that strong networks foster cooperation and enable communities to coordinate and solve collective action problems. He conceptualised social capital to consist of several elements, namely (1) networks which constitute the civic community and its density, (2) the norms of cooperation, reciprocity and trust which govern these networks, and (3) a sense of belonging and solidarity within the civic community, leading to civic engagement and participation in the civic institutions. Putnam thus suggests that a community with strong social capital will be more likely to prosper due to the establishment of effective civic institutions able to maintain order and a governing structure. He further stipulated that the level of social capital in society can be measured by indicators such as the density of membership in voluntary associations, the extent of interpersonal trust between citizens, and their perceptions of the availability of mutual aid (Putnam, 1993, 1995). While there is a general agreement by the principal theorists of social capital on the importance of networks and relationships in fostering social capital, a lack of consensus on a precise definition of social capital is apparent (Harpham, Grant, & Thomas, 2002; Johnson, 2007; Portes, 2000). Scholars have also voiced challenges in its conceptualisation and measurements (Harpham, Grant & Thomas, 2002; Payne, Moore, Griffis, & Autry, 2011; Van Deth, 2003). However, there is also a concurrence that the nature of social capital can be generalised to be: 1) The degree of connectedness, as well as the quality and quantity of social relations in a given population. 2) High levels of interpersonal trust and norms of mutual aid and reciprocity which act as resources for individuals and facilitate collective action, and consequently, 3) A collective dimension of society in which the individual is a part of. De Souza Briggs (1997), however, emphasised that a distinction should be made clear between social capital and its elements such as trust and norms; these elements should not be seen as synonymous to social capital. He also made the distinction between social capital and civic engagement, where he defines civic engagement is a means of generating social capital through useful connections with people. Similarly, Lochner, Kawachi, & Kennedy (1999), in a conceptual paper on the operationalisation and measurement of social capital, stressed that social capital is a characteristic of the social structure, whereas social networks and support are attributes of individuals within the social structure. These authors thus observe that social capital should rather be seen as a relationship between an individual and the environment.

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In summary, social capital can be seen as a complex concept which essentially represents the ability of individuals to derive benefits through membership in social networks or interactions. Further to that, there is also consensus drawn from numerous scholars that social capital is a public good which enables a greater output to be produced from the stock of physical and human capital in a society (Coleman, 1988; Cox, 1998; Lin, Cook, & Burt, 2001; Loury, 1977, 1987; Putnam, 1993). Social capital thus plays an important role in influencing change as well as sustaining a changing and adapting environment. Within the context and intent of this study, social capital is largely conceptually defined following the work of Bordieu (1986) as resources consisting of and embedded within a network of social relationships from which an individual is potentially able to derive and utilise to enable action. However, Coleman’s (1988) model of social capital is crucial in this study as it provides the empirical grounds to study how human social structures can generate social capital. Lastly, Putnam’s (1993) work on social capital is also influential in this study as highlights the generation of social capital on a community level, in terms of participation and civic engagement. It thus provides an important theoretical background on the role of social capital in facilitating active participation and action through information use within a socio-religious-institutional setting.

2.6. Social Capital in Community Social Organisations According to Coleman (1990b), social capital is the web of cooperative relationships between citizens that facilitates resolution of collection action problems. All human communities confront collective action problems, and collectively, societies thrive when their members cooperate with one another to achieve common goals (Brehm & Rahn, 1997). Recently, scholars in sociology, economics, and political science identified social capital as a comprehensive explanation for why some communities are able to resolve collective problems more effectively than others (Bowles & Gintis, 2002; Ostrom, 1994; Putnam, 1995; Rydin & Pennington, 2000; Sampson, Morenoff, & Earls, 1999; Wellman, Haase, Witte, & Hampton, 2001). In defining the term “community”, particularly in this context, it comprises any groups of people held together by common values, purpose or interests and who collaborate by sharing ideas, information and other resources, usually within some form of institutional boundaries, such as in a neighbourhood, a school or a workplace (for overviews, see Freilich, 1963; MacQueen et al., 2001; McMillan & Chavis, 1986). These communities are usually broadly labelled according to distinct characteristics, such as geographic communities, professional or common interest communities, virtual communities or even groups of businesses.

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Scholarly interests in this area is motivated primarily by the linkage between levels of social capital and collective outcomes; high levels of social capital seems to be crucial for such measures of collective well-being as economic development, effective political institutions, low crime rates and other social problems like teen pregnancy and delinquency (Bowles & Gintis, 2002; Fukuyama, 1995; Putnam, 1995). Several studies also show that variation in social capital can be explained by citizens' psychological involvement with their communities, cognitive abilities, economic resources, and general life satisfaction (Boix & Posner, 1998; Brehm & Rahn, 1997; Glaeser, Laibson, & Sacerdote, 2002; Rydin & Pennington, 2000; Woolcock & Narayan, 2000). Social capital can also be viewed as a concept that has its basis in individual behaviour, attitudes and predispositions (Brehm & Rahn, 1997; Glaeser, Laibson, & Sacerdote, 2002). Brehm and Rahn (1997) suggest that a mechanism by which social capital forms is the reciprocal relationship between civic participation and interpersonal trust. In their empirical study, they found a stronger tendency for participation to lead to interpersonal trust. They also establish that, while social capital is normally conceived as a property of communities, this reciprocal relationship between community involvement and trust in others is also a demonstration of social capital in individual behaviour and attitudes. Parallels can also be drawn between social capital and empowerment. According to various scholars, empowerment is a process which enhances possibilities for people to develop mastery over their lives (Eklund, 1999; Rappaport, 1987). As social capital is drawn upon to change or improve life circumstances and to solve problems of everyday life (De Souza Briggs, 1997), it thus forms a means for individuals to be empowered. Consequently, empowered individuals mobilise individual and collective resources for social action (Kieffer, 1984). Such individuals contribute back to the communities they are situated in by generating more social capital. Some studies, for example, have shown social capital to be inherently related to individuals’ confidence in the institutions they are involved with (Greeley, 1997). As this confidence leads to a deeper community involvement, the more citizens participate in their communities, the more that they learn to trust others, and vice versa (Ellison & George, 1994; Greeney, 1997). Thus, in studying social capital within communities, it is also important to consider the individual, as it is the individuals within the community that participate and build trust and acquire positive feelings towards each other. In the area of community development and empowerment, social capital is often drawn upon to understand the dynamics within the contextual and situational characteristics of respective communities, and how relationships and interactions between members of the community can affect its sustainable output and growth (Israel, Checkoway, Schulz, & Zimmerman, 1994). Findings from public health research have found that communities with larger stocks of social

24

capital have lower mortality rates, attributed to a higher social cohesiveness resulting from factors like trust, mutual reciprocity and common purpose (Kawachi, Kennedy, Lochner, & Prothrow-Stith, 1997; Griffiths et al., 2007). According to Coleman (1988), social capital facilitates productive activity, and a group “within which there is extensive trustworthiness and extensive trust is able to accomplish much more than a comparable group without that trustworthiness and trust” (p. 101). Furthermore, scholars of community studies such as Chavis and Newbrough (1986) posit that community development is a process that “stimulates opportunities for membership, for influence, for mutual needs to be met, and for shared emotional ties and support” (p. 56). O’Dubhchair (1999) posits that a community has two strengths — community capital and carrying capacity. Community capital refers to “all the things the community has its disposal to allow the community to live and interact productively” (p. 24), which includes the social capital it possesses, while carrying capacity is how well the community is able to enhance its capital to provide for the community's needs in the long term (O’Dubhchair, 1999). Nahapiet & Ghoshal (1998), in examining the consequences of social capital for action, found two distinct themes, firstly, social capital increases the efficiency of action and secondly, it acts as an aid to encourage cooperative behaviour, thereby facilitating the development of new forms of association and innovation within organisations or institutional structures. This has also been reiterated in other studies on social capital and communities/societies (Fukuyama, 1995; Jacobs, 1961; Putnam, 1993). Thus, as a “collective good” or a “resource-for-action” stored in connections between people (see Coleman, 1988; De Souza Briggs, 1997; Putnam, 1993), social capital forms an essential role in the process of community development. The literature highlighted in this section shows that social capital is a significant factor in understanding how individuals and communities resolve their problems, and how communities develop through social action and participation. The literature also indicates social capital to be instrumental in developing strong socio-institutional characteristics within communities that nurture a collective efficacy, sense of belonging and competence or problem-solving ability in a community. The final section in the literature review will thus touch upon studies pertaining to information science and social capital, and the role of information in generating social capital.

2.7. Social Capital in Information Studies Research There is an increasing number of studies in the information sciences field which uses social capital as a conceptual framework, such as in areas related to knowledge sharing and intellectual capital (Chiu & Wang, 2006; Huysman & Wulf, 2006; Nahapiet & Ghoshal, 1998),

25

access to information (Hersberger, 2003; Stanton-Salazar & Dornbusch, 1995; Wellman, Haase, Witte, & Hampton, 2001), community informatics (Pigg & Crank, 2004; Simpson, 2005; Williams & Durrance, 2008), and information seeking behaviour (Courtright, 2007; Huvila, Holmberg, & Widén-Wulff, 2010; Johnson, 2007; Pettigrew, Fidel, & Bruce, 2001; Widén-Wulff, Ginman, Perttilä, Södergård, & Tötterman, 2008). Among various social capital researchers, James Coleman, Nan Lin & Robert Putnam have all developed influential theories that consider the exchange or flow of information as aspects of social capital. Social network analysts, such as Nan Lin, view social capital as resources to which individuals have access through their social relationships. According to Lin, Cook, & Burt (2001), the resources of social capital include any social valued good, such as information, which are accessed and/or mobilised in purposive actions. Putnam, on the other hand, argues that social capital affects information flow, as “the networks that constitute social capital can…serve as conduits for the flow of helpful information that can help us achieve our goals” (Putnam, 2000, p. 288). He therefore posits that communities which lack such networkbased connections may find difficulty in sharing information (Putnam, 2001). While the concept of social capital may be operationalised differently depending on the point of view of the researcher, its value to information science research is in providing a framework within which to understand the relationship between social structure and information access, networks and use. For example, Widén-Wulff & Ginman (2004) discuss a theoretical framework which addresses collaborative information behaviour through the dimensions of social capital in business corporations. Central to the framework is the strong relationship between dimensions of social capital such as network ties, communicative functions and trust, expectations and obligations to information science concepts such as availability of the information resources, information exchange/transfer and information sharing. In a separate empirical study, Alkalimat & Williams (2001) discussed the role of social capital in community informatics, by using the concept of social capital as a framework for the examination of technology use in local communities. Information scientists are also interested in studying how information producing institutions can generate social capital. Johnson (2010), for example, investigated the relationship between use of public libraries and social capital, in order to understand how use of the library is related to generalized trust and community involvement. Miller (2014) did a comparative study of public libraries in Edinburgh and Copenhagen with regards to their potential for social capital creation. She found three main factors affect the library’s potential to create social capital; the

26

library building and space, the library’s staff and volunteers, and the links that the library has with the community. While the literature discussed above shows a growing focus on social capital in information science research, it is still a relatively under-researched area, particularly in research pertaining to information use environments. This study thus aims to contribute in this area to look at how information science concepts can be systematically applied through the IUE framework in investigating the phenomenon of social capital in a particular setting.

2.8. Uses and Gratifications Paradigm The uses and gratifications paradigm is a well-established theory which was originally developed in mass communication research, which suggests that people actively search out media messages, or information, to satisfy certain needs rather than being passive receivers of information (Blumler, & Katz, 1974). Blumler and Katz (1974) also suggest that being able to seek out and gather information provides people a sense of control. In satisfying their social and psychological needs, the uses and gratification theory proposes that users are actively involved in media usage and interact highly with the communication media (Luo, 2002; Rubin, 1983). It also suggests that users are goal-directed and wish to fulfil a core set of needs. This implies that the use of a medium is mainly determined by the functions it can serve, and gratifications are provided by the attributes, the content provided by the medium, and the social and physical contexts with which each medium is associated with (Katz, Blumler, & Gurevitch, 1973). Gratification of information needs is also dependent on the perceived value of being a member. It is thus widely adopted to investigate user motivations for new media uses, and has been successfully applied to understand user motivations in various information technology (IT)-related settings (Dholakia, Bagozzi, & Pearo, 2004; Zhou, Jin, Vogel, Fang, & Chen, 2011). This paradigm is also used in information science studies, particularly in information behaviour, such as in investigating information needs, information acquisition and motivations to seek and use information (Pettigrew, Fidel, & Bruce, 2001). The comprehensive model of information seeking (CMIS), for example, drew from various theories including uses and gratification (Johnson & Meischke, 1993). Williamson (1998) also used the uses and gratification theory to derive a model of incidental information acquisition. This paradigm is very relevant to this study particularly in operationalising and measuring IUE constructs, particularly as it examines user motivations in using information and the gratifications which the information mediums or the community characteristics afford to the user. In the IUE, information flow or transfer is the main driving force of the framework, and elements such as the accessibility of information, the scale of use and availability of

27

information, the media and format of information are some of attributes and functions that impact information flow and use. At the same time, it is user-centric and operates within the context and situational factors that influence user motivations in seeking and using information.

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Chapter 3

Methodology

3.1. Research Method The purpose of this study is to obtain an understanding of the IUE of the mosque, which includes the information problems, resolutions and information use of the mosque community, as well as institutional settings, may affect the generation of social capital. To collect data on the information problems and use of the mosque community, this study employs the survey method in the form of self-administered pen-and-paper questionnaires. As the focus is on information behaviour characteristics and social behaviour characteristics, survey method was chosen as it is the most appropriate when researchers want to learn about "self-reported beliefs or behaviours" (Neuman, 2011). Also, as the mosque population is relatively substantial in Singapore, survey research is observed to be the best method “in collecting original data for describing a population too large to observe directly” (Babbie, 2007, p. 244). As this study also investigates the systemic element in the Information Use Environment (IUE) of the mosque, an additional instrument which more accurately measures variables relating to the institutional setting is also required. While qualitative interviews would be the most appropriate instrument to gain an understanding of the institutional environment, due to time and resource constraints, a researcher-administered questionnaire was used to collect this data from one relevant officer working in each of the mosque involved in the study. This questionnaire was analysed quantitatively in combination with the main research instrument, the self-administered questionnaire to the mosque community.

3.2. Research Design 3.2.1. Data Collection Procedures The data collection was conducted from 1st January 2014 to 30th October 2014. During this time, individuals in the mosques under study were approached and invited to participate in the study questionnaire. Self-administered pen-and-paper questionnaire was chosen due to the varied demographic profile as well as the accessibility to the population, literacy rate, computer skills, and Internet access. As the population was situated in the mosques, online or telephone questionnaires were a less suitable mode. Furthermore, pen-and-paper questionnaires catered to the more matured demographic age group as well as people who were not tech savvy or were not connected to data/wireless networks in the mosque. Based on literacy levels, those who did not prefer to do much reading had the questionnaire read out to

29

them and responses recorded by the researcher. Translations of the English text into Malay text were also provided on the questionnaires. This questionnaire is termed as a user-based questionnaire and can be found in Appendix A. To improve response rates, participants were informed that S$1 will be donated to the mosque for every completed survey returned. At the same time, one staff member from each mosque whose work was related to information and communication was approached to fill in the systems-based questionnaire, which is a set of questions relating to the systemic elements or infrastructure of the mosque, which includes the characteristics and content of the information the mosque produces and disseminates. This is a researcher-administered pen-and-paper questionnaire, chosen in this mode to facilitate any clarifications or elaborations if necessary. The systems-based questionnaire can be found in Appendix B.

3.3. Sampling 3.3.1.

Study Population

The population of this study consists of patrons to the mosque, loosely termed “mosquegoers”. Mosque-goers include congregants, volunteers, as well as people who frequent the mosque for various reasons, such as parents of mosque madrasah or kindergarten students, regular Islamic class attendees, mosque event participants and individuals who engage in services or facilities offered by the mosque. They consist of different age groups, from youth, to working adults to the pioneer generation, between the ages of 21 years to 60 years.

3.3.2.

Sampling Frame

As this is an exploratory study, the objective is to collect a rich and in-depth informative sample rather than to aim for generalisability across the larger mosque community in Singapore. As such, probability sampling was not utilised in this study. Furthermore, approaches such as random sampling is unsuitable, as due to the nature and size of the population, it is unlikely to be able to randomly select and identify individuals in the mosque community. Purposive sampling was used in selecting individuals who frequent the mosque, by choosing the mosque as the venue to conduct the data collection. Three mosques out of the 70 mosques in Singapore (MUIS, 2013) were selected from the North, Central and North-East regions of Singapore. In the initial sampling frame, the mosques were chosen based on population distribution and location. As a rough estimate, census data on Resident Population Aged 5 Years and Over by Planning Area and Language Most Frequently Spoken at Home (Singapore Census of Population, 2010b) was used. The population of Malay-speaking households were

30

chosen as they make up the majority of Muslims in Singapore. The mosques chosen were situated in areas with the highest, median, and lower end (below 5000) of the population distribution. The table below illustrates the population distribution from Census data. Table 3.1 Resident Population Aged 5 Years and Over by Planning Area and Language Most Frequently Spoken at Home (Singapore Census of Population, 2010) Total

English

Mandarin

Chinese Dialects

Malay

Tamil

Other Indian Languages

Other

3,399,054

1,097,443

1,211,505

487,031

414,475

110,667

40,334

37,600

Ang Mo Kio

159,408

46,338

61,143

32,771

10,352

6,079

1,202

1,522

Bedok

264,108

96,675

80,351

37,280

38,903

4,953

3,575

2,372

Bishan

85,933

44,620

23,841

10,709

3,225

2,045

540

954

Bukit Batok

133,659

41,029

49,889

15,031

17,785

5,368

2,460

2,096

Bukit Merah

133,583

37,409

41,195

36,709

8,624

6,995

1,057

1,593

Bukit Panjang

121,427

33,440

51,221

14,239

17,673

2,758

1,039

1,056

62,191

43,439

11,549

4,798

304

366

312

1,422

1,930

750

342

150

514

148

27

-

Chua Chu Kang

165,926

46,003

67,434

17,764

24,533

5,768

2,278

2,146

Clementi

78,299

27,571

24,284

13,486

7,988

2,976

1,014

979

3,036

759

1,316

733

8

70

80

70

Geylang

104,955

27,447

37,123

20,707

13,969

3,404

996

1,309

Hougang

200,910

63,388

80,880

32,805

14,566

6,038

1,795

1,438

Jurong East

79,771

20,084

29,866

11,948

11,502

4,308

1,061

1,001

Jurong West

245,593

49,634

108,075

29,058

41,596

11,109

3,012

3,109

Kallang

83,528

23,414

29,154

17,767

5,895

4,712

1,654

932

Mandai

1,406

686

395

230

43

53

-

-

39,652

21,012

8,962

4,884

2,635

506

1,269

384

Newton

4,785

3,319

680

204

64

32

122

363

Novena

39,703

18,953

10,244

6,638

1,430

1,273

489

676

Outram

12,870

2,041

4,458

4,795

882

516

16

161

PasirRis

126,215

56,929

35,055

10,119

20,280

1,574

1,120

1,138

Punggol

53,707

19,430

21,235

5,963

4,825

874

1,017

364

Queenstown

82,291

30,842

23,272

16,181

6,629

3,217

931

1,221

River Valley

6,726

4,484

1,029

657

99

25

118

313

12,410

2,816

4,484

3,147

311

1,413

183

55

Planning Area

Total

Bukit Timah Changi

Downtown Core

Marine Parade

Rochor

31

Sembawang

66,351

19,107

28,062

7,278

7,607

2,165

627

1,504

Sengkang

153,704

46,112

65,613

19,906

13,992

4,270

2,730

1,081

Serangoon

114,847

52,649

35,374

16,016

4,828

3,827

1,116

1,036

Singapore River

1,060

776

103

57

68

-

-

56

Tampines

241,228

76,645

76,917

27,721

50,345

4,090

3,189

2,321

14,024

10,509

1,562

1,074

112

26

165

575

Toa Payoh

108,787

36,377

37,740

22,355

7,005

3,728

575

1,007

Woodlands

225,249

50,698

90,263

19,741

51,078

9,043

2,533

1,892

Yishun

167,395

40,711

67,705

23,982

24,748

6,893

1,997

1,358

Others

2,386

1,346

687

126

54

43

36

94

Tanglin

The number of three mosques was decided upon due to the time and resource constraints pertaining to this study. It was not viable for the researcher to travel to a large number of mosques, due to the variance in the programmes and visitors to the mosque each day which did not allow for a consistent response rate in each mosque. The time taken to conduct the data collection process in each mosque was also substantial, subject to the demographic profile of the individuals encountered and their agreement to participate in the study. Within each chosen mosque, purposive sampling was utilised to distribute the user-based questionnaires. While purposive sampling will yield a non-representative sample (Neuman, 2011), this study aimed to survey information-rich mosque-goers by focusing on individuals who met two specific criteria: (1) they are familiar with the mosque, and (2) they patron the mosque to meet or resolve a particular need or problem. Through this technique, a total of 210 responses made up the sample from the three mosques. This number is deemed to be adequate for three mosques, according to the rule of thumb method in deciding sample size (Neuman, 2011), by comparison with the recently concluded Mosque Perception Survey which was conducted across mosques in Singapore with a sample of 1000 (Straits Times, 2014). As of current, there are no relevant statistics on the number of mosque-goers in Singapore which the researcher could obtain that would give a more informed sampling number for this study. While the sampling technique used was a non-probability sampling method, the researcher took care to include all possible demographic/non-demographic categories of the population, by collecting responses from different age groups and sex, different educational and literacy levels, different digital literacy levels and different reasons for being in the mosque at that particular time. However, it was noted that the response rate was much higher for women than men, thus, there is a higher percentage of women represented in this study than men. This

32

phenomenon also reflects a number of studies which have found that in traditional survey modes, women tend to participate more than men (Kwak & Radler, 2002; Moore & Tarnai, 2002). However, this may also be a reflection of the composition of the study population, as according to MUIS (2011b), there has been an increase in the participation and contribution of Muslim women in mosque programmes and activities (see also The Straits Times, 2012). The gender representation in this study is thus deemed to be fairly adequate.

3.3.3. Survey Instrument & Measures According to Neuman (2011), structured surveys could be used to measure multiple variables at the same time, and from the data, relationships between the variables can be tested statistically. To explore and respond to the research questions and purpose of the study, a userbased questionnaire and a systems-based questionnaire were crafted. The user questionnaire was composed of three sections, the first section measuring variables related to the IUE of the mosque, and the second section measuring social capital variables in relation to the mosque. Demographic questions were included in the questionnaire as the last section (Appendix A). The systems questionnaire comprised three sections as well, the first measuring information availability and dissemination patterns in the mosque, the second measuring information exchange in the mosque, and the last comprising the background/demographic information of the mosque (Appendix B). Three independent variables and three dependent variables were examined through both the questionnaires. Eight constructs were derived from these six variables, measured using a total of 89 items from both questionnaires; 58 items from the user questionnaire and 31 items from the systems questionnaire. An overview of the variables, constructs, conceptual and operational definitions and respective measurement in the form of questionnaire items are tabulated in Appendix C. According to Neuman (2011), measuring aspects of social life is an ongoing process, and a great deal can be learnt from measures created by other researchers; thus past scales or indexes can be used or modified for different research studies and purposes (p. 220). The user questionnaire instrument was adapted from Lee (2009) and Lochner, McMillan, and Chavis (1986). The items from Lee (2009) constitute the uses and gratifications measurements related to the IUE. Measurements and items reviewed in Lochner, McMillan, &Chavis (1986) were drawn for the social capital component of the instrument. Both scales had been tested for reliability and validity from the various researchers involved in the development of the instruments. The question items were reconstructed to fit the context of the mosque and its participants. A percentage-based scale was used for both questionnaires, and treated as interval/ratio level of

33

measurement. The question items were also translated into Malay to cater to the largely majority Malay-Muslim population who frequent the mosque, a significant proportion being in a more matured age group who prefer to communicate in Malay. Items in the system questionnaire were also adapted from the instrument by Lee (2009), based on the uses and gratifications theory of the functional needs of community members/users. Context-specific questions were modified using the Mosque Convention 2011 report (MUIS, 2011a). The same percentage-based scale was used for the system questionnaire. Each system questionnaire for the three mosques was pegged to the responses for the mosque respectively. Both questionnaires were pilot-tested and amendments were made before they were distributed.

3.4. Study Constructs 3.4.1. Independent Variables The three independent variables are exclusively related to the Information Use Environment and are derived from Taylor’s (1991) work on Information Use Environments. The variables are “Information Characteristics”, “Information Retrieval” and “Information Use in Meeting Needs”. Information Characteristics comprise “Information Availability/Dissemination Patterns”. Information Retrieval comprised “Information Seeking/Acquisition Process”, and Information Use in Meeting Needs comprised “Information Utility for Needs Fulfilment”. Under the Information Characteristics construct, Information Availability/Dissemination Patterns are measured by 15 items (Cronbach’s α = 0.908). Under the Information Retrieval construct, Information Seeking/Acquisition Process is measured by 14 items (Cronbach’s α = 0.836). And under the Information Use in Meeting Needs construct, Information Utility for Needs Fulfilment is measured by 5 items (Cronbach’s α = 0.784).

3.4.2. Dependent Variables The three dependent variables measure social capital dimensions. While all three variables are measured based on social capital indicators, the third variable measures a social capital indicator

using

an

Information

Use

construct.

The

variables

are

“Social

Cohesiveness/Solidarity”, “Psychological Sense of Community” and “Information Use leading to Community Competence”. Social Cohesiveness/Solidarity comprised “Common Values”, and Psychological Sense of Community comprised two constructs, “Membership” and “Shared Emotional Connection”. Information Use leading to Community Competence comprised “Information Utility for Civic Engagement”.

34

Under the Social Cohesiveness/Solidarity construct, Common Values is measured by 8 items (Cronbach’s α = 0.947). Under the Psychological Sense of Community construct, Membership is measured by 8 items (Cronbach’s α = 0.860) and Shared Emotional Connection is measured by 7 items (Cronbach’s α = 0.858). And under the Information Use leading to Community Competence construct, Information Utility for Civic Engagement is measured by 8 items (Cronbach’s α = 0.897).

35

Chapter 4

Results and Analysis

4.1. Demographics A total of 203 completed surveys were analysed from the sample of 210 individuals who participated in the study. Seven surveys were not included in the analysis as either the completion rate of the survey was below 20%, or only the demographic section was completed. While 13 participants had not written their age in the survey form, all participants had confirmed verbally that they were within the age range of 21 to 60 years old (M = 36.84, SD = 15.22). Of the participants, 180 indicated they were Singaporeans, 11 were foreigners and 20 did not indicate their nationality. The characteristics of sex, race, age groups and education level are tabulated in Table 4.1. Table 4.1 Demographic Characteristics of Participants Characteristics Sample (%) Sex (n=194) Male 22.9 Female 68.6 Race (n=193) Malay/Indonesian Indian Chinese

72.4 17.1 1.0

Age (n=190) 21-35 years 36-45 years 46-60 years

51.9 6.7 31.9

Education Level (n=192) Primary school 12.4 Secondary school 33.8 Poly/ITE 21.0 Tertiary 24.3 Note: Differences in the number of respondents were due to non-response for the respective survey items

36

4.2. Information Practices and the IUE of the Mosque Community Research Question 1: What is the Information Use Environment (IUE) of the mosque? The following sections use a variety of descriptive analysis tools in order to understand the features of the IUE of the mosque. The findings report on the characteristics of the “Sets of People”, “Setting”, “Problems” and “Problem Resolution” pertaining to the mosque community.

4.2.1. Characteristics of the “Set of People” within the Mosque IUE Findings in this segment report on whether the IUE independent variables in the user questionnaire (Information Retrieval, Information Use to Meet Needs and Information Utility for Civic Engagement) are influenced by individual demographic (sex, age groups, education, and race) and non-demographic (language preferences, attitudes to new technology, types of information sources preferred, social networks) characteristics. The IUE independent variables in the user questionnaire are also interchangeably referred to in the results and analysis section as information practices.

4.2.1.1. Demographic Characteristics and Information Practices An independent t-test was run to compare mean differences in information seeking practice (Information Retrieval, Information Use to Meet Needs and Information Utility for Civic Engagement) across sex. Generally, the results show that there is no statistically significant differences in Information Use (for Meeting Needs and for Civic Engagement) across sex, t(91.32) = -0.536, p > 0.01 and t(103) = 1.59, p > 0.01 respectively. There is however a statistically significant difference in Information Retrieval between males (n = 48, M = 61.01, SD = 10.45) and females (n = 142, M = 53.23, SD = 19.75), t(188) = 2.620, p < 0.01. A one-way ANOVA was conducted to compare the effect of age groups (youth, middle-aged and matured) on information practices. There was a significant effect of age groups on Information Use for Civic Engagement at the p < 0.05 level [F(2, 183) = 3.72, p = 0.026]. Post hoc comparisons using the Tukey HSD test indicated that the mean score for the middle-aged group, which is between 36 to 45 years (M = 66.64, SD = 17.30), was significantly different than the matured age group, which is between 46 to 60 years (M = 51.10, SD = 22.80). However, the youth group, which is between 21 to 35 years (M = 57.20, SD = 19.70), did not significantly differ from the other two groups. These results suggest that there is a significant difference in the use of Information for Civic Engagement between the middle-aged group and the matured age group.

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One-way ANOVA was also conducted to compare the effects of education on information practices. However, ANOVA results indicate that education levels did not have a significant difference to information practices, showing that education levels do not affect information practices of the mosque community. ANOVA results did however show a significant effect of race on Information Retrieval at the p < 0.05 level [F(4, 186) = 2.94, p = 0.022]. Post hoc comparisons using the Tukey HSD test indicated that the mean score for the Malay race (M = 56.82, SD = 17.32) was significantly different than the Indian race (M = 46.84, SD = 18.80). However, respondents who indicated that they were from other racial groups, such as Chinese, (M = 65.00, SD = 28.28) did not significantly differ from the Malay and Indian groups. These results suggest that there is a significant difference in Information Retrieval for the Malay and Indian groups. This phenomenon partly be explained by information access, according to Taylor’s observation that “race may make a difference in restricting the options, and hence, changing the nature of required information” (Taylor, 1991, p. 223).

4.2.1.2. Non-demographic Characteristics and Information Practices In analysing the relationship between non-demographic characteristics and information practices, an independent sample t-test was conducted to compare mean differences of information practices (Information Retrieval, Information Use to Meet Needs, and Information Use for Civic Engagement) across languages preferred in seeking information. The results show a statistically significant difference in Information Retrieval between those who seek information in both Malay and English languages (n = 92, M = 59.63, SD = 14.83) and those who seek information only using the Malay language (n = 43, M = 50.80, SD = 18.77), t(133) = 2.954, p < 0.01. There are no statistically significant differences in Information Use (for Meeting Needs and for Civic Engagement) across languages preferred. The difference in the mean between the group seeking information in English and Malay and the group seeking information only in Malay can be explained through further analysis on the trends among 1) technological usage, 2) frequency of going to the mosque, and 3) age with languages preferred. A contingency table below (Table 4.2) outlines the trends of computer and Internet usage, frequency of mosque visits, and age groups of the two groups – bilingual (English and Malay) and unilingual (Malay) information seekers. Internet usage, while an originally continuous variable, was transformed into a categorical variable for this purpose. The categorization follows guidelines from iKeepSafe (2016), where “low” Internet usage is determined as 2 hours and below, “moderate” usage as 3 to 16 hours, and “high” usage as more than 16 hours.

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Table 4.2 Demographic and Non-Demographic Factors against Languages Preferred to Seek Information Languages Preferred Total Malay & English Malay Use computer at home (n=134) No 19.8% 38.1% 76.7% Yes 23.3% 61.9% 80.2% Frequency of mosque visit (n=133) Less than once a week At least once a week More than once a week

7.8% 47.8% 44.4%

9.5% 38.1% 52.4%

8.3% 44.7% 47.0%

Internet Usage (n=114) Low Moderate High

40.7% 54.3% 4.9%

93.9% 6.1% -

56.1% 40.4% 3.5%

Age Groups (n=131) Youth (21-35) Middle-Aged (36-45) Mature (46-60)

65.6% 10.0% 24.4%

9.8% 4.9% 85.4%

48.1% 8.4% 43.5%

Generally, the results show that the group which prefers unilingual mode of information seeking may engage in less interaction with technology than the bilingual information seekers. Specifically, cross-tabulation shows that the unilingual group consists largely of the matured age group, who mostly do not use a computer at home and engage in low Internet usage. They are also the group who tend to go to the mosque more frequently than the other two age groups. Thus, the results of the cross-tabulation analysis may point to another nondemographic characteristic which affect information practices in the mosque community: attitudes to new technology, as outlined by Taylor in his IUE paper (1991). This is also in view of the ANOVA results which had shown that education level does not result in significant differences in information practice, thus this difference in technological interactions cannot be attributed to education level. Also, according to the system questionnaire, Malay is the main language used to disseminate information across all three mosques (Table 4.3).

Table 4.3 System Questionnaire 3.5: What is the main/other language used when disseminating information? Languages Main Other1 Other2 Mosque ENN Malay English AND Malay English Tamil ANR Malay English Tamil

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Thus, the results indicate that the matured age group may have a less inclined attitude towards new technology than the other age groups, and making up the majority of the unilingual group, resulted in a significant difference in information practices between the bilingual and unilingual groups, even though the language used to disseminate information on both online and non-online platforms are primarily in Malay. Cross-tabulation on 1) technology-user interactions across sex as well as on 2) age group with sex was then conducted to affirm “attitudes to new technology” as a non-demographic characteristic of the mosque IUE. The contingency table which outlines the trends in technology usage across sex and age is shown in Table 4.4. Results show that male respondents are more inclined to use technology than female respondents. However, looking at the age demographics, the majority of male respondents fell in the youth category, while a significantly large population of female respondents fell into the matured age category, suggesting that while a large part of “attitudes to new technology” may be attributed to sex, the cross tabulation results as well as the earlier analysis on technological use across language preferred highlights the effect of age as well. In studying other non-demographic factors which may affect the IUE, information transfer across the different mediums (online social network, word-of-mouth, and mass media) was explored, and descriptive statistics was used to look at the mean, median, modes and standard deviations across the usage of the three mediums in relation to information seeking and retrieval, outlined in Table 4.5. The mean for getting updates through word-of-mouth is significantly higher than through the Internet or mass media, with the smallest standard deviation (M = 62.16, SD = 21.60), indicating that human sources seem to be the preferred choice of medium for the respondents. Cross-tabulations of age groups against these three items were then conducted to further explore the relationship between these variables. The contingency table is outlined in Table 4.6.

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Table 4.4 Demographic and Non-Demographic Factors against Sex Sex

Total

Male

Female

Use computer at home (n=192) No Yes

6.2% 93.8%

37.5% 62.5%

29.7% 70.3%

Frequency of mosque visit (n=190) Less than once a week At least once a week More than once a week

53.2% 46.8%

14.0% 47.6% 38.5%

10.5% 48.9% 40.5%

Internet Usage (n=114) Low Moderate High

7.7% 84.6% 7.7%

56.8% 41.6% 1.6%

45.1% 51.8% 3.0%

Age Groups (n=190) Youth (21-35) Middle-Aged (36-45) Mature (46-60)

81.2% 4.2% 14.6%

49.3% 8.5% 42.3%

57.4% 7.4% 35.3%

Table 4.5 Descriptive Statistics for Information Transfer/Retrieval Items N

Mean

SD

Median

Mode

1.4. I usually get updates from the mosque through the Internet

181

42.29

31.58

40

70

1.5. I usually get updates from the mosque via word-of-mouth

199

62.16

21.60

70

70

1.6. I usually get updates from the mosque through mass media

191

46.07

26.01

40

40

Item

Note: SD – Standard Deviation

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Table 4.6 Information Transfer/Retrieval Items against Age Groups Youth

Age Groups Middle-Aged

Mature

Total

Get updates through the Internet (n=190) Less frequently (< 70% of the time) Very frequently (>70% of the time)

46.8% 45.0%

28.6% 64.3%

53.7% 31.3%

47.9% 41.6%

Get updates through word-of-mouth (n=190) Less frequently (< 70% of the time) Very frequently (>70% of the time)

33.0% 67.0%

7.1% 85.7%

29.9% 67.2%

30.0% 68.4%

Get updates through mass media (n=190) Less frequently (< 70% of the time) Very frequently (>70% of the time)

72.5% 22.9%

14.3% 78.6%

43.3% 49.3%

57.9% 36.3%

The results show that across all age groups, getting updates through human sources is the most frequent compared to the Internet and mass media. Differences in usage of the Internet and mass media channels to seek/retrieve information can be seen in the mature and youth groups respectively, with a significantly lower proportion of the mature age group getting updates though the Internet (31.3%) and similarly for youth getting updates from mass media (22.9%).

These results indicate that human sources of information are yet another key non-demographic characteristic which influences the IUE of the mosque community. As social networks are also a key driver of social capital, a Pearson product-moment correlation analysis was conducted to assess the relationship between information dissemination channels and social capital constructs (i.e. Social Cohesiveness, Sense of Community and Community Competence). The results are tabulated in Table 4.7 below.

There was a positive correlation between most of the variables. However, getting updates through word-of-mouth had the highest number and strength of correlations to the three social capital constructs. It is also correlated the strongest with Social Cohesiveness, r = 0.541, p < 0.01. The results affirm that increased social network activity is correlated with increased social capital, and suggest that information transfer through human sources i.e. word-of-mouth is more effective than online social networks in enhancing social capital.

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Table 4.7 Correlations among Information Dissemination Channels Items and Social Capital Constructs 4. Social Cohesiveness

5. Sense of Community

6 Community Competence

1. I usually get updates from the mosque through the Internet

.328**

.080

.463**

2. I usually get updates from the mosque via word-of-mouth

.541**

.183**

.334**

3. I usually get updates from the mosque through the mass media

.298**

.157*

.274**

**p < 0.01; *p < 0.05.

4.3. The Interaction between “Setting” and “Sets of People”: Social Networks as a Medium of Information Transfer within the Mosque IUE This section explores information transfer within the mosque community in order to gain an insight into the interaction between “Setting” and “Sets of People” within the IUE of the mosque. Information transfer in this context pertains to information seeking practices as well as system-user interactions. The analysis is focused on the angle of social networks, identified by Taylor (1991) as one of the key non-demographic characteristics influencing the IUE. Social networks are also a key consideration of this present study in exploring elements of the IUE which affects social capital. Items from both user and system questionnaire pertaining to social networks, such as on online social networks and human sources, are extracted and analysed using Pearson product-moment correlation analysis in order to examine the associations between system and user. Results from the Pearson product-moment correlation is shown in Table 4.8. The system questionnaire items are indicated in the correlation table as SYS. These systemlevel items indicate the extent to which information aimed at connecting with the community is available, the extent to which information aimed at connecting with the community is disseminated through print and electronic sources, as well as the extent to which the mosque uses physical platforms (e.g. gatherings, face-to-face chats, etc.) to communicate to the community.

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The results indicate that increased availability of information aimed at connecting with the community (Item 1) is not correlated with an increase in the use or sharing of information, based on the non-significant correlations across user-level social network items 7 to 9. This suggests non-use of this type of information, and could be possibly due to the information traits such as irrelevance, timeliness or quality that affected selection criteria in using this particular type of information. The results also indicate that certain patterns of dissemination may have some effect on social network activity, as dissemination of information aimed at connecting with the community through print and online sources (Item 2) has a correlation with users getting updates through the Internet (r = 0.160, p < 0.05) and users sharing the information with others (r = 0.180, p < 0.05). While the strength of the Pearson correlation may be weak, the results highlight these two items on ‘getting updates through the Internet’ and ‘sharing information with others’ as having the only significant correlations to Item 2, thus making the relationship noteworthy. Among all the user-level items measuring information transfer via social networks, only the item on ‘sharing information received with family and friends’ (Item 9) has a correlation with the system-level item on ‘using physical platforms to communicate to the community’ (Item 3), with a moderately strong correlation of r = 0.210, p < 0.01. This indicates that an increase in communication using physical platforms such as events, talks, gatherings on the mosque level is correlated with an increase in members sharing the information with people in their social network. Generally, the user-level items on information seeking (Items 4, 5, & 6) and information use (Items 7, 8 & 9) pertaining to social networks are significantly correlated to each other, indicating that social network is a strong non-demographic characteristic of the mosque community in influencing information transfer and use within the IUE framework. The only items which do not have a significant relationship with each other are the information seeking item on ‘getting updates via word-of-mouth’ (Item 5) and the information use item on ‘utilizing information received to participate in mosque social media platforms’ (Item 8). This indicates that an increase in getting updates via word-of-mouth is not correlated to an increase in mosque social media platform participation. This suggests that information received through human sources may not necessarily translate to participation in mosque social media platforms. It also suggests that there may be less of an interaction between the online social networks and human sources in the transfer of information within the whole IUE framework.

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Table 4.8 Correlations among Social Network items 4.

5.

6.

7.

8.

9.

1. Availability of information aimed at connecting with the community (SYS)

.13

.07

.04

-.14

-.01

.08

2. Dissemination of information aimed at connecting with the community (Print and Electronic) (SYS)

.16*

.04

.03

-.08

.01

.18*

3. The mosque uses physical platforms to communicate to the community (SYS)

.13

-.03

.01

.08

.04

.21**

4. I usually get updates from the mosque through the Internet

---

.22**

.23**

.21**

.51**

.36**

5. I usually get updates from the mosque via word-of-mouth

.22**

---

.32**

.35**

.11

.46**

6. I seek information from the mosque community to meet and interact with people who have the same interests as me

.30**

.32**

---

.47**

.53**

.32**

7. The information I receive enables me to interact with people in the mosque community

.21**

.35**

.43**

---

.37**

.54**

8. The information I receive enables me to participate in the mosque social media platforms

.51**

.11

.53**

.37**

---

.44**

9. I will share the information I receive from the mosque with my family and friends

.36**

.46**

.32**

.54**

.44**

---

**p < 0.01; *p < 0.05. Column headings start from Item 4. for easier reference

4.3.1. “Problems” and “Problem Resolution”: Information Use of the Mosque Community Members within the IUE Framework To gain an insight into the “problems” and “problem resolution” of the mosque community members within the IUE perspective, descriptive statistics were utilized to observe the trends pertaining to information use of respondents in the mosque community to meet their needs.

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The scores for mean, median, mode and standard deviation were tabulated for two variables measuring information use: Information Use to Meet Needs and Information Use for Civic Engagement. Table 4.9 shows the results for the Information Use to Meet Needs variable items. Results showed that information was primarily sought to increase knowledge and understanding, followed by the use of information to enhance faith or spirituality. Using information to meet and interact with people also scored a high mean. With regards to the Information Use for Civic Engagement variable, descriptive statistics show a much lower mean across all items as compared to Information Use to Meet Needs. The results for Information Use for Civic Engagement are tabulated in Table 4.10 below. The highest score is for sharing information received with family and friends, followed by information which enables interaction with community members, and information which enables knowledge contribution to the community. Based on the trends for information use in meeting needs and information use for civic engagement, particularly the item with the highest mean, sharing of information with others (n = 191, M = 66.80, SD = 23.10), it suggests that information use is generally more passive than active, and where active, involves other members within individuals’ strong social network ties (individual social circles) rather than those in the weak social network ties (wider community).

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Table 4.9 Descriptive Statistics for Information Use to Meet Needs Items Item N Mean SD 8a. I seek information 190 72.52 19.41 from the mosque community to enhance my level of spirituality

Median 70.00

Mode 70.00a

8b. I seek information from the mosque community to increase knowledge and understanding

189

73.23

20.85

70.00

90.00

8c. I seek information from the mosque community to get help, support and guidance

176

47.39

31.19

40.00

70.00

8d. I seek information from the mosque community to engage in services offered by the mosque

183

56.83

29.68

70.00

70.00

8e. I seek information from the mosque community to meet and interact with people who have the same interests as me.

189

60.63

27.83

70.00

70.00

Note: SD – Standard Deviation; a - Multiple modes exist. The smallest value is shown.

Table 4.10 Descriptive Statistics for Information Use for Civic Engagement Items Item

N

Mean

SD

Median

Mode

9a. The information I receive enables me to interact with people in the mosque community

189

61.69

25.25

70.00

70.00

9b. The information I receive enables me to contribute my knowledge for the benefit of the community

180

61.61

27.22

70.00

70.00

9c. The information I receive enables me to participate in mosque social media platforms

172

48.95

29.22

70.00

70.00

(Table 4.10 continues)

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(Table 4.10 continues) Item

N

Mean

SD

Median

Mode

9d. The information I receive enables me to plan and/or participate in activities related to the mosque

175

50.69

29.22

40.00

70.00

9e. The information I receive enables me to organize or propose activities for the community

173

41.16

30.72

40.00

40.00a

9f. The information I receive enables me to provide suggestions/feedback to the mosque.

185

50.27

27.37

40.00

40.00

9g. The information I receive enables me to organize or propose activities for the community

189

55.93

27.81

70.00

70.00

9h. I will share the information I receive from the mosque with my family and friends

191

66.75

23.08

70.00

70.00

Note: SD – Standard Deviation, a. - Multiple modes exist. The smallest value is shown

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4.4. Interactions between IUE and Social Capital Research Question 1: How do institutional aspects influence the use of information to build social capital in the mosque community? Research Question 2: How do technology/systemic-user interactions influence the formation of social capital in the mosque community? Research Question 3: What are the different uses of information that build social capital in the mosque community? The following sections uses bivariate linear regression and stepwise multivariate regression analysis tools in order to explore the interaction of different features of the mosque IUE in generating social capital, as well as the whole IUE framework in generating social capital. The bivariate linear regression findings (Tables 4.11 to 4.22) report on the interaction of the individual IUE variables on three elements of social capital (Social Cohesiveness, Sense of Community and Information Use for Civic Engagement). Under Sense of Community, Membership and Shared Emotional Connection are two elements which are analysed separately in the regression models. Findings from the stepwise multiple regression analysis (Tables 4.23 to 4.38) were used to report on the interaction of the IUE factors and individual items on three elements of social capital, with the inclusion of interaction variables pertaining to system-user interactions and demographic-user interactions. Taken in sum, the regression analysis thus sheds light on the three research questions above to answer the overall research question, “How do institutional factors and individual information needs and uses within an Information Use Environment influence social capital within the socio-religious community of the Singapore mosque?” The preliminary analyses (Sections 4.2. – 4.3.) on research question one sets the context for the regression analysis and provides a greater depth of understanding of the various interactions and uses of information within the IUE framework that builds social capital. From the results and analysis of the data, a model of the relationship between IUE elements and social capital of the mosque is then drawn for a more visual illustration (Fig. 4.1).

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4.4.1. Descriptive Statistics for IUE and Social Capital Variables Examined The dependent variables in this study make up the social capital constructs of Social Cohesiveness (M = 60.70, SD = 15.15), Sense of Community comprising Membership (M = 52.84, SD = 19.04) and Shared Emotional Connection (M = 58.46, SD = 19.00), and the IUE construct Information Use for Civic Engagement (M = 55.04, SD = 21.42). Information Use for Civic Engagement, while generally taken as a construct under the social capital dependant variable, also acts as an IUE independent variable in examining the relationship and interactions between the IUE of the mosque community and social capital. This is due to the nature of the construct; while inherently part of the IUE framework, it also comprises a measure of social capital. Thus, it is included in the analysis as part of the IUE constructs when examining the other social capital variables, and at the same time it is also examined as a social capital construct in relation to other IUE variables. The other IUE variables are Information Retrieval (User) component (M = 58.75, SD = 18.40) and Information Use in Meeting Needs (M = 62.64, SD = 19.49). System-level variables are primarily used as interaction variables to study the effect of the setting in the IUE framework in the interactions between the IUE of the mosque community and social capital. For the purpose of reporting results with more clarity, in this section, the variable Information Use for Civic Engagement is seen as a separate variable from the other two IUE constructs, Information Use to Meet Needs and Information Retrieval, as it is analysed as both an IUE and social capital variable in different situations. For more concise reporting, the term “general information practices” is used interchangeably to describe the two variables, Information Use to Meet Needs and Information Retrieval, as a whole. In general, all measures scored moderately high for both IUE and social capital constructs. Respondents rated Social Cohesiveness the highest among the social capital constructs, and Information Use to Meet Needs scored the highest among IUE constructs. This indicates that common values, which is defined by the Social Cohesiveness variable, is strong in the mosque community, and there is a high use of information to meet needs (M = 62.64), even as the information retrieval experience may not be as optimal (M = 54.87). The results also show that Information Use for Civic Engagement scored moderately high as both an IUE and social capital construct. Table 4.11 depicts the descriptive statistics of the study variables.

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Table 4.11 Descriptive Statistics for Study Variable Items- Social Cohesiveness, Membership, Shared Emotional Connection and Information Use for Civic Engagement as Social Capital constructs, and Information Use for Civic Engagement, Information Retrieval (User) and Information Use to Meet Needs as IUE constructs Item

N

Mean

SD

Median

Mode

Social Cohesiveness

202

60.67

15.15

62.50

78.75

Membership

200

52.84

19.04

55.00

65.00

Shared Emotional Connection

200

58.46

18.98

61.43

80.00

Info Use for Civic Engagement

198

55.04

21.42

56.70

78.75

Information Retrieval (User)

201

54.87

18.39

58.75

58.75

Information Use to Meet Needs

197

62.64

19.49

64.00

90.00

Note: SD – Standard Deviation; a - Multiple modes exist. The smallest value is shown.

4.4.2. Linear Regression Analysis 4.4.2.1. Effect of Information Use for Civic Engagement on Social Capital Research Question 4: What are the different uses of information that build social capital in the mosque community? Information Use for Civic Engagement is regarded in this study as an IUE variable in terms of information use within the IUE context, as well as a social capital variable in terms of the purpose of use which is for civic engagement. Thus, as an IUE variable, in order to ascertain its influence on social capital, bivariate linear regression was conducted to examine the relationships between Information Use for Civic Engagement and the other non-IUE related social capital constructs, namely Social Cohesion, Membership and Shared Emotional Connection. The results are outlined in Tables 4.12 – 4.14. All three linear regressions yielded statistically significant results, where overall, 36% of the variance of Social Cohesiveness, 46.7% of the variance in Membership, and 35% of the variance of Shared Emotional Connection could be explained by Information Use for Civic Engagement. The effect of Information Use for Civic Engagement on the three other social capital constructs suggests that Information Use for Civic Engagement as an IUE construct has a moderately strong influence on social capital.

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Table 4.12 Bivariate Linear Regression –Information Use for Civic Engagement (IUE9) – Social Cohesiveness Effect B β t Sig. (Constant) 38.12 16.09 .00* Information Use for Civic .42 .76 10.36 .00* Engagement Dependant Variable: Social Cohesiveness R=.60, R2=.36, F(1, 195)= 107.31*, *p < 0 .05

Table 4.13 Bivariate Linear Regression –Information Use for Civic Engagement (IUE9) – Membership Effect B β t Sig. (Constant) 19.12 6.94 .00* Information Use for Civic .61 .68 13.05 .00* Engagement Dependant Variable: Membership R=.68, R2=.47, F(1, 194)= 170.25*, *p < 0.05

Table 4.14 Bivariate Linear Regression –Information Use for Civic Engagement (IUE9) –Shared Emotional Connection Effect B β t Sig. (Constant) 29.40 9.64 .00* Information Use for Civic .53 .59 10.19 .00* Engagement Dependant Variable: Shared Emotional Connection R=.59, R2= .35, F(1, 193) = 103.77*, *p < .05

4.4.2.2. Effect of Information Practices on Social Capital Research Question 2: How do institutional aspects influence the use of information to build social capital in the mosque community? Research Question 4: What are the different uses of information that build social capital in the mosque community? In examining the effect of general information practices within the mosque IUE on social capital, another series of bivariate linear regressions were conducted to establish the predictive power of the other two IUE constructs, Information Retrieval (user) and Information Use to Meet Needs, on social capital. The results are tabulated in Tables 4.15 – 4.22 below. Results showed that both IUE constructs statistically predicted all constructs of social capital. Information Use in Meeting Needs explained the highest variance in Information Use for Civic Engagement (β = .73, p < 0.05) at 53% (Table 4.22) as compared to information retrieval (β =

52

.53, p < 0.05) at 28% (Table 4.21). This large difference between the variances of the two IUE constructs is only observed in the linear regression to predict Information Use for Civic Engagement. This suggests that both Information Use to Meet Needs and Information Retrieval (User) affect Social Cohesiveness and Sense of Community (comprising Membership and Shared Emotional Connection constructs) similarly; however, Information Use to Meet Needs affect Information Use in Civic Engagement more strongly than Information Retrieval (User) does. This indicates that a higher extent of use of community information in the mosque significantly influences higher civic participation or community competence, as inferred by Information Use for Civic Engagement as a social capital construct. Table 4.15 Bivariate Linear Regression: Information Retrieval (User) & Social Cohesiveness Effect B t β (Constant) 33.25 12.31 Information Retrieval .50 .61 10.69 (User) Dependant Variable: Social Cohesiveness R=.61 , R2=.37, F(1, 198)= 114.26*, *p < .0.5

Sig. .00* .00*

Table 4.16 Bivariate Linear Regression: Information Use in Meeting Needs & Social Cohesiveness Effect B β t Sig. (Constant) 31.89 10.66 .00* Information Use in .50 .59 10.04 .00* Meeting Needs Dependant Variable: Social Cohesiveness R=.59 , R2=.34,F(1, 194)= 100.82*, *p < .0.5

Table 4.17 Bivariate linear regression: Information Retrieval (User) & Membership Effect B β t (Constant) 19.40 5.40 Information Retrieval .60 .57 9.75 (User) Dependant Variable: Membership R=.57 , R2=.33, F(1, 196)= 95.01*, *p < .05

Sig. .00* .00*

Table 4.18 Bivariate Linear Regression: Information Use for Meeting Needs & Membership Effect B β t (Constant) 13.94 3.88 Information Use in .62 .63 11.28 Meeting Needs Dependant Variable: Membership R=.63 , R2=.40, F(1, 192)= 127.32*, *p < .05

Sig. .00* .00*

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Table 4.19 Bivariate Linear Regression: Information Retrieval (User) & Shared Emotional Connection Effect B β t Sig. (Constant) 24.14 6.94 .00* Information Retrieval .62 .60 10.36 .00* (User) Dependant Variable: Shared Emotional Connection R=.60 , R2=.35, F(1, 196) = 107.35*, *p < .05

Table 4.20 Bivariate Linear Regression: Information Use for Meeting Needs & Shared Emotional Connection Effect B β t Sig. (Constant) 24.10 6.30 .00* Information Use for .55 .56 9.35 .00* Meeting Needs Dependant Variable: Shared Emotional Connection R=.56, R2=.31, F(1, 192)= 87.40*, *p < .05

Table 4.21 Bivariate Linear Regression: Information Retrieval & Information Use for Civic Engagement (IUE9) Effect B β t Sig. (Constant) 20.35 4.89 .00* Information Retrieval .63 .53 8.74 .00* Dependant Variable: Information Use for Civic Engagement (IUE9) R=.53 , R2=.28, F(1, 195) = 76.42*, *p < .05

Table 4.22 Bivariate Linear Regression: Information Use for Meeting Needs & Information Use for Civic Engagement (IUE9) Effect B β t Sig. (Constant) 3.71 1.03 .31 Information Use for .81 .73 14.82 .00* Meeting Needs Dependant Variable: Information Use for Civic Engagement (IUE9) R=.73, R2=.53, F(1, 193) = 219.65*, *p < .05

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4.4.3. Stepwise Regression Analysis 4.4.3.1. Significant Predictors of Social Capital and the Influence of Interaction Variables Research Question 2: How do institutional aspects influence the use of information to build social capital in the mosque community? Research Question 3: How do technology/systemic-user interactions influence the formation of social capital in the mosque community? Research Question 4: What are the different uses of information that build social capital in the mosque community? To identify significant IUE factors which predicts social capital, a series of stepwise multiple regressions were conducted. An initial set of models were created predicting the four social capital constructs: Social Cohesiveness, Membership, Shared Emotional Connection and Information Use in Civic Engagement (Section 4.4.3.2.). The IUE predictor variables comprised Information Retrieval (User) and both Information Use (Meeting Needs and Civic Engagement) variables, where applicable, and results were used to explore how different IUE factors influenced social capital. Secondly, as the IUE framework highlights “setting” as one of the important factors affecting the IUE of a group of people, systemic elements are included in the regression analysis as interaction effects with the main IUE predictor variables in another series of regression models (Section 4.4.3.3.). These systemic elements comprise of items pertaining to availability of information, patterns of dissemination, as well as the information retrieval system of the mosque (See Appendix C). This second set of models were then compared with the initial set of models to determine any differences in the F-value between both models in accounting for the variance predicting a particular social capital construct. Subsequently, significant models were examined for the interaction effects to provide a more in-depth understanding of the contextual factors of the IUE which may affect social capital.

4.4.3.2. Initial Regression Models (Without Systemic Elements) Results of the initial regression models are tabulated below, from Tables 4.23 to 4.28. In general, Information Retrieval is a notable predictor of social capital as it is present across all four models of Social Capital constructs. Information Use for Civic Engagement is also a notable predictor of social capital, as it is present in all the models as well, except where it is examined as a Social Capital variable. In terms of effect size, Information Use for Civic

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Engagement has an overall larger size (0.28 ≤ β ≤ 0.42. p < 0.05) as compared to Information Retrieval (0.15 ≤ β ≤ 0.40. p < 0.05), suggesting that it has a larger effect on social capital. Specifically, all three IUE variables are able to explain 47% of variance in Social Cohesiveness (Table 4.23), and 54% of variance in Membership (Table 4.24). Information Use for Civic Engagement and Information Retrieval are able to explain 46% of variance in Shared Emotional Connection (Table 4.25), and Information Use in Meeting Needs and Information Retrieval are able to explain 55% of variance in Information Use for Civic Engagement (Table 4.26). These results suggest at largely interwoven networks of IUE factors which results in an effect on social capital.

Table 4.23 Multiple Regression of Information Practices - Social Cohesiveness Effect B β (Constant) 26.02 Information Use in Meeting .16 .20 Needs Information Retrieval (User) .27 .32 Information Use for Civic .19 .28 Engagement Dependant Variable: Social Cohesiveness Excluded Variables: Information Use for Civic Engagement R=.69, R2=.47, F(3, 190) = 56.89*, *p