تحلیل شبکه اجتماعی در تحقیقات سیستم های اطلاعاتی حسابداری
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی|
|10173||2013||11 صفحه PDF||18 صفحه WORD|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Accounting Information Systems, Volume 14, Issue 2, June 2013, Pages 127–137
2.نمونه تحلیل شبکه اجتماعی
شکل 1. شبکه هیات علمی دانشکده بازرگانی
3.تحلیل شبکه اجتماعی در تحقیقات
3.1.تحقیق درمورد شرکت های شبکه AIS
3.2.تحقیقاتی که سیستم های اطلاعاتی حسابداری در آن گره ها هستند
3.3.تحقیق درمورد اتصالات/روابط بین عوامل انسانی
4.تحلیل شبکه اجتماعی برای پیش بینی، کشف و جلوگیری از کلاه برداری
شکل 2. فرامین اجتماعی و کلاه برداری همان طور که توسط نظریه بی سازمانی اجتماعی توضیح داده می شود.
شکل 3. فرامین اجتماعی و ساختارهای فعالیت جنایی
5.1.کنترل و قابلیت حسابرسی سیستم های اطلاعاتی
5.2.انتشار الکترونیکی اطلاعات حسابداری
5.3.دیدگاه های سازمانی/اجتماعی درمورد تاثیر فناوری بر حسابداری
This paper introduces social network analysis as an alternative research method for conducting accounting information systems related research. With advances in information and communication technologies, transaction data are being recorded in electronic form, resulting in a variety of research opportunities to examine dyadic interactions. A network consists of a set of nodes connected by ties. Social network research focuses on how outcomes are influenced not just by the attributes of the nodes (e.g. individuals), but also by the ties connecting nodes to each other. The nodes are typically conceptualized as actors, such as individuals, teams, or organizations. A unique network structure is created to reflect each different type of tie, such as trust, advice, collocation, or organizational affiliation. Social network analysis can be used for research examining individual, dyadic or network levels of analyses, and is a powerful tool for conducting multi-method research. Given the vast amounts of trace electronic data collected via accounting information systems, this paper reviews how social network analysis not only opens new research avenues for accounting information systems researchers, but identifies opportunities for the field of accounting information systems to inform social network research by identifying new network structures and dynamics leveraging transactional data.► The purpose of this paper is to encourage the use of social network analysis by accounting researchers. ► To facilitate the understanding of social network analysis, we provide an overview of social network theories. ► We examine selected accounting journals to identify the frequency of use of social network analysis. ► We provide suggested areas of research that could benefit from taking a social networks approach.
There has been a general shift in management research over the past decade towards more relational theories of organizations that view actions and actors not as independent, autonomous agents, but as embedded within socio-technical systems. In contrast to theories that examine individuals based on their attributes, such as gender, age, education, or occupation, social network perspectives focus on how the relationships between entities, such as individuals, functional units, or organizations, influence interactions and outcomes. The concept of a “network” is broad and can be applied to a variety of phenomena where a set of relations is ascribed to an identified set of actors. What unites social network perspectives is the focus on the patterns and implications of the ties within a collective (Scott, 1991 and Wasserman and Faust, 1994). For example, at the individual level ties facilitate the spread of information among network participants, enable the flow of both tangible and intangible resources among network members, and place constraints on each member's behavior (Burt, 1992). Social network research focuses on the significance of relationships as essential for understanding social action, but varies widely in the attributes that are studied. A network is defined as a set of nodes connected by ties. Nodes are typically “actors”, and can be people, teams, organizations or information systems. Relations, or ties, connect the actors and can vary in content, direction, and relational strength, all of which influence the dynamics of the network (Garton et al., 1999). The content of ties refers to the resource exchanged or common bond, such as information, money, advice, or kinship. The direction of ties indicates an “ego” who gives the resource, and the “alter” who receives it, although ties in some networks are undirected, such as a shared attribute (e.g. gender), or joint membership on a team. The relational strength of ties pertains to the level of activity, such as quantity of communications, or the intensity, such as the social influence exerted by the tie, indicating that ties can be valued or weighted. For instance, the relational strength of ties could indicate the amount of energy, emotional intensity, intimacy, commitment or trust connecting the actors. Relational ties are often studied in management research as important aspects of social influence that can exert control, such as social punishments or ostracism (Ostrom, 1990). Other aspects of social influence foster cohesion and prosocial behavior in the network, such as trust, identification, the diffusion of information and commitment (Coleman, 1990 and Nahapiet and Ghoshal, 1998). Each tie defines a different network, and while some ties are often related (a trust network is often correlated to a friendship network), ties are often assumed to function differently. Not all ties are considered to have positive outcomes; for instance, network research is often used to map the flow of disease or terrorist networks. Therefore, some network research focuses on how to improve the flow of the resource through the network, such as adoption of a new accounting information system, or how to disrupt the flow of resources in the network, such as taking out key nodes in a fraud network. Depending upon the theory being applied, some studies examine network variables as independent variables causing consequences, such as adoption of a technology or improved performance, while other studies examine network variables as dependent variables, identifying the causes underlying the pattern of network connections, how networks come to be, and how networks change over time (Borgatti and Foster, 2003).
نتیجه گیری انگلیسی
In Section 3, we provided an overview of current accounting research utilizing social network analysis. From this examination, three distinct literature streams emerged: transactions and control mechanisms in the context of inter-organizational dynamics, networks where accounting systems are viewed as nodes, and connections between human actors in an accounting context. From these streams, we presented a series of research questions which could serve to expand our knowledge in these areas and which social network analysis is uniquely positioned to inform in the near-term. In Section 4 we discussed one of these examples in depth, to provide deeper insights into how social network analysis could be applied in the context of fraud detection and investigation. While social network analysis offers opportunities to expand and contribute to the research streams mentioned above, we would be remiss if we didn't expand our discussion of how social network analysis can be leveraged to inform other areas of interest to AIS researchers. To this end, we looked to the topics typically addressed in the International Journal of Accounting Information Systems for areas where social network analysis might provide distinct benefits over other methods and foster a better understanding of these. Although there are numerous topics where we feel this method might prove fruitful, we focused on three that we feel have the most promise. 5.1. Control and auditability of information systems Since the Sarbanes Oxley Act of 2002, accounting researchers have focused anew on investigating issues around control and accountability of information systems. Of particular interest has been evaluating the nature and effectiveness of the control environment (Bowen et al., 2007, Klamm and Watson, 2009 and Bart and Turel, 2010). The control environment represents the foundation for an organization's system of internal controls and includes management's ethical values and integrity, organizational structure, and authority and reporting arrangements (COSO, 1992). Social network analysis could prove useful for research aimed at better understanding the nature and effectiveness of the control environment as well as the overall system of internal controls. For example, it could be used • as a method for examining communication and coordination between key stakeholders important to the identification and control of risk (such as auditors, members of the audit committee, risk owners, and management), • as a method for examining the effectiveness of coordination mechanisms inscribed in organizational structures as well as informal coordination mechanisms, and • as a method for examining the effectiveness of traditional controls (such as segregation of duties, approvals, and restricting access) compared to social controls embedded in the fabric of relationships. 5.2. Electronic dissemination of accounting information Information from accounting and transaction processing systems is a necessary component of planning, budgeting and management control. For this information to be useful, it must be accessible to decision makers in a proper format and timely fashion. However, it is often difficult to identify which actors require specific information, especially in globally dispersed organizations or networked enterprises with diverse stakeholder groups. As we have previously discussed, actors can be individuals, work units, organizations, regulatory bodies or even other information systems. Social network analysis provides a useful methodological approach to examine the interconnections between diverse actors and how these linkages can inform questions around which actors need accounting information and in what format. For example, it could be used • as a method to examine flows of information between linkages in inter-organizational systems connecting networked enterprises, • to identify whether key information is kept confidential or is transferred beyond organizational boundaries, and • as a method to identify key sources of accounting information as well as consumers of this information. 5.3. Organizational/social perspectives on impact of technology on accounting Prior research has demonstrated that informal networks augment or supersede formal hierarchies with respect to knowledge sharing. An extension of research aimed at understanding the dissemination of accounting information would be to more fully explore where and to whom people look for advice and expertise. While Murthy and Taylor's (2009) work on examining knowledge sharing practices on the Accounting Education using Computers and Multimedia (AECM) email list takes a first step, further investigation into networks aimed at connecting expertise, such as the American Accounting Association's AAA Commons initiative, might serve to bridge the gap between formal networks and informal networks. Social network analysis provides a new approach to more fully explore how accounting and business process knowledge is dispersed across organizational or professional boundaries, as well as understand the manner in which it is accessed. For example, it could be used • as a method to identify the location of expertise within and outside traditional hierarchies and organizational structures, • as a method to identify informal expertise networks and provide insight on how people perform their work, • as a method to aid in the design of systems aimed at connecting people with expertise (such as AAA Commons), and • as a method to explain attributes of individuals and groups critical to internal control, dissemination and creation of accounting-related information, and policy and standards. To conclude, the purpose of this article was to present social network analysis as an alternative method that has high potential for expanding AIS research. Social network analysis focuses on the pattern of ties connecting nodes within a network, and emphasizes that both the pattern of relationships and characteristics of the dyads influence the actions of network members. While most prior research using social network analysis has focused on network dynamics in face to face networks, advances in information and communication technologies, especially accounting information systems, open new possibilities for the types of network structures and research questions that can be investigated.