After ANT:an illustrative discussion of the implications for qualitative accounting case research

The main aim of this article is to shed some light on the way in which actor network theory (ANT) might contribute to case research in accounting. The paper will seek to explain some of the theoretical suppositions which are commonly associated with ANT and which have so far made little impact on the accounting literature. At the same time the accounting literature has shown a particular reluctance to engage with the central concept of ANT which Lee and Hassard characterise as the desire to bring together the "human and non-human, social and technical factors in the same analytical view". The article also features a discussion of a research project which used an approach giving emphasis to both humans and objects in order to understand how ``facts'' have come to be settled as they are. In taking such views into the research it is hoped to provide insight into both the detail of accounting as it is practised within organisations and the manner in which human actors and objects of technology may combine to constitute networks within organisations.

A biography:fabrications in the life of an ERP package

This paper provides an account of the way Enterprise Resource Planning (ERP) systems change over time. These changes are conceptualized as a biographical accumulation that gives the specific ERP technology its present character, attributes and historicity. The paper presents empirics from the implementation of an ERP package within an Australasian organization. Changes to the ERP take place as a result of imperatives which arise during the implementation. Our research and evidence then extends to a different time and place where the new release of the ERP software was being 'sold' to client firms in the UK. We theorize our research through a lens based on ideas from actor network theory (ANT) and the concept of biography. The paper seeks to contribute an additional theorization for ANT studies that places the focus on the technological object and frees it from the ties of the implementation setting. The research illustrates the opportunistic and contested fabrication of a technological object and emphasizes the stability as well as the fluidity of its technologic. Copyright © 2007 SAGE.

Interactive data in financial reporting:the construction of the non-professional investor

The Securities and Exchange Commission (SEC) in the United States and in particular its immediately past chairman, Christopher Cox, has been actively promoting an upgrade of the EDGAR system of disseminating filings. The new generation of information provision has been dubbed by Chairman Cox, "Interactive Data" (SEC, 2006). In October this year the Office of Interactive Disclosure was created(http://www.sec.gov/news/press/2007/2007-213.htm). The focus of this paper is to examine the way in which the non-professional investor has been constructed by various actors. We examine the manner in which Interactive Data has been sold as the panacea for financial market 'irregularities' by the SEC and others. The academic literature shows almost no evidence of researching non-professional investors in any real sense (Young, 2006). Both this literature and the behaviour of representatives of institutions such as the SEC and FSA appears to find it convenient to construct this class of investor in a particular form and to speak for them. We theorise the activities of the SEC and its chairman in particular over a period of about three years, both following and prior to the 'credit crunch'. Our approach is to examine a selection of the policy documents released by the SEC and other interested parties and the statements made by some of the policy makers and regulators central to the programme to advance the socio-technical project that is constituted by Interactive Data. We adopt insights from ANT and more particularly the sociology of translation (Callon, 1986; Latour, 1987, 2005; Law, 1996, 2002; Law & Singleton, 2005) to show how individuals and regulators have acted as spokespersons for this malleable class of investor. We theorise the processes of accountability to investors and others and in so doing reveal the regulatory bodies taking the regulated for granted. The possible implications of technological developments in digital reporting have been identified also by the CEO's of the six biggest audit firms in a discussion document on the role of accounting information and audit in the future of global capital markets (DiPiazza et al., 2006). The potential for digital reporting enabled through XBRL to "revolutionize the entire company reporting model" (p.16) is discussed and they conclude that the new model "should be driven by the wants of investors and other users of company information,..." (p.17; emphasis in the original). Here rather than examine the somewhat illusive and vexing question of whether adding interactive functionality to 'traditional' reports can achieve the benefits claimed for nonprofessional investors we wish to consider the rhetorical and discursive moves in which the SEC and others have engaged to present such developments as providing clearer reporting and accountability standards and serving the interests of this constructed and largely unknown group - the non-professional investor.

The multiple pheromone ant clustering algorithm and its application to real world domains

The Multiple Pheromone Ant Clustering Algorithm (MPACA) models the collective behaviour of ants to find clusters in data and to assign objects to the most appropriate class. It is an ant colony optimisation approach that uses pheromones to mark paths linking objects that are similar and potentially members of the same cluster or class. Its novelty is in the way it uses separate pheromones for each descriptive attribute of the object rather than a single pheromone representing the whole object. Ants that encounter other ants frequently enough can combine the attribute values they are detecting, which enables the MPACA to learn influential variable interactions. This paper applies the model to real-world data from two domains. One is logistics, focusing on resource allocation rather than the more traditional vehicle-routing problem. The other is mental-health risk assessment. The task for the MPACA in each domain was to predict class membership where the classes for the logistics domain were the levels of demand on haulage company resources and the mental-health classes were levels of suicide risk. Results on these noisy real-world data were promising, demonstrating the ability of the MPACA to find patterns in the data with accuracy comparable to more traditional linear regression models. © 2013 Polish Information Processing Society.

The SEC’s retail investor 2.0: Interactive data and the rise of calculative accountability

The Securities and Exchange Commission (SEC) in the United States mandated a new digital reporting system for US companies in late 2008. The new generation of information provision has been dubbed by Chairman Cox, ‘interactive data’ (SEC, 2006a). Despite the promise of its name, we find that in the development of the project retail investors are invoked as calculative actors rather than engaged in dialogue. Similarly, the potential for the underlying technology to be applied in ways to encourage new forms of accountability appears to be forfeited in the interests of enrolling company filers. We theorise the activities of the SEC and in particular its chairman at the time, Christopher Cox, over a three year period, both prior to and following the ‘credit crisis’. We argue that individuals and institutions play a central role in advancing the socio-technical project that is constituted by interactive data. We adopt insights from ANT (Callon, 1986; Latour, 1987, 2005b) and governmentality (Miller, 2008; Miller and Rose, 2008) to show how regulators and the proponents of the technology have acted as spokespersons for the interactive data technology and the retail investor. We examine the way in which calculative accountability has been privileged in the SEC’s construction of the retail investor as concerned with atomised, quantitative data (Kamuf, 2007; Roberts, 2009; Tsoukas, 1997). We find that the possibilities for the democratising effects of digital information on the Internet has not been realised in the interactive data project and that it contains risks for the very investors the SEC claims to seek to protect.

The multiple pheromone Ant clustering algorithm

Ant Colony Optimisation algorithms mimic the way ants use pheromones for marking paths to important locations. Pheromone traces are followed and reinforced by other ants, but also evaporate over time. As a consequence, optimal paths attract more pheromone, whilst the less useful paths fade away. In the Multiple Pheromone Ant Clustering Algorithm (MPACA), ants detect features of objects represented as nodes within graph space. Each node has one or more ants assigned to each feature. Ants attempt to locate nodes with matching feature values, depositing pheromone traces on the way. This use of multiple pheromone values is a key innovation. Ants record other ant encounters, keeping a record of the features and colony membership of ants. The recorded values determine when ants should combine their features to look for conjunctions and whether they should merge into colonies. This ability to detect and deposit pheromone representative of feature combinations, and the resulting colony formation, renders the algorithm a powerful clustering tool. The MPACA operates as follows: (i) initially each node has ants assigned to each feature; (ii) ants roam the graph space searching for nodes with matching features; (iii) when departing matching nodes, ants deposit pheromones to inform other ants that the path goes to a node with the associated feature values; (iv) ant feature encounters are counted each time an ant arrives at a node; (v) if the feature encounters exceed a threshold value, feature combination occurs; (vi) a similar mechanism is used for colony merging. The model varies from traditional ACO in that: (i) a modified pheromone-driven movement mechanism is used; (ii) ants learn feature combinations and deposit multiple pheromone scents accordingly; (iii) ants merge into colonies, the basis of cluster formation. The MPACA is evaluated over synthetic and real-world datasets and its performance compares favourably with alternative approaches.