[雙語翻譯]--外文翻譯--數(shù)字化、“大數(shù)據(jù)”及會計信息的轉(zhuǎn)化（節(jié)選）

1、2800 單詞， 單詞，1.6 萬英文字符， 萬英文字符，4800 漢字 漢字出處： 出處：Bhimani A, Willcocks L. Digitisation, ‘Big Data’ and the transformation of accounting information[J]. Accounting types of knowledge; Big Data; outsourcing; management acco

2、unting; transformation1. 1. IntroductionGlobally produced data double every 18 months, with data volume processed by organisations expanding by 35 – 50% per year. It is likely that the next 10 years will see a significa

3、nt accel- eration of these trends (Manyika et al. 2011). The proliferation of mobile devices, applications and operating systems, is altering how we work, what we work on, where we work and what2. 2. From data to knowl

4、edgeTo assess the impact of digitisation on management accounting activities it is useful to consider documented conceptualisations of how data and knowledge relate to each other. The relationships between data, inform

5、ation and knowledge in a system used by agents – whether an individual, or an organisation, or a society – and how such a system can be seen as effective are of key relevance to understanding ongoing changes in account

6、ing systems design. One conception of linkages between data, information and knowledge is to regard data as a record, information as message and knowledge as a model (of how something works). The components form an inf

7、ormation system in receiving input, processing data into information and knowledge and producing outputs. At this abstract level Figure 1 can represent, with modifications in each case, how a com- puter system is design

8、ed to function, or how an individual, organisation or society might function. Boisot and Canals (2008) characterise information as constituting ‘those significant regu- larities residing in the data that the agent attemp

9、ts to extract from it’. They see data as originating in discernible differences in physical states of the world, in terms of time space and energy. However, an agent is needed – to be bombarded by these stimuli and sens

10、e some (or all) of it as data. But what constitutes a significant regularity can only be established with respect to the individual dispositions of the receiving agent. Moreover, data can only constitute information

11、for an agent that is already knowledgeable. Knowledge is, in this respect, a set of expectations held by an agent and modified by the arrival of information. For these authors, agents have values as well as stored ment

12、al models. In Figure 1, an agent operates perceptual filters to orient the senses to certain types of stimuli within a given range. Stimuli passing through this filter get registered as data, but then conceptual filter

13、s extract information-bearing data from what has been so registered: ‘both types of filters get tuned by the cognitive and affective expec- tations .. . shaped as these are by prior knowledge .. . to act selectively on

14、 stimuli and data’. In this light, the utility of data is that it can carry physical information about the world, that of infor- mation lies in the fact that it can modify an expectation or a state of knowledge, while

15、that of knowledge resides in it allowing an agent to act in adaptive ways in and upon the physical world. If this provides us with a plausible heuristic/normative model for discussing the issues con- fronting organisa

16、tions, then we still need to delve more deeply into the knowledge aspects of the model.Figure 1 distinguishes between tacit (uncodified, embodied) and explicit (capable of being clearly stated) knowledge. However, this i