Case Study of a Complex Informing System: Joint Interagency Field Experimentation (JIFX)

Autor: Sandra Sanchez Murphy, T. Grandon Gill, William F Murphy, Raymond R. Buettner
Jazyk: angličtina
Rok vydání: 2015
Předmět:
Zdroj: Informing Science The International Journal of an Emerging Transdiscipline, Vol 18, Pp 063-109 (2015)
ISSN: 1521-4672
1547-9684
Popis: Introduction An axiom of informing science is that the underlying complexity of the informing to be accomplished will exert a significant impact on the structure of the informing system most appropriate to achieve the desired informing outcome. The Joint Interagency Field Experimentation (JIFX) event incorporates a design intended to achieve informing at an unusually high complexity level. The present paper describes an exploratory research case study intended to examine how the nature of JIFX, viewed as an informing system, facilitates and has adapted to the task of informing a highly diverse set of clients, including inventors, software developers, military personnel, disaster recovery personnel, vendors, government contracting agencies, and academics. We begin with an introduction to informing systems theory, as it relates to complexity, and then examine the background and nature of the JIFX event. We then describe the methodology and report the results of a year-long research project that attempted to assess the consequences of past JIFX participation on a particular subset of clients: participants in the JIFX experiments. The results are then analyzed and the degree to which our observations of JIFX conform to, and extend, informing science are discussed and presented as a conclusion. Task Complexity and Informing Systems The nature and forms of task complexity have been recognized as being critical to achieving effective informing (Gill & Hicks, 2006). It has been further argued that one of the most important factors influencing the structure of an informing system is the degree to which it is focused towards routine informing versus complex informing (Gill, 2009). The theoretical underpinnings of the case study are based in these two areas. Sources of Task Complexity Task complexity is a term that has eluded definition for many decades, despite a number of attempts to specify it (e.g., Campbell, 1988; Gill & Hicks, 2006; Wood, 1986). The major challenge in dealing with the term is the ambiguous manner in which it has been used. For example, Gill and Hicks identified no fewer than 13 distinct definitions and usages of the term in the management and psychological literature that fell into five broad classes, shown in Table 1. Three Domains of Task Complexity Gill (2010) later proposed that a sixth class, based on biologist Stuart Kauffman's (1993) notion of complexity leading to a rugged fitness landscape, was necessary. With this, complexity could be viewed as occurring in three overlapping domains: what is experienced by the task performer, the characteristics of the symbolic representation of the task, and driven by the actual behavior of the real world context in which the task is performed. These three domains (also referred to as dimensions) are depicted in Figure 1 (adapted from Gill & Murphy, 2011) and listed in Table 2. [FIGURE 1 OMITTED] Ruggedness The third domain, which deals with real world contexts, is particularly relevant when it comes to the design of informing systems. Complexity in this domain derives from two principal sources: ruggedness and turbulence. Ruggedness describes the degree to which the attributes that describe a task state interact in determining its fitness. Fitness, in turn, specifies the desirability of a particular state. In a biological context, fitness tends to be driven by successful reproduction across generations (Gill & Hevner, 2011). In the context of a task, this might correspond to the degree to which a task performer attempts to return to a particular task state and the degree to which other performers seek the same state, perhaps as a consequence of imitation (Gill, 2012). To clarify the concept of ruggedness, the contrast of a multiple-choice test and a cooking recipe can be a useful example. If we represent the attributes of a multiple choice test in terms of the responses to each individual question, then (in the typical test) each response will contribute to fitness independently. …
Databáze: OpenAIRE
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