The semantics of the uncertainty literature

Kwakkel, Jan H.; Cunningham, Scott

doi:10.1109/picmet.2008.4599838

Cited by 5 publications

(3 citation statements)

References 98 publications

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“…In light of the heavily loading terms, we assigned the names to the factors. A more detailed exploration of this table can be found in Kwakkel and Cunningham (2008).…”

Section: Resultsmentioning

confidence: 99%

Managing polysemy and synonymy in science mapping using the mixtures of factor analyzers model

Kwakkel

Cunningham

2009

J. Am. Soc. Inf. Sci.

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A new method for mapping the semantic structure of science is described. We assume that different researchers, working on the same set of research problems, will use the same words for concepts central to their research problems. Therefore, different research fields and disciplines should be identifiable by different words and the pattern of co-occurring words. In natural language, however, there is quite some diversity because many words have multiple meaning. In addition, the same meaning can be expressed by using different words. We argue that traditional factor analytic and cluster analytic techniques are inadequate for mapping the semantic structure if such polysemous and synonymous words are present. Instead, an alternative model, the mixtures of factor analyzers (MFA) model, is utilized. This model extends the traditional factor analytic model by allowing multiple centroids of the dataset. We argue that this model is structurally better suited to map the semantic structure of science. The model is illustrated by a case study of the uncertainty literature sampled from data from the ISI Web of Science. The MFA model is applied with the goal of discovering multiple, potentially incommensurate, conceptualizations of uncertainty in the literature. In this way, the MFA model can help in creating understanding of the use of language in science, which can benefit multidisciplinary research and interdisciplinary understanding, and assist in the development of multidisciplinary taxonomies of science.

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“…In light of the heavily loading terms, we assigned the names to the factors. A more detailed exploration of this table can be found in Kwakkel and Cunningham (2008).…”

Section: Resultsmentioning

confidence: 99%

Managing polysemy and synonymy in science mapping using the mixtures of factor analyzers model

Kwakkel

Cunningham

2009

J. Am. Soc. Inf. Sci.

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“…Moreover, how do scholars use these different terms interchangeably? Moreover, in some situations, how does the meaning of uncertainty change based on the context (Kwakkel & Cunningham, 2008)? All those questions underline the critical importance of defining and conceptualizing uncertainty.…”

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confidence: 99%

“…All those questions underline the critical importance of defining and conceptualizing uncertainty. To define and conceptualize uncertainty, the researcher needs to develop taxonomy or typologies to articulate what the uncertainty is, what its characteristics are, and how individuals, managers, or organizations respond to the uncertainty (Kwakkel & Cunningham, 2008).…”

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confidence: 99%

How do middle managers deal with uncertainty in the strategy process

Aktaş¹,

Duarte²

2022

IJMDM

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Uncertainty is an unavoidable dimension of organizational life, and it is also challenging even for the most competent managers (Pich, Loch, & Meyer, 2002). This thesis examined middle managers' uncertainty responses during the formulation and implementation of the strategy process in three studies.The first study was qualitative and intended to expose the sources of uncertainty, managerial responses, and variables, which are essential for middle managers to cope with uncertainty in the strategy process. Study 1, involving interviews with 22 middle managers in civilian and military organizations, resulted in six sources, including a new classification--International instability and disasters--and five different responses: Collaborative responses, Emotional responses, Cognitive responses, Value-based responses, and Bureaucratic responses. In the second study, we conducted a Multidimensional scaling technique (N=70) to create a taxonomy of perception of managerial uncertainty responses in order to understand the nature of uncertainty in any organization and to help to build new theories. Results indicated six clusters: Protection by Support, Protection by Structure, Protection by Scapegoats, Certainty of Change, Development by Debate, and Development by Change. In the third study, we examined the effects of individual responses to uncertainty and organizational factors on managerial responses using quantitative analysis (N=310). The results showed that organizational-level knowledge sharing has positive effects on managers' desire of change. This study added a new source of uncertainty and five different managerial responses to uncertainty, and revealed that individual-level cognitive uncertainty and desire of change result in bureaucratic and collaborative responses. Additionally, we contend that managers respond to uncertainty v variously, from suppressing to collaboration, either to protect themselves or to act towards a constructive change in the organizations.

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