The SAGE Handbook of Process Organization Studies 2016
DOI: 10.4135/9781473957954.n16
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Sequential Analysis of Processes*

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Cited by 8 publications
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“…. [are] deciphered to understand the process” (Poole et al, 2017: 254), we arranged the simplified descriptions of multiple NPD processes as strings of sequential data. An event sequence is an ordered listing of occurrences that is compiled to understand how a process such as a routine or parts of the routine are accomplished (Strauss and Corbin, 1998: 145).…”
Section: Methodsmentioning
confidence: 99%
“…. [are] deciphered to understand the process” (Poole et al, 2017: 254), we arranged the simplified descriptions of multiple NPD processes as strings of sequential data. An event sequence is an ordered listing of occurrences that is compiled to understand how a process such as a routine or parts of the routine are accomplished (Strauss and Corbin, 1998: 145).…”
Section: Methodsmentioning
confidence: 99%
“…We can identify this space of possible paths by analysing the sequential relations between actions in a process. In keeping with Cloutier and Langley (2020), we adopt an etic (outsiders) perspective, rather than an emic (insiders) perspective (Pike, 1967; see also Poole, Lambert, Murase, Asencio, & McDonald, 2017). Taking the example from the medical clinic: by looking at how checking-in is related to other actions such as sitting in the waiting room, going to the examination room and obtaining the patient history, and how these in turn are related to other actions in a patient visit, we can identify all the possible ways in which a patient visit can unfold.…”
Section: Introductionmentioning
confidence: 99%
“…Process data concern evolving phenomena and are temporally structured—being tied to specific moments in an unfolding process. Therefore, process data are typically organized according to temporal units such as events, episodes, or periods (Langley, 1999; Poole et al, 2017). To investigate how change and development come about, it is crucial that authors maintain the “temporal interconnectedness” of data (Pettigrew, 1990) and avoid chunking data only thematically or conceptually, because what happens at any moment in time is affected by what comes before and what may come after.…”
Section: Connecting Theory and Data: Temporal Coherencementioning
confidence: 99%