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It becomes vital for organizations to construct the strategies for new employees to accumulate empirical knowledge (1X. Y. Li, Jiang, Song, & Liu, 2017; X. Li, Jiang, 2Guan, Li, & Wang, 2019; Maslen, 2014; Reimlinger, Lohmeyer, Moryson, & Meboldt, 2019). Complex problems solving is an important resource of knowledge accumulation for engineers, especially for novice engineers, in the process of which novice engineers can transfer the external knowledge into their internal knowledge and as a result their expertise get accumulated and knowledge structure is reconstructed (Ahmed, Wallace, & Blessing, 2003; Hatchuel& Weil, 2003; Ho &Kuo, 2013; Wang & Hai, 2018). Accordingly, novice engineers’ expertise get accumulated and knowledge structure is reconstructed However, problem solving in complex conditions is different from that in simple conditions, and many cognitive factors and non-cognitive factors are involved for engineers to reason, evaluate and make beneficial decisions. (Funke, 2010; Scherer &Tiemann, 2012). An interesting question is whether the personal factors of novice engineers are more important in the process of knowledge accumulation, or whether the external Scenarios factors are more important? In this regard, this paper aims to identify the personal factors and external Scenarios factors for knowledge accumulation based on the complex cognition and Concept-Knowledge (C-K) theory, and then builds a novel complex cognitive structure model affecting novice engineers’ knowledge accumulation in the process of complex problems solving.
C-K theory considers that the complex problem solving is the process of individual knowledge accumulation. Complex problem solving aims to transform undecidable propositions (concepts) into true propositions (knowledge) (Hatchuel & Weil, 2003). In the process of solving complex engineering problem, unknown concept turns explicit, new objects and new knowledge are created (Hatchuel& Weil, 2009; Masson, Hatchuel, & Weil, 2016). Wang (2013) presents that both complex problems solving and knowledge accumulation belong complex cognitive processes (Wang, Wu, Chen, & Spector, 2013). Complex cognition is defined as all mental processes which are used by individuals for deriving new information and knowledge out of given information, with the intention to solve problems, make decision, and plan actions (Knauff& Wolf, 2010). The crucial characteristic of complex cognitive process is that it takes place under complex conditions in which a multitude of cognitive processes interact with one another or with other non-cognitive processes. The complex cognition, beyond the traditional single cognition, has obtained increasingly attention from societies of management, psychology, and neurosciences (Schmid, Ragni, Gonzalez, & Funke, 2011).
In this context, a research model is posited here that the knowledge accumulation is positively associated with external factors such as complex context, complex problem characteristics, and internal factors such as complex problem-solving strategies. Through literature review, each construct is, theoretically, decomposed into subcomponents. An empirical analysis is conducted in order to test the relationships among these constructs and structural equation modeling (SEM) is employed to analyze the data collected. Despite abundance of research on knowledge accumulation, there have been few studies concerning the theoretical and empirical research under the complex cognition and C-K theory, especially in the context of complex engineering problem solving.