Construction of Knowledge Automation Measuring Scale

Construction of Knowledge Automation Measuring Scale

Shabina Shaikh, Arabella Bhutto
Copyright: © 2021 |Pages: 25
DOI: 10.4018/IJITPM.2021040103
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Abstract

Organizations are moving from non-automated knowledge management to automated knowledge. Particularly in the banking sector to measure the automated knowledge, knowledge automation measuring scale is developed and tested. The purpose of this study is to develop the knowledge automation measuring scale (KAMS) and to measure the knowledge automation of banking processes through the same scale. The authors present the current standing of banks through KAMS and validated the results with stakeholders. A qualitative research is conducted; data is collected from 200 bankers who are at managerial level in commercial banks of Pakistan. Knowledge automation measuring scale is developed by considering Bohn's eight scale stages, identifying top banking activities and applying thematic analysis. Knowledge automation measuring scale is created and validated from the banking sector.
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2. Theoretical Aspect

Knowledge is widely recognized as essential competitive factor which can significantly support an organization’s adaptation, existence and performance (Bohn, 1994; Boisot, 1998; Mertins et al., 2000; O’Dell and Grayson, 1998; Palacios and Garrigos, 2006; Sigala and Chalkiti, 2015). Viewing firms as knowledge system help researchers and practitioners refine their interpretations of what organizations are. The magic to achieve coordinated action does not only depend on gathering knowledge but also depends on searching and highlighting ways of staying connected and interdepending knowledge each one has (Nonaka, 2005). Many organizations involve in handling and managing knowledge for leveraging knowledge both within the organization and outside to their shareholders (Rubenstein-Montano et al., 2001).

Successful firms use precise mechanisms to manage knowledge in technology driven contemporary organizations where focus is on globalization, technology, and industrial convergence (Gold and Arvind Malhotra, 2001; Santoro et al. 2018). The statistics show extensive research has been done on organizational knowledge focusing the issue managing knowledge to increase organizational benefit (Santoro et al. 2018).

It is important to know how much an organization recognizes and knows the effects of organizational knowledge (Alstete, 2007). Researchers have suggested frameworks to map and assess stages of knowledge at organizations. The framework suggested by Bohn (1994), and used by many researchers (Ramesh and Tiwana, 1999; Alstete, 2007; AlShihi and Zualkernan, 2012), contains an eight stage model explaining how knowledge grows through organizational learning, using technology, and an evolutionary perspective on how knowledge changes in each stage of the following knowledge growth model/framework (Figure 1). Bohn’s eight-scale stages (Bohn, 1994) is used to measure technological knowledge in a process. The scale measures the knowledge in a process starting from complete ignorance to complete knowledge.

Figure 1.

Bohn’s Eight-Scale Stages (Bohn, 1994)

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