The Antecedents of Search Performance: Information/ Knowledge Seeking for Task Completion

The Antecedents of Search Performance: Information/ Knowledge Seeking for Task Completion

Mathupayas Thongmak (Thammasat Business School, Thammasat University, Thailand)
Copyright: © 2020 |Pages: 22
DOI: 10.4018/IJKM.2020010102
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Searching and evaluating information are two core information processes of an individual's information behavior. Thus, this research aims to examine search performance to complete tasks regarding experiences, knowledge, and intention in both views. Based on literature studies, this study considered experiences as drivers of knowledge; experiences and knowledge as determinants of intention; and intentions as predictors of search performance. The proposed model was empirically tested using structural equation modeling. The results supported all relationships except the influence of experiences on intention. This work contributes to a theoretical model of antecedents driving search performance for task fulfillment. The findings help educational institutions/ enterprises to enhance students/ workers' search performance. Suggestions to improve the decision guidance of a KMS are also described.
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Data, information, and knowledge are key resources of organizations, which their distinctions are not always obvious (Patel, McCarthy, Morris, & Elhag, 2000; Yan & Davison, 2013; Yuan, Rickard, Xia, & Scherer, 2011). The value of data comes from the process to transform data into information, knowledge, or wisdom and the use of these resources in the value-creation activities (Jennex, 2017). Knowledge contains information, but not to be vice versa (Jennex & Olfman, 2006). It is the most valuable asset to maintain an organization's competency (Ranasinghe & Dharmadasa, 2013; Shanshan, 2014). Knowledge management is an ability to apply the collection of those resources to influence current activities (M. Jennex & Olfman, 2003, 2005). Successful innovation relies on the efficient utilization of knowledge both from external and internal (Patel et al., 2000; Sun & Hou, 2017).

Business performance is defined as the degree to which an organization is able to fulfill its tasks to meet stakeholders’ needs (Vij & Farooq, 2014). Organizational learning is an organization’s ability to collect and use information/ knowledge to improve task performance (Patel et al., 2000). According to the revised knowledge-KM pyramid of M. E. Jennex (2017), organizational learning could happen both as a bottom-up process (starting with the interpretation of data) or a top-down process (determining from wisdom/ intelligence). Organizational Memory (OM) is the set of information and knowledge used in a process/ task in order to make it effective (Jennex & Olfman, 2003; Jennex & Olfman, 2006). Four key knowledge management processes to develop knowledge resources for an organization consist of identification, acquisition, distribution and preservation (Becker, Jørgensen, & Bish, 2015; Shanshan, 2014). Knowledge/ information retrieval in the acquisition phase plays an important role in OM (Schwartz, Divitini, & Brasethvik, 2000; Yuan et al., 2011). A Knowledge Management System (KMS) retains information/ knowledge and make them available in the computerized forms (Jennex & Olfman, 2003). Searching and knowledge/ information quality are the success factors of the KMS success model (M. Jennex & Olfman, 2005).

Simple knowledge-seeking tasks can be easily fulfilled through the Internet (Yuan et al., 2011). The Internet has been increasingly used to obtain data, information, and knowledge because of its ease of access and more up-to-date (Al-Harthi & Ginsburg, 2003; Patel et al., 2000; Quintana, Pujol, & Romaní, 2012; Smith, Baxter, Boss, & Hunton, 2012; Yuan et al., 2011). Web platforms such as Wikipedia, YouTube, and Facebook also promote a new way of information search (Campatelli, Richter, & Stocker, 2016). The Internet and the World Wide Web (WWW) are valuable sources for younger and older people searching for health information, coaches searching for sport information, engineers searching for software development information, and consumers searching for products (Assimakopoulos & Yan, 2006; Cheng & Huang, 2013; Robertson-Lang, Major, & Hemming, 2011; Shanahan, 2008; Wilson, Bloom, & Harvey, 2010; Xiao, Sharman, Rao, & Upadhyaya, 2014; Younger, 2010). There is an abundance of information/ knowledge on the Internet, but not all is of high quality (Quintana et al., 2012; Shanahan, 2008; Tanaka et al., 2010; Yuan et al., 2011). Thus, evaluating the sources of information/ knowledge is an essential process (ALHawari, Talet, Alryalat, & Hadi, 2008). The organization also requires an effective filter to verify sources of a formless network of knowledge on the Internet (Jennex, 2017).

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