Abstract:
Organizational knowledge resides in the processes, products, services, people, culture,
documents, and systems of an organization. Organizational knowledge management
consists of identification, acquisition, development, storage, transfer, utilization, and
evaluation of knowledge within and outside the organization. Effective organizational
knowledge management not only enhances the performance of the organization but also
help to get competitive advantage. Enterprise systems are enterprise application
software to support organizational processes, knowledge management, reporting, data
analytics, etc. Knowledge management systems (KMS), in particular, are a type of
enterprise systems used by organizations to organize and manage organizational
knowledge. These systems support the implementation of knowledge management
within an organization and help organizations to generate new knowledge while
recording, utilizing, and allocating existing knowledge. The potential for adopting KMS
is an essential element in SMEs, especially in developing countries. Large
Organizations are widely accepting these systems while there is still a scarcity of
understanding of the factors behind the non-adoption of KMS by SMEs. The software
industry is a complex, knowledge-extensive, and experimental industry and can get
immense benefits from knowledge management systems. Therefore, the interest of this
research is to examine the adoption patterns of SMEs belong to the software industry
to adopt the knowledge management systems. The research model of this study is based
on the concept of UTAUT2 (Extended Unified Theory of Acceptance and Use of
Technology) and investigating its constructs to examine the adoption patterns of KMS.
This study examines the impact of Performance Expectancy, Effort Expectancy, Social
Influence, Price value on the Behavioral Intention of user to use the KMS and how
Facilitating Conditions and Behavioral Intention to use KMS influence the Use
Behavior of a user to adopt KMS. This is an explanatory study and descriptive in nature.
The quantitative approach is used and an online survey was conducted among 383
respondents. Total 280 responses were analyzed by using SPSS. This sample was
adequate as using Power and Precision software a minimum sample of 230 was
computed. To understand the effect of the understudy constructs we ran pearson
correlation and regression tests. The outcome of this research show that Social
Influence has a significant influence on the employee’s behavioral intention to adopt
KMS while performance expectancy and price value has strong and effort expectancy
has a weak but positive impact on the behavioral intention of the employee to use KMS.
The results also show that facilitating conditions and behavioral intention are the
components that strongly explained the use behavior of a user to use KMS.
