Influence of knowledge transfers on the achievement of change management in the creative industry

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This study aims to determine the influence of knowledge transfer on change management by involving information technology, information systems, and organizational culture variables. The study was conducted in the Java region, Indonesia, involving one of the creative industry subsectors, namely the application and game developer subsector. This study uses qualitative and quantitative research methods. In the qualitative method, online interviews were conducted with five production managers from application and game development companies to confirm and understand the variables used in the study (information technology, information system, organization culture). In the quantitative method, a survey was conducted with 168 production employees from five companies as respondents. A proportional random sampling technique was utilized, using AMOS 24 to test the hypotheses. Data analysis included descriptive statistical methods, parametric statistical methods, and confirmatory factor analysis. Hypothesis testing shows that information technology (p = 0.000; β = 0.622; cr = 5.606) and information systems (p = 0.002; β = 0.280; cr = 3.048) significantly influence knowledge transfer. Information technology (p = 0.023; β = 0.279; cr = 2.274) and information systems (p = 0.000; β = 0.304; cr = 3.374) also significantly influence change management. Knowledge transfer significantly affected change management (p = 0.035; β = 0.271; cr = 2.110). Organizational culture significantly influences change management (p = 0.011; β = 0.145; cr = 2.554). Organizational culture, namely trust, becomes an element in accelerating change management (p = 0.042; β = 0.459; cr = 1.998). Interestingly, knowledge transfer only mediates information technology in achieving change management (t = 2.00 > 1.96).

Acknowledgment
This work was supported by the Faculty of Information Technology, Satya Wacana Christian University, for the research budget.

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    • Figure 1. Normality test
    • Table 1. Calculation table for each company
    • Table 2. Respondents’ demographics
    • Table 3. Output for mean, standard deviation, loading factor, validity, and reliability tests
    • Table 4. Goodness of fit test
    • Table 5. Hypothesis testing
    • Table 6. Sobel test
    • Table A1. Questionnaire reserarch instrument
    • Tabel B1. Sobel Test Calculation: Test 1
    • Tabel B2. Sobel Test Calculation: Test 2
    • Conceptualization
      Anton Hermawan, Mohammad Isa Irawan
    • Formal Analysis
      Anton Hermawan
    • Funding acquisition
      Anton Hermawan
    • Writing – original draft
      Anton Hermawan
    • Writing – review & editing
      Anton Hermawan, Bambang Widjanarko Otok
    • Supervision
      Mohammad Isa Irawan, Bambang Widjanarko Otok
    • Validation
      Mohammad Isa Irawan
    • Visualization
      Mohammad Isa Irawan, Bambang Widjanarko Otok
    • Methodology
      Bambang Widjanarko Otok
    • Software
      Bambang Widjanarko Otok