Impact of managerial communication, managerial support, and organizational culture difference on turnover intention: A tale of two merged banks

  • Received July 27, 2020;
    Accepted December 9, 2020;
    Published December 18, 2020
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/ppm.18(4).2020.30
  • Article Info
    Volume 18 2020, Issue #4, pp. 376-387
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Mergers and acquisitions are critical mechanisms for promoting the stable and effective production of the financial sector, and an effort to improve the strategic edge of financial institutions. M&A process also entails a high degree of confusion, which can be difficult for the workers. This study was conducted in the Philippines to examine the differences in the employees’ opinion in managerial communication, managerial support, and organizational culture difference relative to employee turnover. It also seeks to determine if the socio-demographic profile of respondents has a significant influence on turnover intention. The sample in this study is determined using a purposive sampling method. A total of 350 questionnaires are complete and feasible to analyze where 250 respondents belong to Bank A, and 100 respondents belong to Bank B. Using Levene-Welch post-hoc multiple comparison and binary logit regression with bootstrap, the findings revealed that managerial communication, managerial support, and organizational culture were associated with turnover intention. Further, the findings revealed that turnover intention differs per demographic profile. Therefore, management is to develop a post-merger integration plan, ensuring to attain competitive advantage and successful mergers and acquisitions.

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    • Table 1. Demographic characteristics
    • Table 2. Description of the constructs
    • Table 3. Correlation matrix
    • Table 4. Level of opinion on turnover intention relative to managerial communication, managerial support, and organizational cultural difference
    • Table 5. Omnibus tests of model coefficients and model summary for turnover intention
    • Table 6. Classification of odd events of turnover intention with a demographic profile
    • Table 7. Variables in the equation to predict the odds of low turnover intention associated with factors and demographic profile
    • Table 8. Variables in the equation to predict the odds of high turnover intention associated with factors and demographic profile
    • Table 9. Variables in the equation to predict the odds of high and low turnover intention associated with a demographic profile
    • Conceptualization
      Myra V. De Leon
    • Data curation
      Myra V. De Leon
    • Formal Analysis
      Myra V. De Leon
    • Methodology
      Myra V. De Leon
    • Investigation
      Myra V. De Leon
    • Project administration
      Myra V. De Leon
    • Resources
      Myra V. De Leon
    • Software
      Myra V. De Leon
    • Validation
      Myra V. De Leon
    • Visualization
      Myra V. De Leon
    • Writing – original draft
      Myra V. De Leon
    • Writing – review & editing
      Myra V. De Leon