Abstract
The effects of COVID-19 on tourism are irreversible, with potential reductions in income, job losses, shifting working landscapes, and visible health-related fears. These adversities are reinforced in the hospitality business, particularly for hotels, the income streams of which rely on individual movements. This study investigates the process undertaken by the hotel industry in Indonesia to face the current challenges, particularly in terms of the dynamic capabilities possessed by hotel businesses. This construct discusses the potentiality of maximizing existing resources and its impact on innovation norms to leverage hotel dynamics. A total of 329 hotel managers responded to the survey, and the data were finalized by employing PLS-SEM. The findings primarily support the hypothesized direct relationships, but refute the presence of indirect relationships. The results amplify how past investments in sustainable resources are easily deployed assets during COVID-19 and create a welcoming environment for dynamic innovation among hotels during periods of change.
Highlights
As the COVID-19 pandemic has spread worldwide, new business practices have been developed, in the hotel industry
We argue that possessing integrated dynamic capability (D.C.) is critical for hospitality business during adversity, but requires several prerequisite foundations, i.e., existing resources and innovation norms within the organization
This study proposes the technological support (Ray et al 2004) and hotel infrastructure (Choi and Chu 2001) are the past capacity possessions that can be established to support hotel innovation norms and dynamic capability
Summary
This study approaches the solutions to the proposed hypotheses by quantitative This At study solutions to theby proposed by quantitative method. Best,approaches this study the is still exploratory forming hypotheses inferential statistics for the method. Best, this study still exploratory by forming the variable At relationships. Variance-based partial-least-square structural-equation-modeling for the partial-least-square structural-equation-modeling the analysis. The deletion whether the indicators can represent the variables by the outer model quality. We check the model discriminant validity by its heterotrait–monotrait test, with an expected value below 0.9 This test ensures that all indicators only represent the said variable instead of other unrelated constructs. These validity and reliability tests are the backbone for conducting the inner model measurement to observe the answers to the proposed hypotheses. All steps will be further explained in the result section
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