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The tourism industry has grappled with the challenges posed by the onset of the coronavirus disease (COVID-19) since the start of 2020, experiencing a complete lockdown that profoundly affected travel activities. This viral outbreak had a critical impact on both the financial and non-financial aspects of life, including the intellectual capital (IC) of the tourism and hospitality sectors. However, there is a scarcity of studies addressing this issue within the context of tourism-related businesses. Thus, this paper aims to investigate the changes in the overall IC and its components before and during the COVID-19 pandemic, with a specific focus on understanding the transformation of IC in the tourism industry of Thailand, a country that is highly dependent on tourism. The study involved 37 tourism-related companies listed on the Stock Exchange of Thailand (SET). Organizational data from financial and annual reports published between 2019 and 2020 were collected for analysis. The assessment of value added intellectual capital (VAICTM) was employed to evaluate the performance of the overall IC and its components during the pandemic. The results, based on the testing of four hypotheses, indicated that most hypotheses were accepted, signifying a substantial transformation in the overall IC performance of tourism-related companies during the pandemic crisis. This transformation was observed in the IC components of physical and human capitals. However, the structural capital was the only IC component that did not experience a significant impact from COVID-19. To comprehend the reasons and effects of the IC transformations during the pandemic, this study delved into the relevant literature. Additionally, the paper includes implications to support firms in preparing for future challenges. [ABSTRACT FROM AUTHOR]

Today, logistics management requires a comprehensive set of performance indicators that measure both tangible assets and intellectual capital (IC) of organisations. Nevertheless, most of the measures used in the past mainly related to the financial aspect, although some specific components of IC, such as process efficiency and effectiveness, have been considered. Logistics literature lacks a comprehensive consideration of the diverse IC measures, and it is unclear which area of IC requires more focus and development. Therefore, to explore and identify an opportunity for improvement, this study reviews the academic literature related to IC measures in logistics management. This literature review considers 111 academic articles published between 1994 and 2016. Following the six dimensions of the IC-Index, all indicators obtained from the literature are classified according to IC elements. The key contribution of this review is that it addresses the following gaps in the literature: the limited adoption of comprehensive IC methods in logistics studies; underdevelopment of specific indicators and measures used; failure to consider all human capital as well as renewal and development elements; and, finally, lack of academic research considering the influences among the different IC elements and logistics and financial performance. [ABSTRACT FROM AUTHOR]

This study aims to improve the existing problems of intellectual capital (IC) measurement methods including those with unclear and unspecific calculation details and the inability to valuate the influences between IC measures and between IC components, which is a fundamental characteristic of IC. To address the fundamental issues of past methods, this study integrates two multi-criteria decision-making (MCDM) methods: the analytic network process (ANP) and the simple additive weighting (SAW) method, both of which provide specific and clear calculation procedures. ANP is adopted to manage the valuation of influences between IC elements, while SAW is used to solve incommensurable units of IC performance indicators and different concentrations on IC measures and components. Implementation of the method revealed a clear and systematic measurement procedure. The proposed method could consider the relationships among IC measures as well as among IC components and presented calculated results in the form of the weights of IC measurement compositions. Furthermore, the method maintained the crucial characteristics of IC measurement: the ability to standardise units of measure and the capability to valuate the performance of IC for the appropriate measure, component, and holism level. [ABSTRACT FROM AUTHOR]