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This paper aims to provide insights into service innovation (SI) during the COVID-19 crisis and its potential impact on tourism development in the medium-to-long term. The pandemic had a devastating effect on the industry, requiring immediate mitigation. It is yet to fully establish the impact of SI in the face of the COVID-19 volatility, uncertainty, complexity and ambiguity (VUCA). This study discusses the potential link between SI and COVID-19 crisis mitigation and offers recommendations for tourism recovery.

This paper synthesizes empirical evidence on post-crisis tourism SI using a theory-based general literature review approach.

COVID-19 crisis spun various forms of SI, which emerged as a conventional solution to crisis prevention, encompassing the management of crisis-time competitiveness, revenue deficits and risk perception. However, resistance to innovative services is linked to situational conditions.

COVID-19 is an unprecedented crisis. Therefore, this study serves as a primer for further inquiry into SI. For instance, areas such as governance in tourism innovation and consumers' inclination toward innovation-driven services are underexplored.

SI acts as a situational facilitator, but its characteristics can impede or facilitate adoption. Moreover, the irrelevance of innovations in some environments is evidenced. Thus, practitioners must adopt a responsive learning approach in SI adoption. To mitigate the COVID-19 impacts, reconfiguration in SI, recovery marketing strategy, knowledge gap and governance will be critical interventions.

This paper is one of the first comprehensive discussions on the potential role of SI in mitigating the impact of COVID-19 on the THI.

The goal of the study is to offer important insights into the dynamics of the cryptocurrency market by analyzing pricing data for Bitcoin. Using quantitative analytic methods, the study makes use of a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and an Autoregressive Integrated Moving Average (ARIMA). The study looks at how predictable Bitcoin price swings and market volatility will be between 2021 and 2023.

The data used in this study are the daily closing prices of Bitcoin from Jan 17th, 2021 to Dec 17th, 2023, which corresponds to a total of 1065 observations. The estimation process is run using 3 years of data (2021–2023), while the remaining (Jan 1st 2024 to Jan 17th 2024) is used for forecasting. The ARIMA-GARCH method is a robust framework for forecasting time series data with non-seasonal components. The model was selected based on the Akaike Information Criteria corrected (AICc) minimum values and maximum log-likelihood. Model adequacy was checked using plots of residuals and the Ljung–Box test.

Using the Box–Jenkins method, various AR and MA lags were tested to determine the most optimal lags. ARIMA (12,1,12) is the most appropriate model obtained from the various models using AIC. As financial time series, such as Bitcoin returns, can be volatile, an attempt is made to model this volatility using GARCH (1,1).

The study used partially processed secondary data to fit for time series analysis using the ARIMA (12,1,12)-GARCH(1,1) model and hence reliable and conclusive results.

This study examines the influence of stock liquidity on stock price crash risk and the moderating role of institutional blockholders in Vietnam’s stock market.

Crash risk is measured by the negative coefficient of skewness of firm-specific weekly returns (NCSKEW) and the down-to-up volatility of firm-specific weekly stock returns (DUVOL). Liquidity is measured by adjusted Amihud illiquidity. The two-stage least squares method is used to address endogeneity issues.

Using firm-level data from Vietnam, we find that crash risk increases with stock liquidity. The relationship is stronger in firms owned by institutional blockholders. Moreover, intensive selling by institutional blockholders in the future will positively moderate the relationship between liquidity and crash risk.

Since stock liquidity could exacerbate crash risk through institutional blockholder trading, firm managers should avoid bad news accumulation and practice timely information disclosures. Investors should be mindful of the risk associated with liquidity and blockholder trading.

We contribute to the literature by showing that the activities of blockholders could partly explain the relationship between liquidity and crash risk. High liquidity encourages blockholders to exit upon receiving private bad news.

This paper aims to investigate the impact of the COVID-19 pandemic on university students' employability skills and give insights into preparation for future crises that may happen.

Employing an interpretative phenomenological approach with the frame of social cognitive theory, the current study examined the changes in environmental, behavioral and personal elements of human functioning for employability skills being affected by the conditions during the pandemic.

Findings based on ten in-depth semi-structured interviews with students at universities in Vietnam highlighted that the global pandemic performed as both challenge and an opportunity for employability skills development, yet the extent to which the students can benefit from the new studying conditions attributed to each individual's initiatives in taking advantages of resources and acting against difficulties.

Whether the pandemic became a hindrance or a motivation for students' employability skills to develop and whether students effectively utilized an agency to overcome challenges and improved their skills after the pandemic have not yet been investigated. This study added to the body of literature regarding self-regulated learners by demonstrating agency in the learning process as well as how to manage careers and improve employability skills by making use of resources in disconnected settings.

Crowdfunding (CF) has become an increasingly popular means of financing for entrepreneurs and has attracted significant attention from both researchers and practitioners in recent years. The purpose of this study is to investigate the core content and knowledge diffusion paths in the CF field. Specifically, we aim to identify the main topics and themes that have emerged in this field and to trace the evolution of CF knowledge over time.

This study employs co-word clustering and main path analysis (MPA) to examine the historical development of CF research based on 1,528 journal articles retrieved from the Web of Science Core Collection database.

The results of the analysis reveal that CF research focuses on seven themes: sustainability, entrepreneurial finance, entrepreneurship, fintech, social entrepreneurship, social capital, and microcredits. The analysis of the four main paths reveals that equity CF has been the dominant topic in the past years. Recently, CF research has tended to focus on topics such as fintech, the COVID-19 pandemic, competition, Brexit, and policy response.

To the authors' best knowledge, this is the first attempt to explore knowledge diffusion dynamics in the CF field. Overall, the study offers a structure for analyzing the paths through which knowledge is diffused, enabling scholars to effectively manage a large volume of research papers and gain a deeper understanding of the historical, current, and future trends in the development of CF.

Sustainable development goals and the climate change agenda are becoming widely promoted topics of research for the 21st century. The role of cities is increasingly recognised as central to investigating these topics. Yet, the field of informal sector entrepreneurship which so many urban entrepreneurs in developing countries depend upon is seldom considered. To redress this imbalance, this study aims to develop a decision model in accordance with institutional theory (IT) and resource dependency theory (RDT) for city managers to deploy. The model identifies and prioritises optimal strategies to address the three areas of sustainability requirements environment society and economy within the study context of Bangladesh.

This study used a mixed methods research design. In the qualitative part, the authors identified the three areas of sustainability requirements (i.e. environment, society and economy) and their corresponding strategies involving the informal sector that operates within the urban environment. In the quantitative part, the authors applied fuzzy quality function deployment (QFD) integrated with the 0-1 non-linear optimisation technique to identify optimal strategies.

The findings show that strategies such as legitimate frameworks, waste management, allocation of urban public space and training programs contribute in important ways to the three areas of sustainability requirements.

The proposed decision model will assist policy-makers and city managers to prioritise sustainability requirements and implement optimal strategies to address those requirements.

Through the integration of IT and RDT, the decision model developed in this study is unique in its application to urban-based informal entrepreneurship in the context of developing countries. The effective application of the fuzzy QFD approach and the optimisation model in the context of urban-based informal entrepreneurship also offers unique contributions to the field of study.