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The COVID-19 pandemic has affected around 216 countries and territories worldwide and more than 2000 cities in India, alone. The smart cities mission (SCM) in India started in 2015 and 100 smart cities were selected to be initiated with a total project cost of INR 2031.72 billion. Smart city strategies play an important role in implementing the measures adopted by the government such as the issuance of social distancing regulations and other COVID-19 mitigation strategies. However, there is no research reported on the role of smart cities strategies in managing the COVID-19 outbreak in developing countries.

This paper aims to address the research gap in smart cities, technology and healthcare management through a review of the literature and primary data collected using semi-structured interviews.

Each city is unique and has different challenges, the study revealed six key findings on how smart cities in India managed the COVID-19 outbreak. They used: Integrated Command and Control Centres, Artificial Intelligence and Innovative Application-based Solutions, Smart Waste Management Solutions, Smart Healthcare Management, Smart Data Management and Smart Surveillance.

This paper contributes to informing policymakers of key lessons learnt from the management of COVID-19 in developing countries like India from a smart cities’ perspective. This paper draws on the six Cs for the implications directed to leaders and decision-makers to rethink and act on COVID-19. The six Cs are: Crisis management leadership, Credible communication, Collaboration, Creative governance, Capturing knowledge and Capacity building.

This research addresses the pressing need for comprehensive studies in the rapidly evolving field of city tourism. This study aims to understand the overall performance of the International Journal of Tourism Cities (IJTC), the structure of knowledge in city tourism research and the prevalent themes and trends arising from IJTC.

A bibliometric analysis was conducted to scrutinize the publication patterns in IJTC. This involved examining parameters such as the annual count of published articles, the keywords used in them and their respective authors.

The findings reveal that IJTC has a growing and diverse publication output, establishing itself as a reputable and influential publication within urban tourism research. The results reflect various aspects and themes in city tourism research.

The study has certain limitations. The data used for analysis was obtained exclusively from the Scopus database. The analysis was conducted using only one software package, Bibliometrix. Other software packages may offer different features for bibliometric analysis. The study relied exclusively on quantitative methods for data analysis. Qualitative methods could have provided more nuanced interpretations of the data.

Comparative analyses could be conducted between IJTC and other journals within urban tourism or related disciplines. Such research would yield valuable insights into the current state of the field and aid in identifying areas warranting further investigation.

The findings from this study can inform the decisions and actions of various stakeholders involved in urban tourism. Practitioners and policymakers can draw from this research to make informed decisions. Existing and emerging authors can identify relevant topics for their research. Readers can access pertinent information for their needs.

This study offers a unique contribution by thoroughly comprehending the performance of IJTC between 2015 and 2023. It progresses the existing body of knowledge on city tourism research by examining its current status and future trends.

This paper aims to explore the Spanish Self-Initiated Expats’ (SIEs) motivations and factors involved in the choice of the host destination.

Through an exploratory and qualitative study, drawing upon SIE literature on motivations and careers, 22 Spanish SIEs were interviewed in a semi-structured way.

Most SIEs clearly detailed the line of reasoning behind the host destination choice (specific destination); a second group considered a limited number of potential countries to relocate to (alternative destinations), and the smallest one did not choose a specific location. Career motivations were the most mentioned ones and different degrees of career planning were found: those with a very defined career planning process relied upon one potential destination, while those with a less defined one considered several alternative host destinations. The European Region Action Scheme for the Mobility of University Students experience was one of the most mentioned factors influencing the choice of the host destination, which may be common to other European Union (EU) nationals. As to the limiting ones, the visa requirements outside the EU were identified. Other factors were particular to Spain, such as the perceived need for English proficiency for a successful global career and the degrees of career planning.

These findings may assist Talent Management Managers to align organizational strategies with SIEs motivations. They may also help future Spanish and European SIEs in their individual career management process.

This study contributes to a better understanding of the expatriation motivations and factors influencing the destination location of Spanish SIEs, adding to the SIE and global career literature.

This paper aims to investigate place marketing and branding at the micro-place scale through the case study of St Christopher’s Place in London (UK). This study illustrates the distinctive differences of micro-place marketing, in comparison to city and country levels.

An exploratory case study was conducted through a sequential mixed methods approach involving direct observation, semi-structured interviews, questionnaires and social media analysis. Analysis of data was performed by using thematic analysis and triangulation of quantitative measures collected through the questionnaire and social media analysis.

Analysis of data illustrated noticeable differences of place management at the micro-place level compared to city or country scale of place marketing and branding. The function of emotional marketing leading to value co-creation is more effective at this level, establishing close and personal ties between occupiers and customers. Yet, measurement of micro-place marketing and branding value creation is difficult to achieve.

This study draws attention to the unique value and benefits of place branding at smaller spatial scales. Findings contribute to the place micro-brand concept by adding knowledge of micro-places through place management activities comparing them with city and country scales, and emotional marketing value co-creation practices, including challenges relating to measurement.

Being awarded world heritage status is a distinguishing factor when it comes to promoting tourism in a city. Tourism in these cities should be developed in a way that does not compromise either the city’s heritage or the inhabitants' quality of life. Thus, the main purpose of this paper is to analyze the effects of a European city achieving world heritage status on the subjective quality of life of its citizens.

First of all, we classify European cities according to whether or not they have been declared world heritage sites. Then, we analyze the effect of this classification on the main aspects used to measure the residents' perception of quality of life that are available in the Flash Eurobarometer 419.

The results show that achieving world heritage status has a negative effect on residents' perceptions of the noise level, air quality and feeling of safety. However, it does not affect their perceptions of public transport or cleanliness. In addition, world heritage status positively affects residents’ perceptions of the cultural activities in the city and their ease of finding a job. Residents report high levels of happiness in both world heritage and non-heritage cities, although levels are somewhat higher in non-heritage cities.

Residents' perceptions of the influence of tourism on their quality of life are undoubtedly of major importance; however, due to a lack of available data, few studies have examined this subjective quality of life at the city level.

This research investigates Airbnb’s financial implications in emerging economies and their potential to influence stock market profitability.

Employing a multifaceted approach, the study combines parametric and nonparametric tests, robustness checks, and regression analysis to assess the impact of Airbnb’s announcements on emerging economy stock markets.

Airbnb’s announcements affect emerging economies' stock markets with a distinct pattern of cumulative abnormal returns (CAR): negative before the announcement and positive afterward. Informed investors strategically leverage this opportunity through short selling before the announcement and acquiring positions following it. Regression analysis validates these trends, revealing that stock index returns and inbound tourism affect CAR before announcements, while GDP growth influences CAR afterward. Announcements pertaining to emerging economies exert a more pronounced impact on stock indices compared to city-specific announcements, with COVID-19 period announcements demonstrating greater significance in abnormal returns than non-COVID-19 period announcements.

This study advances existing literature through a comprehensive range of statistical tests, differentiation between emerging countries and cities, introduction of five macroeconomic variables, and reliance on credible primary Airbnb data. It highlights the potential for investors to leverage Airbnb announcements in emerging markets for stock market profits, emphasizing the need for adaptive investment strategies considering broader macroeconomic factors.

The purpose of this study is to examine the effects of market-based approach to provision of housing to low-income households in urban Malawi.

This study was conducted in Blantyre, Malawi, between 2019 and 2022 and used both quantitative (household survey) and qualitative (in-depth interviews and document study) methods of data collection. Interviews were conducted with key players and investors in the housing sector. Household survey data were analyzed through descriptive statistics, which allowed the generation of descriptive housing valuables, whereas qualitative data were analyzed through content analysis.

This paper demonstrates that, rather than ameliorating the housing problems facing low-income households, the market approach to provision of housing in Malawi has worsened the housing situation in the country. This is so because the market approach to the provision of housing in Malawi is not only enforcing the logic of capitalistic accumulation in the housing sector but also supporting mechanisms of exclusion based on economic stratification within the community.

Completeness of data over time as there is no market data bank available in the country.

The findings from this study suggest that some degree of state intervention in addressing the housing problem in Malawi is required.

The study findings suggest that a market approach to the provision of housing can increase social inequality as low-income households face challenges in accessing housing.

There is a paucity of research on the effects of the market approach on the provision of affordable housing to low-income households in Malawi. This paper assesses this important policy gap and provides significant policy directions.

This paper aims to develop a cross-border regional brand management model to help enhance cooperation for developing such localities. It analyzed its applicability in the Brazil–Argentina and Italy–Austria cross-border regions comprising several cities.

A systematic literature review was conducted to obtain a theoretical basis and select elements for creating the cross-border regional brand management (CRBM) model. To apply the model, in-depth interviews were conducted with 19 specialists of different nationalities and distinct expertise on cross-border governance and regional branding. In addition, to validate the proposed model, a focus group was carried out, and specialists were consulted using forms, providing 22 additional opinions.

The results show good managerial practices and gaps that must be overcome to create and manage the brands from the two regions analyzed.

The theoretical contributions consist in extending the literature in place branding by presenting the first CRBM model and the conceptual explanation of each of the model's elements.

The study's practical implications occur through the suggestion of good management practices for the studied localities arising from the applicability of the CRBM model. Furthermore, it is expected that the model developed can be applied in other locations, bringing practical contributions to the management and creation of cross-border regional brands in other countries.

This study presents the first CRBM model and its applicability to two cross-border regions.

The objective of this paper is to evaluate whether the data from consignors, logistics service providers (LSPs) and consignees contribute to the prediction of air transport shipment delays in a machine learning application.

The research database contained 2,244 air freight intercontinental shipments to 4 automotive production plants in Latin America. Different algorithm classes were tested in the knowledge discovery in databases (KDD) process: support vector machine (SVM), random forest (RF), artificial neural networks (ANN) and k-nearest neighbors (KNN).

Shipper, consignee and LSP data attribute selection achieved 86% accuracy through the RF algorithm in a cross-validation scenario after a combined class balancing procedure.

These findings expand the current literature on machine learning applied to air freight delay management, which has mostly focused on weather, airport structure, flight schedule, ground delay and congestion as explanatory attributes.

Warranty-based big data analysis has attracted a great deal of attention because of its key capabilities and role in improving product quality while minimizing costs. Information and details about particular parts (components) repair and replacement during the warranty term, usually stored in the after-sales service database, can be used to solve problems in a variety of sectors. Due to the small number of studies related to the complete analysis of parts failure patterns in the automotive industry in the literature, this paper focuses on discovering and assessing the impact of lesser-studied factors on the failure of auto parts in the warranty period from the after-sales data of an automotive manufacturer.

The interconnected method used in this study for analyzing failure patterns is formed by combining association rules (AR) mining and Bayesian networks (BNs).

This research utilized AR analysis to extract valuable information from warranty data, exploring the relationship between component failure, time and location. Additionally, BNs were employed to investigate other potential factors influencing component failure, which could not be identified using Association Rules alone. This approach provided a more comprehensive evaluation of the data and valuable insights for decision-making in relevant industries.

This study's findings are believed to be practical in achieving a better dissection and providing a comprehensive package that can be utilized to increase component quality and overcome cross-sectional solutions. The integration of these methods allowed for a wider exploration of potential factors influencing component failure, enhancing the validity and depth of the research findings.