This research conducts a comparative urban analysis of two coastal cities with analogous tourism models situated in distinct geographical regions: Balneário Camboriú in Brazil and Benidorm in Spain. The study delves into two critical urban phenomena impacting the sustainability of tourist cities, utilising social network data to gather insights into economic and urban activities (Google Places) and spatio-temporal patterns of citizen presence (Twitter). The spatial analysis explores the municipal and, to a more detailed extent, the coastal strip extending 500 m inland from the coastline, spanning the entire length of each city to their municipal boundaries. The analysis uncovers both similarities and differences between the two destinations, offering insights that could inform future development strategies aimed at fostering sustainable urban environments in these well-established coastal tourist areas.

This study simultaneously examined the linkages among environmental dynamism, three dynamic capabilities, and the competitive advantages of retail businesses, which have not been identified before. Furthermore, this study fills the significant gaps in the literature and practical guidelines for retail development through improving retailer’s dynamic capabilities in response to environmental dynamism. The study used a quantitative approach by partial least squares SEM (PLS-SEM) to examine the hypotheses. Data were collected from 304 Vietnamese retail business managers. The results show that environmental dynamism plays a significant role in fostering the improvement of retailers’ dynamic capabilities. The findings also reveal positive linkages among the three dynamic capabilities before they significantly improve retailers’ competitive advantage. These are the valuable guidelines for retailers to nurture their dynamic capabilities, including service innovation capabilities, multi-channel integration, and brand orientation for sustaining their competitive advantages.

In this paper, we explore the static and dynamic effects of oil rent on competitiveness in Saudi Arabia’s economy during the period 1970–2022. In addition, we examined the short-run, strong and long-run relationships between exports and industry, inflation, energy use (oil rents) and agriculture using the Autoregressive Distributed Lag (ARDL) approach developed. The analysis showed that government spending will contribute to enhancing the competitive environment with a difference of one year. Moreover, the industry will contribute to increasing competitiveness for a positive relationship in the long term. The results stated that there is an insignificant relationship between competitiveness, inflation, and oil rents. The analysis also shows that inflation has a negative impact with statistical significance in the short term. In addition, the error correction model (ECM) coefficient is negative and has statistical significance at 0.76 at a 1% significant level, which indicates the existence of an error correction mechanism and thus the existence of a long-term relationship between the variables.

The complex interactions of industrial Policy, structural transformation, economic growth, and competitive strategy within regional industries are examined in this research. Using a dynamic capabilities framework, the study examines the mediating roles of organizational innovation and adaptability in the link between competitiveness and macroeconomic variables. A two-way fixed effects model is used in this study to examine the influence of structural transformation (ST) on Industrial Policy (IP). Using regional data covering the years 2010 to 2022, the research undertaken in this paper explores the dynamics of the Indonesian economy by empirically assessing the consequences of structural change on industrial Policy. In order to establish a comprehensive model that clarifies the mechanisms through which industrial policies and structural shifts impact the development of dynamic capabilities, ultimately influencing competitiveness strategies, this research draws on a large amount of empirical data and integrates insights from seminal works. Our research adds to our knowledge of strategic management in regional industries by providing detailed information on how economic development and policy interventions influence businesses’ ability to adapt and gain a competitive edge. In addition to advancing scholarly discourse, this study offers business executives and politicians valuable insights for managing the intricacies of global economic processes.

This study addresses the impact of the tourism sector on poverty, poverty depth, and poverty severity in Indonesia, focusing on the micro-level dynamics in the province. Despite numerous tourism destinations, their strategic contribution to regional progress remains underexplored. The motivation stems from the need to comprehend the nuanced relationship between tourism and poverty at both the national and local levels, with specific attention to the untapped potential at the province level in Indonesia. We hypothesize that a higher tourism sector GRDP will be inversely correlated with poverty levels, and the inclusion of a Covid-19 variable will reveal a structural impact on poverty dynamics. Employing a Panel Regression Model, secondary data from the Central Statistics Agency (BPS) spanning 2011–2020 is utilized. A panel data regression equation model, including CEM, FEM, and REM, is employed to analyze the intricate relationship between tourism and poverty. The findings demonstrate a negative correlation between higher tourism sector GRDP and the number of poor people. The Covid-19 variable, considered a structural break, reveals a significant association between increased cases and elevated poverty and severity across Indonesian provinces. This study contributes a micro-level analysis of tourism’s role, emphasizing its impact at the provincial level. The findings underscore the need for strategic initiatives to harness the untapped potential of tourism in alleviating poverty and promoting regional progress.