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This paper reviews the role of two significant smart technologies, artificial intelligence (AI) and blockchain technology (BT) in achieving sustainable tourism success. Such changes will maintain consistent tourism growth in the Middle East and North Africa (MENA) region by improving environmental, social and economic sustainability.

This study uses a qualitative approach focusing on AI and blockchain-based adaptations towards sustainability in technology-driven platforms, particularly in the tourism sector. However, this study is conceptualized with Day's (1989) IMRAD (introduction, methods, results and discussion) framework and Hall's (2012) suggestions. This reinforced the structure of this article by the preferred reporting items for systematic reviews and meta-analyses (PRISMA) concept. In addition, the entire study proceeds by way of accentuating the research question.

The potential of these technologies (AI and blockchain) can internalize a win-win situation for economic prosperity and sustainable conservation of environmental resources. Even though, apathy among potential tourists (of traditional mass tourism) can be revived under sustainable tourism in the region through smart technology. Replacing traditional practices and policies with innovative technologies can reduce the adverse effect on environmental and cultural resources.

This research justifies the potential for AI and blockchain to balance economy-oriented tourism and sustainability-prone technologically advanced tourism as a caustic issue for the MENA region. Indeed, this study has revitalized and transformed the less eventful margins of leading cultural-heritage-based tourism into sustainable profitability with concerns over diversity, socio-economic conditions, economic recession and burgeoning geopolitical instability.

The purpose of this study is to identify the emergence of apparel brands in Bangladesh: their timing, order and the reasons behind the patterns. This study also examined whether these evolution patterns followed the same path in Korea and India.

By employing secondary research method, this study gathered and analyzed data from companies, trade organizations, news media and academic articles to determine the socioeconomic backgrounds and underlying dynamics that propelled the evolution patterns. Following Jin et al.'s (2013) approach, we analyzed three types of apparel brands (international, national and private) in Bangladesh.

The findings indicated that in contrast with Korea and India, in Bangladesh (a) the emergence of international brands occurred after the national brands' appearance in the More Advanced Production of Fabric and Apparel stage, (b) national brands also emerged at the same stage and earlier than the international brands developed, and (c) internationalization of national brands and emergence of private brands were not observed. The differences in the emergent timing and order were explained by socioeconomic and cultural aspects, along with industry life cycle perspectives.

Findings indicate that the Bangladeshi market is dominated by national apparel brands. Therefore, international brands are advised to consider the business strategies of local competitors and develop their own pricing and merchandising strategies to maintain their supremacy as premium brands.

This study addressed apparel brand evolution patterns in a lower middle-income country. The results revealed some unique aspects. Unlike in other developing countries, national brand development in Bangladesh was initiated by entrepreneurs.

Khan Jahan Ali (KJA) Bridge was constructed to promote industrial and commercial activity and improve economic and employment activity for local people. This study assessed the post-socioeconomic and environmental impacts of KJA Bridge on the inhabitants living adjacent to 2 Km from the bridge. As there is a slum adjacent to the bridge, the bridge has impacted much on the improvement of the social economic condition and lifestyle of the slum people.

The study approached a questionnaire-based field survey data collection through interviewing the people in the surrounding areas. To assess the environmental impacts, land cover change (LCC), carbon emissions and land surface temperature (LST) data were derived from Landsat images and processed in geospatial environment.

The study suggests that after bridge construction, 84% people have new jobs and about 87% people's income level has been increased. As a tourist spot, the bridge served employment opportunities for the 12% of the inhabitants. About 83% house structures have been improved, where the percentages of pucca and semi-pucca houses increased by 11% and 23%, respectively. The frequency of school-going children and literacy rate also increased. Despite all the socioeconomic development, 7.48% agricultural, 9.75% vegetation, 1.74% waterbodies were declined. Net carbon emissions increased to 13,432.39 tons from 3,323.46 tons; average LST increased from 25.750 to 32.550°C after the bridge construction.

This study focused on descriptive statistical analysis and portrayed the impact of the bridge on social, economic and environment from a micro point of view.