Search

With the development of social media, interactive activities such as anthropomorphic communications are more accessible and popular. The country-of-origin(COO) stereotype is one of the most important factors which influences individuals' attitudes toward brands. This study aims to investigate the feasibility and validity of anthropomorphic communication via social media on COO stereotypes in international competitions. Experimental results indicate that the strategy of using anthropomorphic communication has positive effects for developing countries, but not the same for developed countries; the perceived social presence mediates the relationship between anthropomorphic communication and COO stereotypes of developing countries. However, the mediating effect is not obvious in developed countries, the influence of anthropomorphic communication is effective and feasible only when individuals' mindset is global. The theoretical model in this paper is a useful supplement to the existing achievements of anthropomorphism and COO stereotypes, it provides a reference for enterprises in developing countries to use anthropomorphic strategies accurately to reduce negative COO stereotypes and improve international competitiveness, it also gives suggestions for companies in developed countries to adopt anthropomorphic communication strategies cautiously. [ABSTRACT FROM AUTHOR]

The automotive industry serves as a crucial support system for the economies of industrialized nations in their pursuit of international market competitiveness. Despite this industry's importance, most developing countries face the challenge of acquiring a reasonable economic position at the global level in the automotive sector for various reasons. The most salient reasons include inconsistent government policies, multiple taxes, investor insecurity, political instability, and currency devaluation. Identifying risks is crucial for a new entrant in the already-established automotive industry. The researchers have used multiple (qualitative and quantitative) techniques to identify and prioritize risks in setting up manufacturing plants. The efforts to tackle these identified risks are undertaken at the domestic and government levels to smoothen the establishment of industry. The risks are first identified, in the current study, by reviewing the previous literature and conducting interviews of the various stakeholders (automotive dealers, managers, and customers). Then this study uses Monte Carlo simulation (MCS) approach and develops a risk exposure (high, medium, or low) matrix for the automotive industry of Pakistan. The findings reveal that the depreciation of local currency against the foreign exchange, oligopoly nature of competition, and low market acceptability of new entrants due to their products' image are the most critical risks the automobile industry faces. These findings will help automotive research institutes in developing national policies that specifically aim to support new players in the automotive industry, particularly in addressing high-priority hazards. The results may also provide valuable insights for new participants seeking to identify and address the key challenges in the Pakistani automotive industry before entering it. [ABSTRACT FROM AUTHOR]

The evolution of economic and innovation systems at the national scale is shaped by a complex dynamics related to the multi-layer network connecting countries to the activities in which they are proficient. Each layer represents a different domain, related to the production of knowledge and goods: scientific research, technology innovation, industrial production and trade. Nestedness, a footprint of a complex dynamics, emerges as a persistent feature across these multiple kinds of activities (i.e. network layers). We observe that, in the layers of innovation and trade, the competitiveness of countries correlates unambiguously with their diversification, while the science layer shows some peculiar features. The evolution of the scientific domain leads to an increasingly modular structure, in which the most developed countries become relatively less active in the less advanced scientific fields, where emerging countries acquire prominence. This observation is in line with a capability-based view of the evolution of economic systems, but with a slight twist. Indeed, while the accumulation of specific know-how and skills is a fundamental step towards development, resource constraints force countries to acquire competitiveness in the more complex research fields at the expense of more basic, albeit less visible (or more crowded) ones. This tendency towards a relatively specialized basket of capabilities leads to a trade-off between the need to diversify in order to evolve and the need to allocate resources efficiently. Collaborative patterns among developed countries reduce the necessity to be competitive in the less sophisticated research fields, freeing resources for the more complex ones. [ABSTRACT FROM AUTHOR]

Overfishing has severe social, economic, and environmental ramifications. Eliminating global overfishing is one of the United Nations' Sustainable Development Goals (SDGs). The SDGs require effective policy and progress monitoring. However, current indicators are issue-specific and cannot be utilized to measure fisheries efficacy holistically. This study develops a comprehensive index that takes into account the inputs, outputs, and ecological implications of fisheries. These components are then merged to form a single composite fishing index that evaluates both total fishing pressure on the ecosystem and historical patterns. The global fishing intensity grew by a factor of eleven between 1950 and 2017, and geographical differences emerged. The fishing intensity of developed countries peaked in 1997 and has since fallen due to management, but developing countries' fishing intensity has increased continuously over the whole research period, with quasi-linear growth after 1980. Africa has experienced the most rapid expansion in fishing activity and now has the highest fishing intensity. This index takes a more comprehensive and objective look at fisheries. Its worldwide spatial–temporal comparison enables the identification of similar temporal trends across countries or regions, as well as areas of uneven development and hotspot sites for targeted policy action. [ABSTRACT FROM AUTHOR]

Global Health Security Index (GHSI) categories are formulated to assess the capacity of world countries to deal with infectious disease risks. Thus, higher values of these indices were expected to translate to lower COVID-19 severity. However, it turned out to be the opposite, surprisingly suggesting that higher estimated country preparedness to epidemics may lead to higher disease mortality. To address this puzzle, we: (i) use a model-derived measure of COVID-19 severity; (ii) employ a range of statistical learning approaches, including non-parametric machine learning methods; (iii) consider the overall excess mortality, in addition to official COVID-19 fatality counts. Our results suggest that the puzzle is, to a large extent, an artifact of oversimplified data analysis and a consequence of misclassified COVID-19 deaths, combined with the higher median age of the population and earlier epidemics onset in countries with high GHSI scores. [ABSTRACT FROM AUTHOR]