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The contribution of the Indian Automobile industry in the economic growth of the country is significantly high. Besides catering to a large domestic market, the automobile industry in India has also captured market shares in many foreign countries successfully in the last few decades. Not only is it an important export-oriented industry of the nation but also the fourth largest exporter of automobiles in Asia. However, in the recent years (2018–2019), it has faced an unprecedented slump. This chapter captures this fact by calculating the growth of car selling for the four quarters of the period 2018–2019 across the Indian states. It primarily tries to find out whether the variation in income and tax levied on petrol and diesel has an impact on the variation in the car selling across the states for the abovementioned time period. It has been proven from our study that higher income of a state has a positive impact, whereas higher tax on petrol and diesel which varies across the states has a negative impact on car selling. Apart from this, this study then distinctively tries to find out whether there exists any neighborhood impact on growth rate of car selling and different tax rate on petrol and diesel on the basis of Moran's Index. It is witnessed that there exists a high level of spatial autocorrelation among the different states in case of growth of a car selling and tax imposition on diesel as well as on petrol. This fact necessitates some degree of regional orientation in formulating an effective policy to revive the automobile industry on the part of the Government.

The objectives of this study were to demonstrate that the high-density 7-Eleven c-stores in Taiwan benefit from economies of scale in distribution and can, therefore, leverage the logistics costs; and to decide the proper locations for the future inauguration of c-stores.

The study spatially analysed the c-stores located in Tainan, Taiwan and examines the influence of spatial configuration on c-store revenue. This study developed models to quantify the revenue and logistics costs that the 7-Eleven convenience store (c-store) chain encountered when adopting a high-density expansion strategy. The revenue models’ parameters were calibrated utilizing data collected from financial statements in 7-Eleven chains’ 2015 corporate annual reports and modelling was used to quantify the influence of agglomeration forces and the distance separating c-stores on revenue.

Positive agglomeration forces increased 7-Eleven’s company-wide sales and the average daily revenue of its individual c-stores, and decreased those of competitors. The study findings demonstrate the high-density 7-Eleven c-stores in Tainan benefit from economies of scale in distribution and can, therefore, leverage their logistics costs. The spatial analysis concluded that higher-density and higher-revenue c-stores were spatially clustered.

The study extends the use of analytical revenue and spatial models to decide the proper locations for the future inauguration of c-stores.

This article aims to analyse the spatial and temporal evolution of multidimensional poverty in Brazil's North Region and its relationship with territorial, economic and population dynamics.

A multidimensional poverty index (MPI) was calculated using the Alkire-Foster method and a spatial econometric model was estimated. The data come from population censuses conducted by the Brazilian Institute of Geography and Statistics (IBGE) for the years 1991, 2000 and 2010.

The results show a decrease in multidimensional poverty over the period analysed. However, they show this reduction occurred in a heterogeneous way in time and space, with emphasis on microregions in which, despite a reduction in the rate, the percentage of the population considered multidimensionally poor remained high during the 30 years of the study.

The quality of available data.

It is possible to point out that public policies focused on improving infrastructure in medium-sized locations tend to have two positive effects: first, making production and consumption more accessible and sustainable for local communities, given that currently the cost of transport and logistics are factors that hinder socioeconomic development; second, to reduce the pressure of demand that this population of small and medium-sized locations exerts on public services currently offered only in larger locations. Although the logic of concentrating most public services in the largest cities makes sense in terms of economic efficiency, the particularities of the northern region and the recognition of its environmental importance point to the need for incentives for more spatially distributed economic activity.

From the paper results, it is possible to think about more local public policies which are able to improve people's lifes without to damage the environment.

This is the first study on multidimensional poverty that covers the entire North region of Brazil (Amazon region) and that contemplates both the temporal and spatial dynamics of poverty.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2021-0699.

The aim of this paper is to provide a narrative review of previous research on tourism demand modelling and forecasting and potential future developments.

A narrative approach is taken in this review of the current body of knowledge.

Significant methodological advancements in tourism demand modelling and forecasting over the past two decades are identified.

The distinct characteristics of the various methods applied in the field are summarised and a research agenda for future investigations is proposed.

本文旨在对先前关于旅游需求建模和预测的研究进行叙述性回顾并对未来潜在发展进行展望。

本文采用叙述性回顾方法对当前知识体系进行了评论。

本文确认了过去二十年旅游需求建模和预测方法论方面的重要进展。

本文总结了该领域应用的各种方法的独特特征, 并对未来研究提出了建议。

El objetivo de este documento es ofrecer una revisión narrativa de la investigación previa sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros.

En esta revisión del marco actual de conocimientos sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros,se adopta un enfoque narrativo.

Se identifican avances metodológicos significativos en la modelización y previsión de la demanda turística en las dos últimas décadas.

Se resumen las características propias de los diversos métodos aplicados en este campo y se propone una agenda de investigación para futuros trabajos.

The purpose of this paper is to analyze the relationship between housing markets and new firm formation in six different industries in all 284 municipalities in Sweden.

The authors have used data from Statistics Sweden and The Swedish Agency for Economic and Regional Growth to develop a model to analyze the relationship between house prices and industry-specific new firm formation, with the interaction effect of financial infrastructure.

In the data, stable high house prices have no effect on entrepreneurship. However, a market with rising house prices has a positive effect on new firm formation, in retail, construction, business-to-business services and miscellaneous sectors, but produced no effect in either mining, agriculture and fishing or in manufacturing. The interaction between rising house prices and financial infrastructure does not change the positive effect on retail, business-to-business services and miscellaneous sectors, but within the construction industry, the positive effect on new firm formation disappears. In manufacturing, the authors observe the opposite – a positive effect, instead of no effect previously.

The contribution of this study is to provide evidence of how house prices are associated with entrepreneurship in different industries, as well as analyzing how the interaction between house prices and financial infrastructure is associated with entrepreneurship. By separating observations in time, endogeneity is controlled and a causal relationship where higher house prices is postulated, which leads to an increase in entrepreneurial activity in different industries. By using a spatial Durbin model, the authors control for spatial dependency.