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This study aims to investigate whether the participation in land rental markets helps to mitigate impacts by climate change on multidimensional poverty in Thailand and Vietnam.

The authors use precipitation data from the National Aeronautics and Space Administration (NASA) and self-reported shocks from the Thailand Vietnam Socio-Economic Panel (TVSEP) project to estimate climate change. Data from the TVSEP are also used to calculate a multidimensional poverty index (MPI). Fixed-effect logit panel regressions with interaction terms are implemented to analyze the above mentioned.

The results show that land rental markets are used as mitigation strategies to climate change in Thailand and Vietnam. The participation in land rental markets also reduces multidimensional poverty. However, as a mitigation strategy, land rental markets are only successful in certain circumstances.

The results show that there is potential in using land rental markets as mitigation strategies to climate change. Further research is needed to better understand which adaptation strategies, besides land rental market participation, and which combinations of different adaptation strategies are successful to mitigate negative effects induced by climate change.

The results show that there is potential in using land rental markets as mitigation strategies to climate change. Therefore, education in the participation in land rental markets and how to use them as a mitigation strategy can be a way to increase households' resilience to negative effects induced by climate change. Households make better decisions regarding their land when they are better informed on the functionality of land rental markets. Additionally, being better informed increases self-confidence to participate in land-rental markets.

Land rental markets as a mitigation strategy to climate change rarely have been studied, and if so, mainly the effect of leasing land has been studied. Additionally, the authors implement new measures of poverty – a multidimensional view on poverty which provides new insights into who are the poor and how they can be lift out of poverty.

The sharing economy has enjoyed rapid growth in recent years, and entered many traditional industries such as accommodation, transportation and lending. Although researchers in information systems and marketing have attempted to examine the impacts of the sharing economy on traditional businesses, they have not yet studied the rental housing market. Thus, this research aims to investigate the impact of the sharing economy (i.e. home-sharing) on traditional businesses (i.e. rental housing market).

The authors assemble rich data from multiple sources about the entry of a leading Chinese home-sharing platform (i.e. Xiaozhu.com) and local housing rental price index. Then, econometric models (i.e. linear panel-level data models) are employed for empirical investigation. Instrumental variables are used to account for potential endogeneity issues. Various robustness checks are adopted to establish the consistency of the findings.

Overall, the estimation results show that the entry of a home-sharing platform will decrease the local housing rental price. Moreover, this impact would be strengthened in a more developed city. Additionally, this impact would be strengthened with higher prices of new houses or second-hand houses.

First, this research is one of the first to study the impact of the sharing economy (i.e. home-sharing) on traditional markets (i.e. housing rentals). Second, it contributes to the relevant literature by documenting that the impact of a platform's entry is not uniform but contingent on city and housing market characteristics. Third, practically, the findings also offer important implications for platform operators and policy makers.

The purpose of this paper is to explore the key features of fashion rental from a business model perspective with a focus on the role played by digital platforms.

A qualitative research design was used based on multiple case studies of three Italian fashion rental enterprises.

The findings reveal the key aspects characterizing fashion rental business models and the centrality of digital platforms in value creation, configuration and capture activities. The study also found that fashion rental platforms are likely to exhibit further successful development in the future.

The academic literature on fashion rental has been mainly focussed on examining consumers' motivations and concerns, paying little attention to the enterprise's viewpoint. To date, no previous study has examined fashion rental business models from the retailer's perspective. This paper is the first to explore the key components of fashion rental business models and how digital platforms influence them from the perspective of retailers. The originality of the study is further strengthened by the unique context of analysis, namely, Italy, a leading country for global fashion.

The purpose of this paper is to investigate how the pandemic affects tenants’ response to their lease obligations. This paper commences with examining the adopted tenant selection criteria during the COVID-19 pandemic. Then, this paper statistically tests if there is a relationship between selection criteria and response on whether the pandemic has effects or not. Then, this paper investigates the specific areas of impact on tenants’ ability to adequately keep to lease agreements in the Nigerian rental market. Finally, this paper proceeds to confirm if there is a relationship between selection criteria and the aspects of tenants’ deficiencies in rental obligations because of COVID-19.

Survey data, backed with interviews, is elicited from practicing estate surveyors and valuers and licensed property managers in Lagos, the largest property market in Nigeria and sub-Sahara Africa. Policy solutions and implications were solicited from personnel at the ministry of housing and senior professionals in the property sector. Data were analyzed using descriptive statistics, factor analysis and computer-aided qualitative data analysis, Atlas.ti.

Tenant’s health status is now accorded a priority together with others. Numbers of tenants are challenged with keeping to the prompt-rent-payment rule. Other areas of slight breaches included livestock rearing, subletting, alteration and repair covenants. Except for tenant reputation and tenant family size, there was no significant relationship between tenant’s health status consideration and the COVID-19 effect on tenant non-compliance with lease obligation. Tenants’ non-compliance with tenancy obligations has a connection with the tenants’ affordability, reputation, ability to sign an undertaking and health conditions during the pandemic. This paper recommends rental housing policy review.

It is recommended that the rental policy should be reviewed to give room for rental allowance or palliatives, private rental market regulation, exploration of the national housing fund and, if possible, social housing adoption policy in Nigeria.

This paper draws policymakers’ attention to the need to prepare for the future safety net that caters to citizenry welfare in challenging times.

In this two-part case, Richard Davis and Stephen Hodgetts, co-owners of D&H Management LLC, are trying to come to terms with changes in the real estate market‐changes that have made their rental homes worth less than their mortgages and at best yielding at most a break-even cash flow. In Part A Davis and Hodgetts are weighing the following options: (1) sell all of the properties, assume a loss (walk away with nothing), and avoid the negative cash flow; (2) walk away from all of the properties, assume a loss (walk away with nothing), and avoid the negative cash flow; (3) delay paying the mortgage on some of the homes, allow these properties, if necessary, to go into foreclosure, and in the interim use the positive cash flow to shore up some of the more positive cash flow homes; (4) contact all of the lenders and try to renegotiate the mortgages so as to have lower monthly rates.

In Part B Davis proposes that he and Hodgetts go their separate ways. Davis walks away with the two properties that have mortgages in his name, while Hodgetts obtains the four properties that have mortgages in his. From Hodgettsʼ perspective this is a losing proposition since (1) he would have to take over the management of four “loser” properties rather than Davisʼs two, an ʼunfairʼ split of the liabilities; (2) he had no interest in managing properties; and (3) he and Davis would be splitting up a long-standing team.

Short-term rentals (STRs) (like Airbnb) are reshaping social behaviour, notably in gastronomy, altering how people dine while travelling. This study delves into revenue management, examining the impact of seasonality and dining options near guests’ Airbnb. Machine Learning analysis of Airbnb data suggests owners enhance revenue strategies by adjusting prices seasonally, taking nearby food amenities into account.

This study analysed 220 Airbnb establishments from Madrid, Spain, using consistent monthly price data from Seetransparent and environment variables from MapInfo GIS. The Machine Learning algorithm calculated average prices, determined seasonal prices, applied factor analysis to categorise months and used cluster analysis to identify tourism-dwelling typologies with similar seasonal behaviour, considering nearby supermarkets/restaurants by factors such as proximity and availability of food options.

The findings reveal seasonal variations in three groups, using Machine Learning to improve revenue management: Group 1 has strong autumn-winter patterns and fewer restaurants; Group 2 shows higher spring seasonality, likely catering to tourists, and has more restaurants, while Group 3 has year-round stability, fewer supermarkets and active shops, potentially affecting local restaurant dynamics. Food establishments in these groups may need to adapt their strategies accordingly to capitalise on these seasonal trends.

Current literature lacks information on how seasonality, rental housing and proximity to amenities are interconnected. The originality of this study is to fill this gap by enhancing the STR price predictive model through a Machine Learning study. By examining seasonal trends, rental housing dynamics, and the proximity of supermarkets and restaurants to STR properties, the research enhances our understanding and predictions of STR price fluctuations, particularly in relation to the availability and demand for food options.

This study aims to investigate the impact of international diversification on the value and operating efficiency of European real estate firms.

The study is conducted using a panel fixed effects regression model to estimate the relationship of international diversification with firm value and operating efficiency. International diversification is mainly measured via the negative of the Herfindahl–Hirschman Index (HHI) using property-level data. Firm value and operating efficiency are proxied by financial ratios observed annually from 2002 to 2021 at the firm level.

The results demonstrate that international diversification has a negative effect on firm value. Additionally, it lowers operating efficiency by weakening a firm's ability to generate operating earnings from its assets. By examining whether the reduction in operating efficiency is due to the rental income channel or the capital gains channel, the authors find strong statistical evidence that international diversification negatively impacts capital gains. International diversification is negatively associated with net gains from property valuations (unrealized capital gains) and net profits from property disposals (realized capital gains).

The empirical analysis is limited to Europe.

This paper extends the geographical diversification literature. While existing literature focuses on domestic diversification within the United States, this paper explores the effects of international diversification on European real estate firms. To the extent of the authors' knowledge, this is the first paper to examine the impact of geographical diversification on capital gains.

This paper aims to test two hypotheses related to the supposedly negative impact of rent control on residential mobility: the mobility of renters is, first, negatively related to how attractive their residential areas are and, second, relatively high for renters living in properties built after 2005.

This paper estimates logit and multinomial logit regressions and models household moves. The multinomial logit regressions separate between short- and long-distance moves and between moves to rentals and to owned dwellings. This paper uses the “relative income” of the tenants’ residential areas to proxy area attractiveness. This paper estimates regressions for entire Sweden and the three largest “commuting” regions and municipalities, respectively.

The full sample provides support of both hypotheses in all regressions. Hypothesis one gets stronger support for moves to other rentals than moves to owned dwellings but about equally strong support for short- and long-distance moves. Hypothesis one obtains strongest support in Gothenburg municipality while hypothesis two obtains strongest support in the Malmö region. Also, hypothesis two obtains stronger support for short-distance moves than long-distance moves and slightly stronger support for moves to owned dwellings than those to rented dwellings.

This paper does not estimate “how much” rent control affects mobility, and results cannot be used to design specific rent setting policies. Results may be sensitive to how different types of moves are defined.

Efforts to reform rent setting policies in Sweden are encouraged.

To the best of the author’s knowledge, this paper’s two hypotheses are not tested before in Sweden and can be tested without control groups.

This paper aims to explore the effects of a surge in tourism short-term rentals (STR) on housing prices in municipalities within Portugal’s two largest Metropolitan Statistical Areas.

This study applies the difference-in-differences (DiD) methodology by using a feasible generalized least squares (FGLS) estimator in a seemingly unrelated regression (SUR) equation model.

The results show that the liberalization of STR had a significant impact on housing prices in municipalities where a higher percentage of housing was transferred to tourism. This transfer led to a leftward shift in the housing supply and a consequent increase in housing prices. These price increases are much higher than those found in previous studies on the same subject. The authors also found that municipalities with more STR had low housing elasticities, which indicates that adjustments to the transfer of real estate from housing to tourism were made by increasing house prices, and not by increasing supply quantities.

The study suggests that an unforeseen consequence of allowing property owners to transfer the use of real estate from housing to other services (namely, tourism) was extreme housing price increases due to inelastic housing supply.

This is the first time that the DiD methodology has been applied in real estate markets using FGLS in a SUR equation model and the authors show that it produces more precise estimates than the baseline OLS FE. The authors also find evidence of a supply shock provoked by STR.

The purpose of this paper is to identify key aspects of business model development for sustainable apparel consumption, as actors show an increasing interest in product‒service systems. This purpose should be seen from a retailers’ perspective so as to develop sustainable solutions for long-term survival in the apparel industry when meeting consumer preferences for fashion as well as an increasing interest in consuming less. Further, this is from a perspective in an economy where sharing and circularity are potential drivers for changing consumer patterns.

The study is based on the apparel retailer Houdini Sportswear and its business model development from a traditional model of selling sportswear to a more future-oriented model where sustainability is more salient. The data for analysis were collected through interviews with employees within the studied company. The interviews have been guided by overarching themes covering relevant areas of interest for this study.

Overall, the paper shows how sustainability can be included in strategic development, from product idea, product development, production and sales/rental to repair, reuse and finally recycling. The paper also highlights potential obstacles in a developed business model with increased sustainability, including technological platforms, distribution networks for collecting and returning products and consumer consumption preferences. There are a few intertwined factors to be considered on different societal levels to achieve long-term success.

This study contributes an increased understanding of how more sustainable solutions can be included when developing business models. While the manufacture, distribution and consumption of clothes have an impact on the environment, some retailers and producers want to reduce this environmental impact. One alternative is to change the way clothes are consumed, to include more sharing and circularity.