Rental Model Research Articles

Establishing a new system of affordable housing

The current housing security system plays a crucial role in improving people’s livelihood and promoting social equity and justice. However, the high eligibility criteria for affordable housing and its limited coverage have resulted in unsatisfactory outcomes of the affordable housing model. This paper introduces and analyzes the Korean Jeonse right system, and, in light of the current state of affordable housing development in China, proposes a new housing rental model. The aim is to address the core issues of the real estate market, alleviate the contradiction between “housing difficulties” and social progress, and offer suggestions for the future evolution of the housing rental market.

On-Demand, Long-Term, or Hybrid? An Economic Analysis of Optimal Rental Models on Sharing Platforms

This study examines three rental models—long-term, on-demand, and hybrid—in the sharing economy and evaluates their impacts on social welfare and consumer surplus. Our analysis reveals the significance of consumers’ setup and transaction costs in determining the optimal rental-model for platforms. We find that the relative setup cost and the relative transaction cost between owners and renters play a crucial role in shaping the equilibrium market price and optimality of the three rental models, whereas the total costs determine the equilibrium transaction volume and sustainability of the three models, with high costs posing barriers to the viability of on-demand and hybrid models. In practice, platforms can maximize consumer surplus by selecting an optimal rental model that narrows the gap in setup costs between renters and owners. Policymakers should implement favorable policies or subsidies to balance consumers’ participation incentives on both sides of the market, leading to mutually beneficial social outcomes.

Economic Viability of Business models for Photovoltaic solar generation in Brazil: Studies of cases

In the last years, worldwide, more capacity of solar energy has been added than any other type of electric power generation technology. The current expansion market is largely due to the increase in market competitiveness of photovoltaic solar energy and demand for electricity. However, the markets continue to be driven largely by government or regulatory incentives and not by innovative business. Therefore, this paper presents: (i) overview of photovoltaic systems regarding the most adopted business models in Brazil; ii) business model economic viability case study. The results presented shows that the acquisition model has the best investment indicators. For the Acquisition and Rental models, all case studies were economically viable, but in the Shared Solar Generation model the Consumer Units C1 and C2 were considered unfeasible by Levelized Cost of Energy - LCOE criterion.

A Decentralized Auction Model for Sustainable Housing Rental Market

The Internet of Things has driven the transformation of the traditional offline rental model to online rental platforms such as Zillow, Zigbang, and Lianjia. These platforms provide abundant housing options, detailed information, convenient communication, and greater price transparency. However, existing online rental platforms are still centralized and rely on third-party intermediaries for settlement, which raises concerns about the integrity of real estate data, transaction security, and price transparency. To improve the real estate leasing business, we propose leveraging the decentralized nature of blockchain technology. By eliminating intermediaries, we can ensure customer privacy and reduce transaction costs. This strategy revolves around smart contracts as a core component, automatically matching landlords and tenants based on their offers, achieving transparency, and maintaining anonymity for both parties. We introduce a novel auction system that combines the features of interactive auctions and sealed-bid auctions, enabling landlords and tenants to engage in range bidding. In this study, we developed a detailed algorithm to define how smart contracts function during the auction process. Through a cost analysis, we demonstrate the economic feasibility and provide a secure, transparent, and reliable approach for online auctions.

Outpatient surgery capacities

This paper deals with outpatient surgery, specifically with outpatient surgery capacities. Interviews were conducted to try to find out how rental models differ and how the rental amount is defined. It was found that there is no standard and that there are often completely different rent levels due to a lack of cost transparency.

Application of business model canvas to merchandising sterile supplies from a hub hospital to smaller hospitals in India

BackgroundOutsourcing and regionalization of Central Sterile Supply Department (CSSD) could mutually benefit both smaller and bigger hospitals. Larger hospitals with established CSSDs have an opportunity to extend their services to maximize the utilization of their equipment. For outsourcing the sterile supplies department to smaller hospitals, extra capital investment is not required. This study highlights the application of merchandizing sterile supplies from hub hospital with a large CSSD to smaller hospitals. MethodsA prospective observational study is conducted at a hub hospital with return on investment observations as the study tool. Business Model Canvas was used to identify spoke hospitals. Two business options, known as the processing model and the rental model, were proposed to the owners of spoke hospitals. ResultIn both models, the infrastructure of CSSD is owned by the hub hospital. In the processing model, the smaller hospital owns the instruments, and in the rental model, hub hospital supplies instruments, and spoke hospitals pay rent for the instruments. The cost of CSSD building and equipment, sterilizing cost, manpower costs, and transporting costs were considered. In the processing model, the profit to the hub hospital will be 60%, 44%, and 28% annually. In the rental model, we see diminished profit margins of 50%–35%. ConclusionThe smaller hospitals can benefit by avoiding investing in infrastructure, skilled workforce, and space. The bigger hospitals can use their vast existing infrastructure more efficiently and break-even quicker on the initial capital investment.

An Ideal of Retirement Villages Business Model in Malaysia: Analysis of case studies

There are three types of retirement villages development business models: the outright sale model, the lease for life model and the rental model. This paper aims to investigate the influence elements of chosen business models adopted in Malaysia's retirement village development. This study uses a qualitative research method through interviews with the selected developers as case studies. The prominent contemplation for developing retirement villages are sustainability, practicality, profitability and land availability. Local developers have been mindful and creative in implementing their retirement village business models.

Hukum Inseminasi Buatan dan Bayi Tabung serta Implementasinya

This paper aims to examine the In Vitro Fertilization (IVF) program from the perspective of Islamic law, and positive law in Indonesia, so that it is clear whether the practice of IVF is religious or Indonesian law. In conducting the analysis, the authors use a type of qualitative literature research with a normative approach. The results of this paper are: (1) The artificial insemination program for IVF is permitted in Islamic law, with the condition that the sperm must come from the husband himself. In vitro insemination with the Surrogate Mother's uterus rental model, there are two opinions. The first opinion states that surrogacy is prohibited because it creates a mix of lineages which are also related to mahram and inheritance. The second opinion states that Surrogate Mother is allowed for emergency reasons. (2) Implementation of IVF in Indonesia is regulated in Law Number 36 of 2009 concerning Health. The law regulates the conditions and procedures that must be met to be able to participate in the program so that babies born in the program do not violate ethics in society and religion.

Process View to Innovate the Management of the Social Housing System: A Multiple Case Study

All countries recognize the right to adequate housing for all human beings. Yet, in many countries, social housing is in a critical state: most buildings need to be restored and better services should be guaranteed. Such actions should be part of a larger plan aimed to overcome the organizational and technological backwardness of the agencies that manage the social housing system. With a not large, but old public asset, the Italian context may represent an interesting case to start investigating difficulties and problems in the management of the social housing system that, as it occurs in most Mediterranean countries, arise when the public housing rental model is adopted. In the paper, a multiple case study on five Italian regional public Agencies responsible for the social housing system is discussed. In particular, the theoretical lens of process theory and ambidextrous business process management are adopted to study the Agencies’ “problematic situation” and identify innovative solutions to address it. The paper contributes to research and practice on process innovation and digital transformation of public administrations: three important lessons are derived and discussed also taking into consideration Industry 5.0, the vision on the future of industry recently proposed by the European Commission. Finally, the adoption of process theory combined with ambidextrous Business Process Management is an underexplored research method in the field of Architecture, Engineering, Construction, and Facility Management (AEC/FM) research. The results reported in the study reaffirm the potential deriving from its adoption also in such a field.

Rental strategy for energy storage to participate in frequency regulation market

Energy storage (ES) can help the renewable energy sources to smooth their output and enhance their profits, which promotes the installation of ES. However, it is inappropriate for small-scale renewable energy communities (REC) to invest costly ES, which requests a new business model to explore the possibility to rent ES for more returns. This paper proposes an ES rental strategy for REC to participate in the frequency regulation market (FRM). Firstly, the FRM is modelled considering the regulation capacity and mileage price. Then, the rental model for REC is built considering capacity rental costs and ES using costs. The correlation of rental capacity with reserved capacity and mileage is built through rental costs and revenue in FRM. The operation method for ES is carried out to maximise the total profits of REC. Finally, the whole model is demonstrated with a REC which has 35 MW photovoltaic and 113 MW wind turbine. The results show that under different rental and market prices, the REC can effectively choose the optimal rental strategy and its profits can mostly be raised by 19.63%.

Research on behavioural differences in the processing of tenant listing information: An eye-movement experiment

Abstract This study uses eye-movement technology to validate the need for online comments to be introduced into the internet rental model and to investigate the factors influencing tenants’ behaviours in the processing of information and decision-making. It has been found that the online review system could significantly increase the rate of house-viewing decisions. Tenants’ decisions were more affected by subjective comments, which were mainly affected byregression behaviours. Gender factors have an impact on information processing, but not on decision-making. The housing type factor does not affect information processing but has a significant effect on decision-making behaviour.

Drivers and barriers to fashion rental for everyday garments: an empirical analysis of a former fashion-rental company

We analyze the business models of online business-to-consumer (B2C) fashion rental and share challenges and lessons learned from an in-depth case study of a former German fashion-rental company. The firm focused on renting everyday, rather than special occasion, clothing, thus increasing the potential sustainability impact of its offer significantly. We also examine drivers and barriers of both an everyday children’s wear and a women’s wear rental model by incorporating both retailer and consumer perspectives through business data, manager interviews, and consumer surveys with customer and target groups. All data were merged into a single, in-depth analysis of the business models. By combining the complementary viewpoints of retailer and consumers, we were able to more precisely pinpoint the locations of the difficulties in the business models. The main barriers to success were the worsening quality of the company’s inventory and its difficulty acquiring and retaining customers, due both to a lack of familiarity with the concept of fashion rental and the poorly perceived price-performance ratio of fashion rental. These issues suggest that online-fashion rental should begin by focusing on special occasion rentals with more high-end fashion options and should plan a sizeable budget for marketing to raise consumer awareness of alternatives to traditional retail models and alleviate customer concerns. If such a rental model is successful and establishes a stable customer base, everyday fashion-rental options could be explored as a supplement. The article demonstrates the importance of integrating different data sources to obtain a comprehensive understanding of why online-rental models fail or succeed.

Environmental assessment of the rental business model: a case study for formal wear

The apparel industry and above all the business model on which it relies (fast fashion) are recognized as the source of marked environmental impacts. An alternative business model such as one of those promoted by the circular economy could be the solution to improve resource productivity and value creation, without damaging the environment. The rental model, or more in general the product-as-a-service, is often linked to multiple benefits such as reduction in environmental impact, increase in competitiveness and user value. However, to be sure of the environmental sustainability of this model, it is necessary to conduct an objective assessment of its application to the context of the apparel industry. The goal of this work was to carry out an analysis of the environmental impacts related to the life cycle of formal dresses. In detail, the analysis focused on the comparison between a business model based on rental of garments and an online purchase model. The results show that by extending the life of a product, in terms of the number of uses, it is possible to limit the environmental impacts associated with the fashion sector. In fact for the case under consideration, the rental business model makes it possible to extend the number of uses of a single dress, with a consequent reduction in the environmental impacts associated with its entire life cycle.

Communicating access-based business models: Company framings of home furnishings rental

Although access-based business models such as product rental hold promise for contributing to sustainable production and consumption, their diffusion is hindered by a lack of consumer acceptance. In order for rental models to resonate with consumers, they must be designed and communicated in a way that aligns with consumers’ needs. While many studies have addressed business model design, few have looked at how rental business models are communicated to consumers. Our study addresses this gap by exploring how rental companies frame their offers to consumers, and how this aligns with consumer drivers to engage in rental previously found in literature. Through a qualitative content analysis of websites of companies in the growing sector of home furnishings rental, we find that, contrary to studies that suggest emphasising sustainability aspects, sustainability is not widely communicated. In addition, while messaging does reflect broad categories of drivers for a variety of consumer goods – including economic benefits, freedom from burdens of ownership, convenience, and novelty – home furnishings rental companies represent these drivers somewhat differently. This includes appealing to more intangible ideas such as aspiration, self-expression and homeliness, as well as citing aspects specific to home furnishings such as the literal burdens of transporting furniture when relocating. Our study raises important questions about the role of sustainability in communications and provides insights from companies actively engaged in rental that can potentially help ensure that company messaging, and in turn rental models themselves, resonate with consumers. We also contribute empirical findings on home furnishings rental, which has seen increasing engagement by practitioners but has received little consideration in academic literature.

Modelling on Car‐Sharing Serial Prediction Based on Machine Learning and Deep Learning

The car‐sharing system is a popular rental model for cars in shared use. It has become particularly attractive due to its flexibility; that is, the car can be rented and returned anywhere within one of the authorized parking slots. The main objective of this research work is to predict the car usage in parking stations and to investigate the factors that help to improve the prediction. Thus, new strategies can be designed to make more cars on the road and fewer in the parking stations. To achieve that, various machine learning models, namely vector autoregression (VAR), support vector regression (SVR), eXtreme gradient boosting (XGBoost), k‐nearest neighbors (kNN), and deep learning models specifically long short‐time memory (LSTM), gated recurrent unit (GRU), convolutional neural network (CNN), CNN‐LSTM, and multilayer perceptron (MLP), were performed on different kinds of features. These features include the past usage levels, Chongqing’s environmental conditions, and temporal information. After comparing the obtained results using different metrics, we found that CNN‐LSTM outperformed other methods to predict the future car usage. Meanwhile, the model using all the different feature categories results in the most precise prediction than any of the models using one feature category at a time

On-Demand, Long-Term, or Hybrid? An Economic Analysis of Optimal Rental Models on Sharing Platforms

On-Demand, Long-Term, or Hybrid? An Economic Analysis of Optimal Rental Models on Sharing Platforms

Exploring a Pricing Model for Urban Rental Houses from a Geographical Perspective

Models for estimating urban rental house prices in the real estate market continue to pose a challenging problem due to the insufficiency of algorithms and comprehensive perspectives. Existing rental house price models based on either the geographically weighted regression (GWR) or deep-learning methods can hardly predict very satisfactory prices, since the rental house prices involve both complicated nonlinear characteristics and spatial heterogeneity. The linear-based GWR model cannot characterize the nonlinear complexity of rental house prices, while existing deep-learning methods cannot explicitly model the spatial heterogeneity. This paper proposes a fully connected neural network–geographically weighted regression (FCNN–GWR) model that combines deep learning with GWR and can handle both of the problems above. In addition, when calculating the geographical location of a house, we propose a set of locational and neighborhood variables based on the quantities of nearby points of interests (POIs). Compared with traditional locational and neighborhood variables, the proposed “quantity-based” locational and neighborhood variables can cover more geographic objects and reflect the locational characteristics of a house from a comprehensive geographical perspective. Taking four major Chinese cities (Wuhan, Nanjing, Beijing, and Xi’an) as study areas, we compare the proposed method with other commonly used methods, and this paper presents a more precise estimation model for rental house prices. The method proposed in this paper may serve as a useful reference for individuals and enterprises in their transactions relevant to rental houses, and for the government in terms of the policies and positions of public rental housing.

Public Housing Allocation Model in the Guangdong-Hong Kong-Macao Greater Bay Area under Clustering Algorithm

In the Guangdong-Hong Kong-Macao Greater Bay Area (Bay Area), the allocation methods of public rental housing are analyzed to achieve scientific and fair housing allocation as much as possible, so as to protect the housing demand of low-income and middle-income families. The housing model in the Bay Area is analyzed firstly, and the key points of public rental housing and allocation management models are discussed comprehensively. Furthermore, a method based on rough-based fuzzy clustering (RFC) is proposed to analyze the housing demands of security groups, and a public housing allocation model is constructed based on actual demand of residents. The housing allocation plan is given and decided by the decision-making department based on the demand of the security objects and the characteristics of public housing. The simulation experiments are performed on the clustering algorithm optimized based on rough set feature selection. On the Chess data set, the optimized clustering algorithm shows an obvious improvement in clustering accuracy and recall rate compared with the traditional clustering algorithms, which are 0.76 and 0.95, respectively. The bilateral matching method based on fuzzy axiom design can fully consider the actual needs of both the supply and demand of the housing security, which is beneficial to improve the rationality and correctness of public housing allocation. The allocation method of public housing based on demand clustering analysis focuses on improving the housing security level and strives to meet the higher-level housing improvement needs of housing security objects, so as to provide security objects with more expected living conditions and improve housing allocation effect.

A Study on the Mutual Rental Model of Container Shipping Alliance Cabins based on Blockchain

As one of the main modes of capacity sharing in the shipping alliance, the essence of which is the space mutual rent transaction among members. However, under the current trading system, the sharing of capacity between shipping enterprises requires a lot of transaction costs and communication costs, cooperation efficiency is not high, and there is a certain competitive relationship between enterprises, they work for their own interests, resulting in more difficult cooperation, and blockchain consensus mechanism, intelligent contracts, distributed bookkeeping and other characteristics can solve these problems of alliance cooperation. Therefore, based on the idea of blockchain, this paper designs a model of mutual lease cooperation in shipping union cabins, gives the model and process of mutual lease transactions based on blockchain, realizes mutual trust and win-win situation among members, simulates through the combination of Hyperledger Fabric and Matlab, and verifies the applicability of blockchain to shipping alliance capacity sharing cooperation.

Research on Clothing Rental Model under Sharing Economy

In recent years, the emergence of various clothing rental platforms makes the clothing rental model has been well applied. Based on the premise of the rapid development of sharing economy, this paper discusses the necessity of clothing rental model in the boom of sharing economy. Based on the analysis of the investment scale, profit growth rate, operation mode and industry structure of the garment rental mode, this paper illustrates the problems of this mode in the supply side, transaction cost, health and safety and market positioning, and then puts forward the strategies to solve these problems.