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The study aims to address a critical gap in existing healthcare payment schemes and care service pricing by recognizing the influential role of patients' decisions on self-management efforts. These decisions not only impact health outcomes but also shape the demand for care, subsequently influencing care costs. Despite the significance of this interplay, current payment schemes often overlook these dynamics. The research focuses on investigating the implications of a novel behavior-based payment scheme, designed to align incentives and establish a direct connection between patients' decisions and care costs. The primary objective is to comprehensively understand whether and how this innovative payment scheme structure influences key stakeholders, including patients, care providers, insurers and overall social welfare.

In this paper, we propose a game-theoretical model to incorporate the performance of self-management with the demand for healthcare service, compare the patient's effort decision for self-management and provider's price decision for healthcare service under a behavior-based scheme with that under two implemented widely payment schemes, that is, co-payment scheme and co-insurance scheme.

Our findings confirm that the behavior-based scheme incentives patient self-management more than current schemes while reducing their possibility of seeking healthcare service, which indirectly induces the provider to lower the price of the service. The stakeholders' utility under various payment schemes is sensitive to the cost of treatment and the perceived health utility of patients. Especially, patient health awareness is not always benefited provider profit, as it motivates patient self-management while diminishing the demand for care.

We provide a novel framework for characterizing behavior-based payment schemes. Our results confirm the need for modification of the current payment scheme to incentivize patient self-management.

The purpose of this paper is to facilitate understanding of how to mitigate the privacy concerns of users who have experienced privacy invasions.

Drawing on the communication privacy management theory, the authors developed a model suggesting that privacy concerns form through a cognitive process involving threat-coping appraisals, institutional privacy assurances and privacy experiences. The model was tested using data from an empirical survey with 913 randomly selected social media users.

Privacy concerns are jointly determined by perceived privacy risks and privacy self-efficacy. The perceived effectiveness of institutional privacy assurances in terms of established privacy policies and privacy protection technology influences the perceptions of privacy risks and privacy self-efficacy. More specifically, privacy invasion experiences are negatively associated with the perceived effectiveness of institutional privacy assurances.

Privacy concerns are conceptualized as general concerns that reflect an individual’s worry about the possible loss of private information. The specific types of private information were not differentiated.

This paper is among the first to clarify the specific mechanisms through which privacy invasion experiences influence privacy concerns. Privacy concerns have long been viewed as resulting from individual actions. The study contributes to literature by linking privacy concerns with institutional privacy practice.

The purpose of this paper is to propose a new velocity prediction navigation algorithm to develop a conflict-free path for robots in dynamic crowded environments. The algorithm BP-prediction and reciprocal velocity obstacle (PRVO) combines the BP neural network for velocity PRVO to accomplish dynamic collision avoidance.

This presented method exhibits innovation by anticipating ahead velocities using BP neural networks to reconstruct the velocity obstacle region; determining the optimized velocity corresponding to the robot’s scalable radius range from the error generated by the non-holonomic robot tracking the desired trajectory; and considering acceleration constraints, determining the set of multi-step reachable velocities of non-holonomic robot in the space of velocity variations.

The method is validated using three commonly used metrics of collision rate, travel time and average distance in a comparison between simulation experiments including multiple differential drive robots and physical experiments using the Turtkebot3 robot. The experimental results show that our method outperforms other RVO extension methods on the three metrics.

In this paper, the authors propose navigation algorithms capable of adaptively selecting the optimal speed for a multi-robot system to avoid robot collisions during dynamic crowded interactions.

The purpose of this paper is to present a new method and model for constructing a new decision-making paradigm of Medicare, which can not only satisfy the needs of the sick people but also reduce the possibility of people slipping back to poverty due to diseases under the policy of Targeted Poverty Alleviation (TPA) of China.

This paper uses the traditional supply chain theory to analyze the Medicare of impoverished people with the policy of TPA of China and transforms it into a multi-layer supply chain optimization decision-making problem. First, a nonlinear integer programming model for poor people’s Medicare decision with opportunity constraints is constructed. To facilitate the solution of the optimal decision scheme, the abovementioned model is transformed into a linear integer programming model with opportunity constraints by using the Newsvendor model for reference. Meanwhile, the scope of the inventory model is discussed, for it can be combined with the construction of the medical insurance system better. Second, the theoretical model is applied to the practical problem. Finally, based on the results of the theoretical model applying the practical problem, we give further improvement and modification of the theoretical model applies it to the actual situation further.

This paper presents a theoretical model about determine the optimal the inventory, under the framework of traditional supply chain decision-making, for it can be combined with the construction of the medical insurance system better. The theoretical model is applied to the practical problem of the fight against poverty in XX County, China. By using the actual data and MATLAB, optimal decision scheme is obtained.

There are two aspects of value. On the one hand, this paper provides a new way to construct a Medicare system of impoverished people with TPA of China. On the other hand, this paper tries making a new way to handle the storage of medicines and related medical devices at basic standard clinics decision-making problems based on above mentioned Medicare system.

Faced with the challenges of rural population decline, combined with the widespread expansion of homesteads in rural areas, local Chinese governments hope to strictly control and minimize rural housing land. Accurately decomposing the process of rural housing expansion and revealing its driving factors will be helpful for land-use regulation by the government.

In this study, an unusually rich dataset of rural housing registration from Pudong New Area in Shanghai is employed. The study aimed to decompose the fragmented accumulation process and its expansion determinants on rural housing assets. The dataset covers all samples of rural households and housing plots at 72 surveyed villages in six towns.

Housing offers profitable capital and earning assets to villagers at the urban fringe, so they have a powerful incentive to build and expand more. The results of this analysis showed that the expansion of rural housing is largely due to the haphazard construction of auxiliary rooms by villagers, especially on plots of arable land that are adjacent to their houses that have been stealthily converted into auxiliary rooms and sheds. Low costs and weak penalties have led to an increase in rent-seeking expansions to rural houses. Houses with the smaller initial areas, families with more laborers and household heads, and the proximity of villages to downtown with convenient living services were the main driving factors for expanding houses. A concerted effort is needed to control the disorganized and unlicensed expansion of housing. This effort should include formulating areas for free use by villagers, high taxes on overused areas, serious penalties for unlicensed housing expansion and effective land-use planning.

An understanding of the expansion status and control measures related to rural houses in Shanghai provides an important reference that can help to guide the formulation of rural housing policies, and the sustainable development of cities worldwide. Of course, this study cannot generalize about housing distribution and expansion status worldwide based on the study area in China, because China's land tenure policies are unique. But land registry data exists that makes research like this feasible. There is a need to carefully examine the detailed housing distribution in each country before it can be decided on how best to address the disorderly increase in rural housing stock, and promote the reduction of rural residential expansion.

First, the process of rural housing expansion by using an unique dataset which covers ten thousands of samples is revealed. Second, the results have policy implications for reducing the amount of idle and inefficiently rural homestead. The focus is on rural housing growth and its driving factors in Shanghai, and the villagers' motivations for housing expansion are explored.

The Indian automotive industry was witnessing a transition from conventional vehicles to greener battery-operated electric vehicles (EVs). However, the acceptance of these EVs was still muted and brought significant challenges for the industry. Literature regarding the adoption of EVs was scarce in the Indian context. It was thus imperative to explore and comprehend the distinct perceptions of industry managers and consumers regarding the adoption of EVs in India. The purpose of this study is to comprehensively analyze the entire Indian EVs ecosystem to address this research gap.

The authors carried out an empirical investigation starting with a structured literature review to identify the researchable gaps. Subsequently, the authors conducted semi-structured open-ended interviews with 38 experts including automotive industry experts and EV consumers. The authors further performed a thematic content analysis of the expert interview responses to document critical insights regarding the adoption of EVs.

The authors identified 11 key factors influencing the adoption of EVs in this study. The vital considerations regarding the availability of charging technologies, its associated selection dilemma, emerging business models and public policy support were presented and discussed. Market penetration of EVs was found to be influenced mostly by the choice of charging technology. Further, the switching intention of consumers was deliberated upon to highlight the specific technological and psychological preferences of consumers. The accessibility of charging stations emerged as the most influential factor. The research findings indicated that harmony among stakeholders was missing in the Indian EVs ecosystem. Instead, there were discrete efforts by organizations. The EVs ecosystem required collaboration for improved adoption of the EVs. Further, the necessity to rectify the chaotic charging infrastructure in the country was highlighted as a major pain point for customers to adopt EV.

This study theoretically contributed to push–pull–mooring (PPM) framework for understanding the adoption of EVs in India. This enabled the authors to extensively analyze consumers’ psychological and technological considerations regarding their switching intention toward EVs.

The findings of this study would help managers in decision-making toward the establishment of charging infrastructure involving multiple considerations such as the accessibility of charging, multi-dimensional competence at charging stations and servicing capabilities. Managers could also use the insights from this study to secure supportive recommendations for improving the overall EV infrastructure. The results of this study would benefit policymakers to set strategic directions through an integrated view of the entire EVs ecosystem involving management of bus and taxi fleets, two-wheelers and three-wheelers and such others.

Generally, in extant research, either firm managers’ or customers’ perspectives are considered separately. This study deliberated upon the PPM framework and switching intention accommodating both the industry and consumers’ perspectives. To the best of the authors’ knowledge, this was, thus, one of the first research articles which integrated insights from both the industry and consumers. This established the PPM framework for understanding the adoption of EVs. Further, it helped in comprehending the specific technological and psychological preferences of consumers regarding switching intention toward EVs.