Cryptocurrencies and Cagan’s model of hyperinflation

The drivers of the prices of Bitcoin and Ethereum are studied within a framework based on Cagan’s model of hyperinflation. In the model, the prices of the cryptocurrencies are driven by stochastic adoption and velocity shocks as well as endogenous expectations of future prices. The model is estimated with data for prices, transaction volumes, and money supplies. A majority of price fluctuations in both currencies can be attributed to shocks in adoption, velocity shocks are much less important. The money demand sensitivity to expected price changes is estimated to be larger for Bitcoin than for Ethereum, and both have higher sensitivity than fiat currencies during episodes of hyperinflation.     

The impact of reverse logistics process coordination on third party relationship quality: A moderated mediation model for multichannel retailers in the fashion industry

Multichannel retailing is a widely adopted strategy in the fashion industry. Companies in this industry find it a source of competitive advantage to invest in reverse logistics infrastructure. However, limited empirical studies investigate the enablers of the relationship quality between the retailers and their reverse logistics service providers. This study quantifies the impact of reverse logistics process coordination between retailers and logistics service providers on relationship quality. Moreover, it tests the mediating role of reverse logistics service quality and the moderating role of conflict frequency in this relationship. Data were collected through a survey using a purposive sample of 241 retail store managers from the fashion retail industry of Pakistan. For this purpose, a self-administered questionnaire was developed using a five-point Likert Scale to gauge the responses. Conditional process analysis was used to evaluate the moderated mediation model. The findings showed a significant positive impact of reverse logistics process coordination on the relationship quality with a logistics service provider, a significant positive mediation effect of reverse logistics service quality, and a significant moderation effect of conflict frequency on the indirect relationship. However, conflict frequency, contrary to the hypothesis in the study, strengthened the indirect relationship. Furthermore, the moderation effect of conflict frequency on the direct relationship was insignificant. This study will help managers better understand the best practices leading to effective management of reverse logistics processes, particularly product returns.     

Exploring the factors that drive consumers to use contactless delivery services in the context of the continued COVID-19 pandemic

The spread of the COVID-19 pandemic has resulted in the launch of contactless delivery services. This research integrates resource matching, service quality evaluation, and perceived value theories to explore the factors that promote the use contactless delivery services. The data was obtained through questionnaire surveys, and research hypotheses were verified through the structural equation modelling approach. With the exception of convenience, the results show that privacy, reliability, security, and flexibility have a significantly positive effect on consumers' intention to use “contactless” delivery services through consumers' perceived value. This study contributes to the literature by introducing theoretical frameworks from various paradigms and enriches the academic research on existing theoretical structure models. It also helps optimize resource allocation and realize the social environment related to coexisting with the COVID-19 pandemic.     

Advertisement policy for dual-channel within emissions-controlled flexible production system

Nowadays, industrial firms are very much careful to build a green environment by reducing carbon emissions. The government imposes some rules and regulations to provide a better eco-friendly environment. In this study, the cap-and-trade mechanism has been considered in a production model to control the carbon emissions rate. The manufacturers invest in advanced green technology to reduce per unit emissions. As online and offline selling is crucial to any industry for increasing customer demand, the manufacturers sell their products by dual-channel and advertise their products by online channel to make more popular of their products. Keeping these in mind, a sustainable flexible production model with single-type substitutable product production is considered here by imposing a cap-and-tax policy, investing in green technology, and advertising for products. This model is divided into two cases: with and without investment in green technology. The demand of each manufacturer depends upon an online selling price, an offline selling price, and an online advertisement of the product. A classical optimization technique helps to get the optimum strategies for the online selling price, offline selling price, advertisement investment, green technology, cycle time, and production rate. From the numerical study, it is proved that the industry gets 6.97% more profit in the case of green technology investment and the proposed study gives 5.74% more profit than the traditional production system. Sensitivity analysis and managerial insights are performed.     

智慧居家养老服务协同供给的优化路径研究——以广西钦州市智慧居家养老项目的实践经验为例

智慧居家养老服务的协同供给可以形成社会联动效应，降低公共服务成本。运用公共服务协同供给分析框架，通过交叉分类方法从协同主体的利益与目标两个变量的耦合性出发分析广西钦州市智慧居家养老项目中养老服务主体间不同种类的协同关系，可以从加强政府领导、形成合作联盟、建立市场标准、创新扶持政策4个方面完善政府、企业、社会组织之间不同类型的协同供给，实现社会资源的高效利用以及向智慧居家养老服务的发展和转变。     

A fast and scalable ensemble of global models with long memory and data partitioning for the M5 forecasting competition

This work presents key insights on the model development strategies used in our cross-learning-based retail demand forecast framework. The proposed framework outperforms state-of-the-art univariate models in the time series forecasting literature. It has achieved 17th position in the accuracy track of the M5 forecasting competition, which is among the top 1% of solutions.     

Chinese relationship management: a qualitative study of banking in New Zealand

This study investigates the relational factors and motivations of Chinese migrant consumers towards financial service providers in New Zealand. Using convergent interviews, a deeper understanding is developed of immigrants’ relational behaviour with service providers. These relationships with service providers are significantly influenced by traditional Chinese values and guanxi and relational embeddedness plays an important role in how they are developed. The research contributes a better understanding of the interplay between Eastern and Western cultures in service relationships among immigrant groups. A general theory of the Chinese perspective of customer relationship management is developed. The implications for how marketing practitioners manage their relationships with migrant customers are explored.     

The influence of hospitable design and service on patient responses

ABSTRACT

A study of 216 respondents examined a medical center environment’s influence on patient responses. A stimulus–organism–response (S-O-R) model was adapted to the theory that more hospitable healthcare servicescape elements will affect patients’ overall satisfaction with healthcare experience, loyalty intentions, and willingness to pay out-of-pocket expenses for healthcare services. Servicescape elements included atmospherics of the healthcare environment, service delivery by healthcare staff, physical design of the healthcare environment, and wayfinding. Results of structural equation modeling confirmed that the four servicescape elements – had a significant impact on patients’ overall satisfaction with the healthcare experience. Furthermore, overall satisfaction with the healthcare experience predicted patients’ loyalty intentions and willingness to pay out-of-pocket expenses for healthcare services. The study makes a significant contribution to the empirical modeling of patients’ behavioral responses to hospitable healthcare environments.     

Forecasting turning points in tourism growth

Tourism demand exhibits growth cycles, and it is important to forecast turning points in these growth cycles to minimise risks to destination management. This study estimates logistic models of Hong Kong tourism demand, which are then used to generate both short- and long-term forecasts of tourism growth. The performance of the models is evaluated using the quadratic probability score and hit rates. The results show that the ways in which this information is used are crucial to the models’ predictive power. Further, we investigate whether combining probability forecasts can improve predictive accuracy, and find that combination approaches, especially nonlinear combination approaches, are sensitive to the quality of forecasts in the pool. In addition, model screening can improve forecasting performance.