Неоднородность потребителей и использование безналичных платежей в Японии в 2007–2020 гг.: модели с латентными классами

PurposeThe rise of digital transaction technology has been transformative for businesses however consumer attitudes to this technology can vary. The comparison of Australians, Chinese and Sri Lankans’ consumers salient attitudes toward payment methods at the Point-of-Sale (POS) provides businesses with insights into the factors impacting consumers' payment preference.Design/methodology/approachA qualitative methodology was employed for data collection from Australian, Chinese and Sri Lankan participants. A combination of focus groups and individual interviews were carried out with a total of 35 participants.FindingsResults indicate that factors of perceived relative advantage, perceived compatibility, perceived risk, perceived rewards, perceived situations and social influence impact consumers' payment preference at POS across all three countries, however the degree of impact varies in importance across the three countries.Practical implicationsIn the cross-cultural comparison of the consumers' payment preference, this research highlights the complex interplay of factors that shapes these payment preferences. The findings, given the growing digitization of transactions, provides banking and financial institutions with a foundational model that can be used to improve their services and business model.Originality/valuePrevious studies failed to distinguish between payment choice at the time of the transaction and payment preference which is repeated behaviour. This study is the first to compare the consumers' payment preference across Australian, Chinese and Sri Lankan consumers and responds to calls for additional research that generalises consumers' payment preferences across cultures.

Each year, many frail older people in Australia and their informal carers, are faced with the complex choice of how to pay for nursing home accommodation (through a refundable, one-off lump sum payment on entry, daily ‘rent-style’ interest payments or a combination), a choice interconnected with several other financial decisions. The payment choice often needs to be made suddenly after a health shock and within tight timeframes, and impacts an older person’s income, consumption, and long-term wealth. To explore what factors potentially bear on this complex choice, we modelled payment choices in online survey data using multinomial and fractional logistic regression. We found payment choices to be associated with an older person’s finances, family situation and health situation, supporting that individual budgets and access to liquidity constrains choice. Informal carer characteristics including educational attainment, English-speaking background, investment risk appetite and perceived stress were associated with choices, suggesting informal carers may directly or indirectly exert influence. Nursing home providers’ payment preferences were also associated with choices, suggesting potential influence due to providers’ capital financing requirements. We offer policy suggestions on reducing the complexity of payment choices, and better aligning the interests of consumers and providers.

Purpose The objective of this study is to investigate the impact of the COVID-19 pandemic on the consumer payment behavior in Italy by correlating financial literacy with digital payment awareness, examining media anxiety and financial security, and including a gender analysis. Design/methodology/approach Consumers’ attitudes toward cashless payments were investigated using an online survey conducted from November 2021 to February 2022 on a sample of 836 Italian citizens by considering the behavioral characteristics and aspects of financial literacy. Structural equation modeling (SEM) was used to test the hypotheses and to determine whether the model was invariant by gender. Findings The analysis showed that the fear of contracting COVID-19 and the level of financial literacy had a direct influence on the payment behavior of Italians, which was completely different in its weighting. Fear due to the spread of news regarding the pandemic in the media indirectly influenced consumers’ noncash attitude. The preliminary results of the gender multigroup analysis showed that cashless payment was the same in the male and female subpopulations. Originality/value This research is noteworthy because of its interconnected examination. It examined the effects of the COVID-19 pandemic on people’s payment choices, assessed their knowledge, and considered the influence of media-induced anxiety. By combining these factors, the study offered an analysis from a gender perspective, providing understanding of how financial behaviors were shaped during the pandemic.

Most research on tipping focuses on countries with high nominal tipping, such as the United States, leaving a gap in understanding tipping behavior in European countries like Germany. Moreover, the shift toward cashless transactions has reshaped consumers’ payment preferences in Germany, influencing tipping practices. This study examines payment method preferences and differences in tipping behavior across various payment methods from the perspectives of both consumers and restaurant staff in Germany. Interviews with 20 restaurant patrons and 13 staff members reveal that Germany operates as a low-nominal tipping society. Cashless payments are becoming the predominant payment method and are altering tipping expectations for both customers and restaurant employees. Additionally, the study explores the motivations and perceptions of consumers and staff regarding tipping in relation to predetermined tipping percentages. The findings provide theoretical and managerial insights, enhancing the understanding of how payment methods influence tipping behavior and contributing to knowledge on tipping norms in Germany.

BACKGROUND: Age-related changes in autonomic regulation and microcirculation may be substantially modified by urban environmental factors; however, comparative analyses of these processes in settlements with different levels of urbanization remain insufficiently studied. AIM: The work aimed to assess the effect of age on spectral parameters of heart rate variability and microcirculation among residents of cities with different levels of urbanization. METHODS: Volunteers from three age groups (group 1, 18–44 years; group 2, 45–59 years; group 3, 60–74 years) permanently residing in a large city (Nizhny Novgorod), an industrial city with a developed chemical industry (Dzerzhinsk), and a small tourist city (Semenov) were examined. Heart rate variability was analyzed using the Poly-Spectrum hardware–software system (Neurosoft, Russia). Microcirculation was assessed by laser Doppler flowmetry (LAZMA analyzer, Russia). Statistical comparisons were performed using Student’s t test with Bonferroni correction. RESULTS: With increasing age, a decrease in total spectral power of heart rate variability (p 0.05) and individual spectral components was observed. Age-related changes in the heart rate variability spectrum were universal: the greatest increase in the contribution of the very low-frequency component was recorded at the age of 45–59 years among residents of the large city (by 66%), the industrial city (by 38%), and the small city (by 29%) compared with group 1, followed by an increase in high-frequency power at the age of 60–74 years: by 3-fold in large city residents, by 1.4-fold in industrial city residents, and by 1.6-fold in small city residents compared with group 2. However, a very low-frequency component was persistently elevated only among residents of the industrial city aged 60–74 years, exceeding that in group 1 by 21% (p 0.05). In microcirculation, aging was associated with a decrease in cardiac rhythm amplitude and an increase in endothelial rhythm amplitude across all groups. In individuals aged 60–74 years living in the large city and the industrial center, a reduction in myogenic rhythm amplitude was observed, whereas in the tourist city, this parameter demonstrated an opposite trend. CONCLUSION: The type of settlement influences universal age-related changes associated with a reduction in the activity of autonomic regulatory mechanisms as a whole. The greatest strain on regulatory systems was observed in middle-aged individuals (45–59 years), with subsequent persistence in older individuals (60–74 years) residing in an industrial center with a developed chemical industry, compared not only with residents of a small tourist city but also with those of a large city. These findings are relevant for the assessment of prenosological conditions and are important for the development of preventive public health measures.

Preferences for Cash vs. Card Payments: An Analysis using German Household Scanner Data

Latent class models for capturing unobserved heterogeneity in major global causes of mortality: The cases of traffic crashes and COVID-19

Variations between major and regional Australian cities in physically active and sedentary travel behaviors

Problem definition: Loyalty programs have greatly expanded in scale and scope, and loyalty points issued by firms serve as a new form of currency alongside the traditional currency of money. In this paper, we study how consumers decide to pay with points or money for a purchase and how these decisions are affected by consumers’ points earning characteristics. Methodology/results: We develop a model of consumers’ payment choices and estimate it on proprietary loyalty program data from a major U.S. airline company using a hierarchical Bayesian framework. Our results demonstrate that mental accounting, the subjective perceived value of points, and the reference exchange rate play important roles in consumers’ payment choices. Moreover, the primary points earning source and the total earning level are jointly associated with consumers’ attitudes toward points and money: Consumers who earn many points and mostly with the focal firm tend to value points more than money, while those who earn few points or mostly through a cobranded credit card tend to value money more than points. To better understand heterogeneity in consumers’ attitudes toward points, we propose a probabilistic segmentation of consumers and identify four behavioral segments with distinctive characteristics. Through counterfactual analysis, we demonstrate how a firm can implement money and point pricing policies to optimally target and influence consumers’ payment choices. Managerial implications: It is important for firms to understand how consumers think about points and decide to pay with points or money as it affects firms’ cash flows, profitability, and consumer loyalty and engagement. We demonstrate that firms can design optimal price targeting policies by utilizing the significant level of heterogeneity in consumers’ attitudes toward points. Furthermore, our results indicate that firms that are expanding their partnership networks and offering more points earning sources should consider the impact that this would have on consumers’ mental accounting of money and points, and consequently their payment choices. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0287 .

This paper uses data from the 2019 China Household Finance Survey (CHFS) to investigate the impact of financial literacy on household allocations to financial and stock assets. It is found that increased financial literacy promotes household participation in financial markets and increases household allocation to risky financial assets, especially stock assets. Further analyses indicate that increased financial literacy promotes household participation in the financial market, and with the accumulation of investment experience and the power of the Internet, households will be biased towards investing in risky assets, which will result in a significant increase in the proportion of investment in stock assets. In addition, the higher the total household assets, the more the household can afford to take risks and thus may allocate more risky financial assets. Household size, the number of people in the labour force, household self-employment in business and owning a home are negatively associated with risky asset allocation.

The paper explores the link between managerial performance and cost efficiency of 617 Japanese general local public hospitals in 1999-2007. Treating managerial performance as unobservable heterogeneity, the paper employs a panel data stochastic cost frontier model with latent classes. Financial parameters associated with better managerial performance are found to be positively significant in explaining the probability of belonging to the more efficient latent class. The analysis of latent class membership was consistent with the conjecture that unobservable technological heterogeneity reflected in the existence of the latent classes is related to managerial performance. The findings may support the cause for raising efficiency of Japanese local public hospitals by enhancing the quality of management.

Factors associated with the follow-up of high risk infants discharged from a neonatal intensive care unit.

The purpose of this paper is to investigate the association between FinTech payments and consumer financial satisfaction with cashless payments using data from the 2017 China Household Finance Survey. This study defines computer payment and mobile terminal payment using a cell phone or pad as payments with FinTech. The results indicate that payments with FinTech are positively associated with financial satisfaction with cashless payments. Furthermore, this result holds in the eastern and central groups of China, but not in the western group, where payments with FinTech are not associated with financial satisfaction with cashless payments. Similarly, the positive association does not hold for consumers with low financial literacy. Moreover, analyses on the mediating effects imply that payments with FinTech play roles through three perceived mediators. Specifically, payments with FinTech help increase consumers’ perceived convenience and perceived popularity as well as reduce perceived risk, which eventually improves financial satisfaction with cashless payments. These findings have implications for consumer policymakers, such as improving the development of FinTech, noticing the heterogeneity in terms of location, and guiding consumers to correctly understand the risks associated with FinTech. Surrounding this issue, future studies may also explore other mediators related to psychology and expand the connotation of Fintech from payments with FinTech to lending and portfolio investments with FinTech.

The basic idea underlying latent class (LC) analysis is a very simple one: some of the parameters of a postulated statistical model differ across unobserved subgroups. These subgroups form the categories of a categorical latent variable (see entry latent variable). This basic idea has several seemingly unrelated applications, the most important of which are clustering, scaling, density estimation, and random-effects modeling. Outside social sciences, LC models are often referred to as finite mixture models. LC analysis was introduced in 1950 by Lazarsfeld, who used the technique as a tool for building typologies (or clustering) based on dichotomous observed variables. More than 20 years later, Goodman (1974) made the model applicable in practice by developing an algorithm for obtaining maximum likelihood estimates of the model parameters. He also proposed extensions for polytomous manifest variables and multiple latent variables, and did important work on the issue of model identification. During the same period, Haberman (1979) showed the connection between LC models and log-linear models for frequency tables with missing (unknown) cell counts. Many important extensions of the classical LC model have been proposed since then, such as models containing (continuous) covariates, local dependencies, ordinal variables, several latent variables, and repeated measures. A general framework for categorical data analysis with discrete latent variables was proposed by Hagenaars (1990) and extended by Vermunt (1997). While in the social sciences LC and finite mixture models are conceived primarily as tools for categorical data analysis, they can be useful in several other areas as well. One of these is density estimation, in which one makes use of the fact that a complicated density can be approximated as a finite mixture of simpler densities. LC analysis can also be used as a probabilistic cluster analysis tool for continuous observed variables, an approach that offers many advantages over traditional cluster techniques such as K-means clustering (see latent profile model). Another application area is dealing with unobserved heterogeneity, for example, in regression analysis with dependent observations (see non-parametric random-effects model).

Introduction. In large cities an assessment of the impact of environmental risk factors in addition to the levels of air pollution on the morbidity of the population and the medical and demographic situation should take into account the influence of the socio-economic living conditions of the population, both availability and quality of medical care. The purpose of the work is to conduct a comparative analysis, assess the informativeness of indicators of air quality, socio-economic living conditions of the population, the availability of medical care, and identify the priority of these factors in large industrial cities of different regions of Russia. Materials and methods. A comparative analysis of indicators of the ecological situation, socio-economic conditions of living and the availability of medical care to the population in large industrial cities for the period 2008-2018 was carried out according to official statistics. Results. The criterion for choosing cities for the analysis was the population size. Large industrial cities of four Federal districts were selected as objects of research: Central (Central Federal District), Volga (Volga Federal District), Ural (Ural Federal District) and Siberian (Siberian Federal District). The main source of anthropogenic load in the Central Federal District in 50.0% of cities included in the analysis is motor transport, in 25.0% - stationary, in 25.0% the contributions of sources are comparable; in the Volga Federal District in 100.0% of cities - mobile sources; in the Ural Federal District, 50% of cities have stationary sources and 50% have mobile sources. In the Siberian Federal District, in 62.5% of the cities included in the analysis, stationary sources make the main contribution to the anthropogenic load. In cities with a population of 0.5-1 million people, the ratio of monetary income to the subsistence level and the number of doctors per 10,000 population is higher than in cities with population of 250-500 thousand. Limitations. Limited access to quantitative data and time periods. Conclusions. The indicator of anthropogenic load per inhabitant is an informative indicator of the direct impact of atmospheric air pollution on the health of the population in large cities. The ratio of the average per capita income to the subsistence minimum most objectively characterizes the level of material well-being of the population in regions with different levels of economic development. The number of doctors per 10,000 people is an indicator of the inequality of the constituent entities of the Russian Federation in terms of the level of medical provision and the availability of medical care.