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This paper examines the notion of intermediate inequality and its measurement. Specifically, we investigate whether the intermediateness of an intermediate measure can be preserved through repeated (affine) inequality-neutral income transformation. For all existent intermediate measures of inequality, we show that the intermediateness cannot be preserved through the transformation; each intermediate measure tends to either a relative measure or an absolute measure. This observation is then generalized to the class of unit-consistent inequality measures. An inequality measure is unit-consistent if inequality rankings by the measure are not affected by the measuring units in which incomes are expressed. We show that the unit-consistent class of intermediate measure of inequality consists of generalizations of an existent intermediate measure and, hence, the intermediateness also cannot be retained in the limit through transformations.

The purposes of this paper are to analyze the path and speed of rural transformation (RT) and explore the relationship between farmer's income and RT as well as structural transformation (ST) and typology of RT in the past four decades in China.

Based on the major indicators of RT and ST, graphic illustration is used to analyze the relationships between these indicators and farmer's income using the time-series and cross-provincial data in 1978–2017.

While China has experienced significant RT and ST, the levels and speeds of these transformations differed largely among provinces. Higher and faster RT and ST are often positively associated with the higher and faster growth of rural income. Based on this study, a general typology of rural and structural transformations and rural income is developed. The likely impacts of institutions, policies and investments (IPIs) on RT are discussed.

The authors believe that the findings of this study provide the insights on regional RT and ST and policy implications to increase farmer's income through facilitating and speeding up RT and ST with appropriate IPIs during the rural transformation.

In the actual livestreaming background, to obtain more income, some broadcasters will transform their original single role orientation into mixed one. This research study aims to conduct an empirical study on the influence of the broadcasters' role orientation transformation on the viewers' tipping behavior.

The authors collect data from Kuai, a leading online live streaming service provider in China. The dataset includes 175,701 live streaming data from 971 broadcasters in 7 months. To avoid unobservable factors, the authors adopt two difference-in-differences (DID) models to estimate the effect of two kinds of broadcaster's role orientation transformation on the broadcaster’s direct income separately. And the authors use the Heckman-type correction to solve broadcasters’ self-selected problem.

The authors evaluated that there is a U-shape relationship between the broadcasters' role orientation transformation and their direct income. The broadcasters' direct income experienced a sharp decline for a short period of time after transformation and followed by a rise after a period of adaptation. And for broadcasters with different genders and amounts of fans, the influence degree of role orientation transformation is various.

This paper provides a fresh usage of the regulatory engagement theory in the brand new information communication technology. And it also explores the boundary effect of the participating object's self-factors in the regulatory engagement theory. Besides, this paper expands the research of livestreaming into natural background. Such results also provide operable suggestions for the livestream platform, the broadcaster himself and the enterprises who want to employ some broadcasters to recommend their products.

Currently, China’s economy is in the critical phase of transforming economic development patterns and replacing old growth drivers with new ones. Whether it can successfully overcome the “middle-income trap” has become a significant issue attracting wide attention.

Driven by underlying digital technologies such as artificial intelligence, blockchain, cloud computing and big data, the fourth industrial revolution featuring the booming digital economy has provided significant opportunities for China’s economy to “overtake” and overcome the “middle-income trap”. The transformation of economic development pattern, the optimization of industrial structure, and the change of growth drivers, brought by the deep integration of digital and real economies are the keys to leaping over the “middle-income trap”.

From the supply side, the digital economy can improve the quality and efficiency of the supply side and promote the supply-side structural reform and economic growth from the following three aspects: First, promote the quality, efficiency and diversification of the supply system; second, promote networking, opening-up and synergy in the innovation system and third, promote the socialization, modularization and flexibility of production pattern. From the demand side, the digital economy can boost the new drivers of the “troika” of economic growth consisting of consumption, exports and investment by changing the market investment direction, promoting consumption upgrade and fostering export strengths. However, once these two attributes interact with each other, especially when data is combined with capital, the most adhesive factor in the market economy, a series of new social relations will then be produced based on the technical attribute, resulting in significant adjustments in social relations, involving both positive and negative externalities.

To overcome the “middle-income trap”, it is necessary to adapt to the laws of economic evolution and promote a fundamental change in economic growth drivers; boost the high-quality development of the digital economy by strengthening the support role of data in the digital economy; and accelerate digital industrialization and industrial digitalization to realize the integration of digital and real economies.

The article explores the transformations low-income women make to appropriate their housing that often goes unnoticed. The aim is to document, acknowledge and make low-income women's efforts to appropriate their housing visible. Lessons learned are assumed to inform the Ugandan low-income housing discourse on design considerations that can contribute to the provision of housing designs that are conducive to low-income women. The study confines its investigation to the housing designs provided under the governmental low-income housing projects in Uganda.

This article presents results from a case study on Masese Women Housing Project MWHP that targeted women as its main beneficiaries. Post Occupancy Evaluations POE methodology was utilised to collect data on the performance of the housing designs provided by the project and the transformations women make to increase their housing appropriateness. Open-ended interviews were carried out with women owners to investigate the transformations they apply to their houses. Results are documented through photography, sketches and measured drawings. Results are synthesised and analysed under outdoors and indoors transformations.

The study confirmed the substantial contribution low-income women make to appropriate their housing. It argues for acknowledging and including women's efforts in the Ugandan low-income housing discourse to support the provision of housing designs that are more user-friendly to them. Design considerations that are essential to attain low-income women convenience with their housing are: its capacity to accommodate women's triple roles, their potential for incremental development and their ability for segmentation into autonomous housing units to allow for their flexible, economic and functional use. The study advocates for directing efforts to the development of traditional building technologies instead of introducing improved but alien ones as an alternative that is more favourable to women.

This paper breaks through the limitations of the research on bullwhip effect in the traditional supply chain, extends the research perspective to digital supply chain and discusses the weakening effect of digital supply chain on bullwhip effect by comparing the overall performance of the two.

This paper starts with the weakening mechanism of supply chain digitization on bullwhip effect, builds bullwhip effect models of traditional supply chain and digital supply chain, respectively, simulates the influence of supply chain digitization transformation on bullwhip effect by using Matlab software and analyzes the causes of bullwhip effect in supply chain led by T company and the digitization process.

Firstly, digitization can reduce bullwhip effect in multi-level supply chain by reducing information feedback deviation. Second, digital transformation is conducive to improving the overall performance of the supply chain. Third, government incentives can promote the digital transformation of supply chain and inhibit bullwhip effect.

Although the study considers the heterogeneous subject -- the government's incentive effect on digital transformation and information sharing – it does not include the influence of the end node in the supply chain, that is the consumer. In addition, this paper only analyzes and discusses the bullwhip effect on the amplification of demand, without considering the situation that the market contraction will lead to the reduction of demand.

This paper considers the distortion degree and delay degree of information feedback, carries out quantitative analysis of bullwhip effect, builds the bullwhip effect model of traditional supply chain and digital supply chain, uses Matlab software to analyze the difference of the influence of supply chain digital transformation on bullwhip effect suppression and puts forward the corresponding control strategy.

The research shows that digital transformation can reduce the bullwhip effect in multi-layer supply chain by reducing the information feedback deviation, which is conducive to improving the overall supply chain performance, and government support can accelerate the digital transformation of supply chain to a certain extent.

First, break through the limitations of traditional supply chain research, expand the research perspective to digital supply chain and discuss the weakening effect of digital supply chain on bullwhip effect by comparing the overall performance of the two. Second, quantify the bullwhip effect through information feedback bias and provide an analysis method for the weakening of the bullwhip effect. Third, the driving role of the government in the digital transformation of the supply chain is considered in the study, so that the model is more close to the actual situation of enterprise operation.

We investigate the relationship between the notion of progressive taxation and inequality reduction under a general version of the concept of inequality equivalence. We consider a two-parameter formalization of the concept of inequality equivalence that both includes, as special cases, the intermediate inequality equivalence and the path-independent/unit-consistent inequality equivalence. Both criteria could range from relative to absolute inequality views as the parameters in the formulation change. For the path-independent/unit-consistent inequality equivalence the condition of nondecreasing average tax rate is necessary and sufficient to guarantee the inequality-reducing effect of taxation for all the inequality views in between the relative and the absolute.

Purpose: Most of the characterizations of inequality or poverty indices assume some invariance condition, be that scale, translation, or intermediate, which imposes value judgments on the measurement. In the unidimensional approach, Zheng (2007a, 2007b) suggests replacing all these properties with the unit-consistency axiom, which requires that the inequality or poverty rankings, rather than their cardinal values, are not altered when income is measured in different monetary units. The aim of this paper is to introduce a multidimensional generalization of this axiom and characterize classes of multidimensional inequality and poverty measures that are unit consistent.

Design/methodology/approach: Zheng (2007a, 2007b) characterizes families of inequality and poverty measures that fulfil the unit-consistency axiom. Tsui (1999, 2002), in turn, derives families of the multidimensional relative inequality and poverty measures. Both of these contributions are the background taken to achieve our characterization results.

Findings: This paper merges these two generalizations to identify the canonical forms of all the multidimensional subgroup- and unit-consistent inequality and poverty measures. The inequality families we derive are generalizations of both the Zheng and Tsui inequality families. The poverty indices presented are generalizations of Tsui's relative poverty families as well as the families identified by Zheng.

Originality/value: The inequality and poverty families characterized in this paper are unit and subgroup consistent, both of them being appropriate requirements in empirical applications in which inequality or poverty in a population split into groups is measured. Then, in empirical applications, it makes sense to choose measures from the families we derive.

This paper studies the dynamic effects of selected macroeconomic factors on the performance of the housing market in Kenya using Autoregressive Distributed Lag (ARDL) Models. This study aims to explain the dynamic effects of the macroeconomic factors on the three indicators of the housing market performance: housing prices growth, sales index and rent index.

This study used ARDL Models on time series data from 1975 to 2020 of the selected macroeconomic factors sourced from Kenya National Bureau of Statistics, Central Bank of Kenya and Hass Consult Limited.

The results indicate that household income, gross domestic product (GDP), inflation rates and exchange rates have both short-run and long-run effects on housing prices while interest rates, diaspora remittance, construction output and urban population have no significant effects on housing prices both in the short and long run. However, only household income, interest rates, private capital inflows and exchange rates have a significant effect on housing sales both in the short and long run. Furthermore, household income, GDP, interest rates and exchange rates significantly affect housing rental growth in the short and long run. The findings are key for policymaking, especially at the appraisal stages of real estate investments by the developers.

The authors recommend the use of both the traditional hedonic models in conjunction with the dynamic models during real estate project appraisals as this would ensure that developers only invest in the right projects in the right economic situations.

The imbalance between housing demand and supply has prompted an investigation into the role of macroeconomic variables on the housing market in Kenya. Although the effects of the variables have been documented, there is a need to document the short-run and long-term effects of the factors to precisely understand the behavior of the housing market as a way of shielding developers from economic losses.

The housing market in Kenya continues to experience an excessive imbalance between supply and demand. This imbalance renders the housing market volatile, and stakeholders lose repeatedly. The purpose of the study was to forecast housing prices (HPs) in Kenya using simple and complex regression models to assess the best model for projecting the HPs in Kenya.

The study used time series data from 1975 to 2020 of the selected macroeconomic factors sourced from Kenya National Bureau of Statistics, Central Bank of Kenya and Hass Consult Limited. Linear regression, multiple regression, autoregressive integrated moving average (ARIMA) and autoregressive distributed lag (ARDL) models regression techniques were used to model HPs.

The study concludes that the performance of the housing market is very sensitive to changes in the economic indicators, and therefore, the key players in the housing market should consider the performance of the economy during the project feasibility studies and appraisals. From the results, it can be deduced that complex models outperform simple models in forecasting HPs in Kenya. The vector autoregressive (VAR) model performs the best in forecasting HPs considering its lowest root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and bias proportion coefficient. ARIMA models perform dismally in forecasting HPs, and therefore, we conclude that HP is not a self-projecting variable.

A model for projecting HPs could be a game changer if applied during the project appraisal stage by the developers and project managers. The study thoroughly compared the various regression models to ascertain the best model for forecasting the prices and revealed that complex models perform better than simple models in forecasting HPs. The study recommends a VAR model in forecasting HPs considering its lowest RMSE, MAE, MAPE and bias proportion coefficient compared to other models. The model, if used in collaboration with the already existing hedonic models, will ensure that the investments in the housing markets are well-informed, and hence, a reduction in economic losses arising from poor market forecasting techniques. However, these study findings are only applicable to the commercial housing market i.e. houses for sale and rent.

While more research has been done on HP projections, this study was based on a comparison of simple and complex regression models of projecting HPs. A total of five models were compared in the study: the simple regression model, multiple regression model, ARIMA model, ARDL model and VAR model. The findings reveal that complex models outperform simple models in projecting HPs. Nonetheless, the study also used nine macroeconomic indicators in the model-building process. Granger causality test reveals that only household income (HHI), gross domestic product, interest rate, exchange rates (EXCR) and private capital inflows have a significant effect on the changes in HPs. Nonetheless, the study adds two little-known indicators in the projection of HPs, which are the EXCR and HHI.