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This study proposes a novel measure for management’s horizon (short-termism or myopia vs long-termism or hyperopia) derived from easily obtainable firm-level accounting and stock market performance data. The authors use the measure to explore the impact of managements’ horizon on firms’ investment efficiency.

The authors rely on two commonly used but uncorrelated measures of management performance: accounting performance (return on capital employed, ROCE) and stock market performance (average abnormal return, AAR). The authors combine these measures to develop a multidimensional framework for performance, which classifies firms into four groups: efficient (high accounting and high market performance), poor (low accounting and low market performance), myopic (high accounting and low market performance) and hyperopic (low accounting and high market performance). The authors validate this framework and deploy it to explore the relationship between horizon and firms’ investment efficiency.

In validation tests, the authors show that management myopia (hyperopia) explains firms’ decision to cut (grow) research and development investments. Further, as expected, myopic (hyperopic) firms are associated with significantly more (less) accrual and real earnings management. The empirical tests on the link between horizon and investment efficiency suggest that myopic managers cut new investments while their hyperopic counterparts grow the same. Ultimately, the authors find that myopia (hyperopia) exacerbates(mitigates) the over-investment of free cash flow problem.

The authors introduce a framework for assessing management’s horizon using easily obtainable measures of performance. The framework explains inconsistencies in prior empirical research using different measures of performance (accounting versus market). The authors demonstrate its utility by showing that the measure explains decisions around research and development investment, earnings management and firm investments.

Digital transformation (DT) has great potential to improve operations and stimulate business growth. It has attracted widespread attention from businesses around the world. However, firm performance in DT implementation (DTI) cannot be neglected. This study examines the benefits and costs of DT and its effects on operations and financial performance of DT.

Based on the financial report data from S&P 500 firms, we measure the financial performance, productivity and market value of DTI with a baseline in 2020. In addition, we collect secondary data to construct linear regression models for three dummy variables, including DT adopters, first movers and better performers.

Empirical results demonstrate that digitally transformed firms are positively correlated with business performance, while the performance among first movers has a partially positive impact. DT has also had a significant impact on long-term performance as shown by our long-term observations. Empirical findings indicate that DT has varying impacts on organizational performance in different dimensions and provides DT target-setting guidance to enterprises.

There are no studies so far that could proffer certain evidence to reveal the influence of DTI on firm performance. Such evidence is necessary for managers to convince their investors and stakeholders to believe that DTI can create new revenue for enterprises.

The aim of this study is to analyze which socioeconomic factors (economic, demographic, and political) most commonly affect the social expenditure of the European Union (EU) and Organization for Economic Co-operation and Development (OECD) countries.

A panel data fixed-effects model is employed for 34 OECD and 23 EU countries between 2000 and 2020.

Results indicate that, in all country groups, economic factors have the most significant influence on social expenditures, with income being the primary determinant, particularly in EU countries. The negative impacts of unemployment and inflation underscore the importance of counter-cyclical measures adopted by countries to maintain stability in their social expenditures. The most influential demographic factor is found as the old-age-dependency ratio. While the rule of law affects social expenditure positively, government effectiveness and female labor force participation affect it negatively. The positive effect of Konjunkturforschungsstelle (KOF) indexes shows the globalization effect, which can be attributable to the compensation hypothesis.

Governments enforce inclusive and sustainable policies to boost economic activities and GDP, thus combating inflation and unemployment and regulating the labor market and socioeconomic problems about aging populations and women’s economic participation to control social expenditures. The rule of law and institutional quality will also boost economic growth.

This study focuses on the effects of social expenditures in a broader view within the framework of the three main factors (economic, demographic, political) and attempts to determine the key factors that account for the differences in social expenditure between the OECD and EU countries.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0384

The main purpose of this paper is to examine the role of population aging in determining the health care expenditure (HCE) in India over the period 1981 to 2018.

While establishing the linkage between population aging and HCE, the study has used economic growth, urbanization and CO2 emissions as control variables and used the autoregressive distributed lag (ARDL) approach to cointegration and VECM based Granger causality approach to estimate both the long-run and short-run relationships among the variables.

The results of the ARDL bounds test showed that there is a stable and long-run relationship among the variables. The long-run and short-run coefficients reveal that population aging and income per capita exert a statistically significant and positive effect on per capita HCE in India. The VECM causality evidence shows that there is a presence of short-run causality from economic growth and population aging to per capita HCE, urbanization to environmental degradation and further from aging to urbanization. However, the long-run causality evidence confirms unidirectional causality from population aging to the per capita HCE.

The research findings could be improved by considering the changes in mortality rate over time because of other environmental factors such as air pollution, among others as control variables. Various other variables affecting the health of an aged person could be considered for better research outcome which is not included in the present study because of the paucity of data. However, the present research findings would certainly serve effective policy instrument aiming at maximizing health gains that are highly associated with the elderly population and economic growth towards achieving sustainable development in India.

The uniqueness of the present study lies in its estimation where the relationship between population aging and HCE is looked at while considering the impact of other environmental factors separately. The causal relationship is shown among the variables using updated econometrics time-series techniques. The study tried to resolve the ambiguity associated with the relationship between aging and HCE at a macro level.

The reform and opening-up of capital market is valued for promoting sustainable development, while its impact presented as the form of deregulation of short-selling on the green innovation of enterprises in developing countries remains unclear. The purpose of this study is to outline the significance of gradual reform of financial markets in developing countries for low-carbon transformation and provide implications for achieving carbon peaking and carbon neutrality goals.

Based on the green subdivided patent data and financial data of China’s A-share listed companies, this paper takes the implementation of securities margin trading program as a quasi-natural experiment and applies the difference-in-differences (DID) model to examine the impact of deregulation of short-selling constraints on the enterprises’ green transformation.

The findings reveal that the initiating securities margin trading program significantly enhances the green innovation performance of enterprises. These findings are valid after performing a series of robustness tests such as the parallel trend test, the placebo test and the methods to exclude other policy interference. Mechanism analyses demonstrate a two-faceted effect of the securities margin trading program on the green innovation of enterprises, in which short-selling policy increases the pressure on capital market deregulation and meanwhile induces the environmental protection investment. The heterogeneity results demonstrate that the impulsive effect imposed by securities margin trading program is more significant in experimental group samples with characteristics of lower financing constraints, belonging to heavy polluting industries and possessing better environmental supervision capability.

First, previous studies have focused on the impact of financial policies implemented by banking institutions on the green innovation of enterprises, but few literatures have explored the validity of relaxing short-selling restrictions or opening the capital market in the field of enterprise’s green transformation in developing country. From the view of securities market reform, this paper broadens the incentive and supervision effects of the relaxation of short-selling control on enterprise’s green innovation performance after the implementation of securities financing and securities lending policy in China’s capital market. Second, previous studies have explored the impact of command-and-control environmental regulations, as well as market-incentivized environmental regulations such as green finance, low-carbon pilots and environmental tax reform, on the green transition of enterprises. Recently the role of the securities market in the green development of enterprises has received more attention in academia. The pilot of margin financing and securities lending is essentially a market-incentivized regulatory tool, but there is few in-depth research on how it affects the green innovation of enterprises. This paper enriches the research on whether the market incentive financial regulation policy can contribute to the green transformation of enterprises under the Porter hypothesis. Third, some previous studies used the ordinary panel regression model to explore the impact of financial policy on enterprise’s innovation performance. However, due to the potential endogenous problems of the estimated model, it might get biased conclusions. Therefore, based on the method of quasi-natural experiment, this paper selects the margin trading pilot policy as an exogenous shock to solve the endogenous or reverse causality problem in traditional measurement model and applies the DID model to study the relationship between core indicator variables.

This article challenges the prevailing view that a minimum income for the poor is only relevant to basic needs. It contributes to the discussion on the meanings of money by specifically focusing on the Italian Citizenship Income scheme as a case study.

A qualitative research design was developed and implemented in four regions of northern Italy. The analysis is based on 131 in-depth interviews with minimum income recipients.

The empirical analysis shows that money transfer has various meanings. Four dimensions are identified: functional, relational, protective, and emancipatory. The first two are connected to spending, while the latter two are related to self-identity. Although the four dimensions may overlap and coexist in the daily lives of minimum income beneficiaries, they are distinguished for analytical purposes.

The article presents a comprehensive analysis of the multiple meanings that minimum income can have for beneficiaries; meanings which are often not explicitly addressed in social policy studies. It goes beyond the equally important consideration of material needs by adding other meaningful aspects. This approach makes a different way of looking at cash transfers possible, and it provides elements useful for the design and analysis of minimum income policies.

The purpose of this paper is to define the impact of training and development (T&D) in the Visegrad countries (V4) as impacted by the Covid-19 pandemic, namely, Hungary, Poland, Slovakia and the Czech Republic. These countries have some political, cultural, social and economic similarities and share some common ground in the human resource development (HRD) sectors.

The authors used the HRD theory and the human capital theory to analyse the context, operations and impact of T&D in the V4 countries due to the Covid-19 pandemic. The research was conducted in 400 companies, 100 from each of the four countries using the computer assisted web interviewing technique. The questionnaire was in a six-point Likert scale format and addressed 12 topics related to T&D: policy, expectations, procedures of diagnosis, preparation, implementation, monitoring, trainees, trainers, investment and expenditures, evaluation, results and controlling.

The authors concluded that in the Visegrad countries, Covid-19 raised expectations on T&D. This was followed by increased levels of action in diagnosis, preparation, monitoring and implementation, following pre-existing and adjusted policies. Evaluation and control were complicated. Investment and results and the human side of the T&D (trainees and trainers) were the ones for which there were more uncertainties and perplexities.

The study has the limitation of using only a small sample in four countries. For further research, the authors suggest a larger study extended to all the European Union countries, an in-depth analysis of the current data and the kurtosis on Policy of T&D.

The results of the research can be used to improve T&D programs after the Covid-19 pandemic. They could also provide information to external trainers to improve and adjust their services according to the opinions of the respondents of the study. The research findings can also serve institutions responsible for policy provision of HRD at a national level by providing possibilities to apply for funding either within national or regional funds like the National Training Fund in Poland or within European Union money at a national level.

The study is original because even if the T&D in V4 countries during the Covid-19 pandemic had already been studied separately (e.g. Mikołajczyk, 2021; Vrabcová, Urbancová 2021; Vinichenko et al., 2021), no empirical, cross-national research analysing specifically the T&D in those countries has been carried out so far. The authors use an innovative methodology, addressing 12 topics and the people involved together with the stages in which a T&D policy is divided. That makes it innovative and very relevant.

This research paper aims to contribute to the field of innovation performance benchmarking by identifying appropriate benchmarking groups and exploring learning opportunities and integration directions.

The study employs a multi-dimensional innovation-driven clustering methodology to analyze data from the 2019 edition of the Global Innovation Index (GII). Hierarchical and K-means Cluster Analysis techniques are applied using various sets of distance matrices to uncover and analyze distinct innovation patterns.

This study classifies 129 countries into four clusters: Specials, Advanced, Intermediates and Primitives. Each cluster exhibits strengths and weaknesses in terms of innovation performance. Specials excel in the areas of institutions and knowledge commercialization, while the Advanced cluster demonstrates strengths in education and ICT-related services but shows weakness in patent commercialization. Intermediates show strengths in venture-capital and labour productivity but display weaknesses in R&D expenditure and the higher education quality. Primitives exhibit strength in creative activities but suffer from weaknesses in digital skills, education and training. Additionally, the study has identified 35 indicators that have negligible variance contributions across countries.

The study contributes to finding the relevant countries’ grouping for the enhancement of communication, integration and learning. To this end, this study highlights the innovation structural differences among countries and provides tailored innovation policies.

In order to solve the decision-making problem that the attributive weight and attributive value are both interval grey numbers, this paper tries to construct a multi-attribute grey decision-making model based on generalized greyness of interval grey number.

Firstly, according to the nature of the generalized gresness of interval grey number, the generalized weighted greyness distance between interval grey numbers is given, and the transformation relationship between greyness distance and real number distance is analyzed. Then according to the objective function that the square sum of generalized weighted greyness distances from the decision scheme to the best scheme and the worst scheme is the minimum, a multi-attribute grey decision-making model is constructed, and the simplified form of the model is given. Finally, the grey decision-making model proposed in this paper is applied to the evaluation of technological innovation capability of 6 provinces in China to verify the effectiveness of the model.

The results show that the grey decision-making model proposed in this paper has a strict mathematical foundation, clear physical meaning, simple calculation and easy programming. The application example shows that the grey decision model in this paper is feasible and effective. The research results not only enrich the grey system theory, but also provide a new way for the decision-making problem that the attributive weights and attributive values are interval grey numbers.

The decision-making model proposed in this paper does not need to seek the optimal solution of the attributive weight and the attributive value, and can save the decision-making labor and capital investment. The model in this paper is also suitable for the decision-making problem that deals with the coexistence of interval grey numbers and real numbers.

The paper succeeds in realizing the multi-attribute grey decision-making model based on generalized gresness and its simplified forms, which provide a new method for grey decision analysis.

The purpose of this study is to use a lifetime income measure to evaluate the long-run housing affordability for an understudied cohort of households in the literature – the millennials. The authors do this in the context of Malaysia, measuring long-run affordability for four housing types across geographic locations and income distributions.

This study calculates a long-run housing affordability index (HAI) using data on house prices and household incomes. Essentially a ratio of predicted lifetime incomes to house prices, the HAI is computed for four common housing types in Malaysia from 2005 to 2016 and for six states in the country. The HAI is also compared across four income percentiles.

The analysis reveals varying patterns of housing affordability among different states in Malaysia. Housing affordability has declined since 2010, with most housing types being unaffordable for millennial-led households with the lowest income. Housing is most affordable for those in the highest income bracket, although even here, there are pockets of unaffordable housing as well.

Based on the findings, this study proposes three targeted interventions to improve housing affordability for Malaysian millennials.

This study fills a gap in the literature by examining the long-run housing affordability of Malaysian millennial-led households based on both geographic location and income distribution. The millennial population is understudied in the housing affordability literature, making this study a valuable contribution to the field.