Tailor-made Policy Research Articles

The Matthew effect: Evidence on firms’ digitalization distributional effects

This paper explores the relationship between Information and Communication Technologies (ICT) diffusion and labor productivity at the firm level. We propose a model that explains labor productivity based on firm-specific characteristics (sector, size, location and year fixed effects), on the level of diffusion of digital technologies, and on human capital. We use quantile regression techniques to gain a more precise understanding of the association between ICT's diffusion and labor productivity for a heterogeneous firm landscape. Our results show that more productive firms are able to extract higher gains from digitalization than low productive ones, which exacerbates productivity differences between them. This requires from a tailor-made policy agenda to promote firm convergence, focused on helping firms to extract the most of digitalization.

Performance differentials of necessity and opportunity entrepreneurs: through the lens of motivation to learn and female entrepreneurial competencies

PurposeWomen entrepreneurs are often categorized and assessed for various outcomes based on their start-up motivations. It is generally assumed that entrepreneurs with opportunity motivation have better performance when compared to necessity entrepreneurs. This study aims to test these suppositions through the lens of the entrepreneur’s motivation to learn (MTL) and level of female entrepreneurial competencies (FECs), namely, business and management, entrepreneurial, human relations (HR) and personal.Design/methodology/approachData collected from 344 respondents through a survey questionnaire was analyzed using the structural equation modelling – partial least squares method using SmartPLS 4.FindingsThe findings highlight the need of recognizing the differentials between necessity and opportunity entrepreneurs as they were found to influence performance and learning outcomes. Opportunity entrepreneurship was found to significantly impact both MTL and the FECs. The authors also observed that business and management skills along with HR competencies played a greater role in the firm performance.Practical implicationsThe findings demonstrate a case for specialized, tailor-made policy approaches rather than the “one size fits all” approach as evident in many government programs. As necessity entrepreneurs form a vital part of the Indian entrepreneurial ecosystem, apart from mentoring, need-based competency development programs may be looked at. Opportunity entrepreneurs may need support and encouragement through advanced skilling and uncomplicated funding options.Originality/valueTo the best of the authors’ knowledge, empirical studies related to women-owned micro, small and medium enterprises in India establishing the relationship between start-up motivation and business performance are scarce. Even in the global context, this is one of the initial studies to examine the relationship through the lens of MTL and competencies.

Analyzing firm-specific factors affecting the financial performance of insurance companies in South Africa

This study aims to investigate the effect that firm-specific factors have on the financial performance of South African insurance companies. This paper looked at the performance of 36 insurers that are publicly traded and have quantifiable markets from 2008 to 2019. The return on assets (ROA) was calculated as a function of the financial performance in this study. While the firm size, leverage ratio, premium growth rate, liquidity ratio, and tangibility of assets were examined as dependent factors using the panel data regression technique, the premium growth rate, liquidity ratio, and tangibility of assets were explored as independent variables. According to the findings of the regression analysis, other firm-specific factors, with the exception of leverage and liquidity ratios, do not have a statistically significant influence on the financial performance of South African insurance companies. A negative and insignificant association was discovered between premium growth rate and ROA at –0.0023 and tangibility of assets and ROA at –0.0113. There was a strong positive and significant relationship between liquidity ratio and ROA at 0.0927, while the size had a positive but insignificant relationship with ROA at 0.0039. Leverage ratio and ROA had a negative but significant relationship at –0.1512. This study suggests that the use of automated systems and insured techs will be advantageous in cutting costs associated with policyholder enrollment, claims agreement, and even easily achieved tailor-made policy initiatives.

Deliberate underpricing and after-market mispricing in Indian IPO market: Stochastic frontier approach

Purpose This paper aims to study the underpricing phenomenon of initial public offerings (IPOs) of 355 Indian companies issued from 2007 to 2019. The research question this paper empirically examines is whether Indian corporate executives deliberately underprice IPOs from its fair value to attract investors, thereby causing an abnormal spike in the prices on the listing day. The findings of this study challenge a commonly held notion of leaving money on the table by IPO issuing companies. Of the overall average listing day returns of 17%, the deliberate premarket underpricing component is found to be mere 5.3%, while the remaining price fluctuation is, inter alia, a result of market momentum along with the unmet demands of impatient investors. Design/methodology/approach Following Koop and Li (2001), this study uses Stochastic frontier model (SFM) to study a routine anomaly of disparity between the primary market price (i.e. IPO issue price) and the secondary market price (listing price). The jump in the issue price observed on a listing day is decomposed into deliberate premarket underpricing component that reflects the extent of managerial manipulation and the after-market misvaluation component attributable to information asymmetry and prevailing market volatility. Findings This paper uses SFM to bifurcate initial returns into deliberate underpricing by managers and after-market mispricing by noise traders. This study finds that a significant part of the initial return is explained through after-market mispricing. This study finds that average initial returns are 17%, deliberate premarket underpricing is 5.3% and after-market mispricing averages 11.9%. Research limitations/implications This study can isolate underpricing done at the premarket by estimating a systematic one-sided error term that measures the maximum predicted issue price deviation from the offered price. Consequentially, the disaggregation of initial returns may be especially informative for retail investors in planning their exit strategy from an IPO by separating the strength of the firm's fundamentals and its causal relationship with the initial returns. Substantial proportion of after-market mispricing implies that future research should focus on factors causing after-market mispricing. As underlying causes are identified, tailor-made policy responses can be formulated to benefit investors. Practical implications This paper has empirically validated that initial return is a mix of both components, i.e. deliberate underpricing and aftermarket mispricing. This disaggregation of initial returns can prove helpful for investors in planning their exit strategy. This study can help investors to become more aware of the importance of the fundamentals of the firm and its causal relation with the initial returns. This information in turn can help reduce the information asymmetry amongst investors and help them lessen the costs of adverse selection. Originality/value A large number of research studies on IPO pricing find overwhelming evidence of underpricing in public issues. This research attempts to decompose the extent of underpricing into deliberate underpricing and after-market mispricing, thereby supplementing the existing literature on the IPO pricing puzzle. To the best of the authors’ knowledge, this study is the first contribution to the literature on initial return decomposition for the Indian capital markets.

Unraveling the association between the built environment and air pollution from a geospatial perspective

Fine particulate matter poses a negative effect on air quality and public health. The formation and dispersion of PM2.5 are often affected by the urban built environment. Previous literature has made great efforts to study the relationship between the built environment and air pollution, and propose corresponding policy implications for reducing air pollution. Most proposed policies are instructive but lack spatial heterogeneity, which is essential because the degree of air pollution and measures in each specific place is different. In this study, the built environment was depicted with multisource data and methods such as street view imagery (SVI) and deep learning, and the integration of geographically weighted regression (GWR) and k-means clustering was applied to explore the spatially varying impacts of the built environment factors on air pollution, and classify the study area into different groups with zonal policies and mitigation measures for PM2.5 reduction. Results show that parking lots significantly influenced PM2.5, followed by floor area ratio, road density, street vehicle volume, industrial facility, and street view greenery. Street view greenery was found to be negatively related to PM2.5 concentration in most of Xiamen Island. The study area was categorized into four groups with tailor-made policy implications considering spatial heterogeneity. For example, zone 1 is in the south of Xiamen Island with the highest coefficients of the parking lot and floor area ratio and lowest coefficient of street view greenery. For zone 1, greenery maintenance in the mountains, restricted high-density development, and improvement of greenery around the parking lot may be effective for this zone. These empirical results provide a new perspective for exploring the spatially heterogeneous mechanism of air pollution and a new approach to propose targeted and zonal policy implications for PM2.5 mitigation.

A composite indicator analysis for optimizing entrepreneurial ecosystems

• We use the ‘benefit of the doubt’ (BOD) weighting to evaluate the entrepreneurial ecosystem at the global scale. • We compute endogenous weights to identify country-specific policy priorities. • We show how countries can design optimal entrepreneurship policy using objective criteria. • Effective policy is conditional on the configuration of countries’ entrepreneurial ecosystem. • Quality improvements in entrepreneurial ecosystems are conducive to higher levels of venture capital investments. We employ the ‘benefit of the doubt’ approach rooted in non-parametric techniques to evaluate the entrepreneurial ecosystem of 71 countries for the period 2016. By scrutinizing the relative efficiency of countries’ entrepreneurial ecosystems, the proposed analysis of composite indicators allows the computation of endogenous (country-specific) weights that can be used for developing more informed policy making. The results show that countries prioritize different aspects of their national system of entrepreneurship which confirms that, contrary to homogeneous prescription, tailor-made policy is necessary if the objective is to optimize the resources deployed to enhance the countries’ entrepreneurial ecosystem. The findings of the empirical application reveal significant improvements in the quality of the entrepreneurial ecosystem can be realized by targeting the policy priorities of the local entrepreneurship system identified by the ‘benefit of the doubt’ weights. By analyzing the variation in economic and entrepreneurship outcomes over the seven-year period centered on the study year (period 2013–2019), we found a significant positive correlation between quality improvements in the entrepreneurial ecosystem and venture capital investments.

The Review of Policy Instruments Stimulating Circular Economy: A Case Study of Poland

The objective of the study was to review policy instruments stimulating circular economy (CE). The review was completed using analytical frameworks; primary material was compiled using the Science Direct database. The following four groups of potential instruments were identified and characterized: nodality, authority, treasure, and organization-based. Subsequently, an in-depth analysis was performed in order to examine their implementation in Poland. The study revealed a broad spectrum of application of legislative and economic instruments (targets, direct legal regulations, extended producer responsibility, taxation). On the other hand, the application of information instruments was revealed to be insufficient (information campaigns, eco-labelling) and the application of organization-based instruments to be negligible (eco-industrial parks, circular public procurement). We argue that a comprehensive character of support is required. This denotes the need for new, tailor-made policy instruments to be introduced. Finally, the article presents challenges for the policy mix in relation to the transition to CE, and suggests avenues for future research.

Multiculturalism with Hong Kong Characteristics

AbstractHong Kong (a special administrative region of the People’s Republic of China) is promoted as “Asia’s World City” due to its interconnectivity, East-meets-West geopolitical orientation, and composition of migrants from both Asian and non-Asian countries. Hong Kong-based scholars have suggested that Hong Kong’s policy towards the social inclusion of non-Chinese communities is ambiguous. For example, the Race Discrimination Ordinance (RDO) lacks an informative description of racial discrimination, which may lead to shortcomings in ethnic minority protections under the current social policy for integration (e.g., ethnic minorities’ experiences related to religious discrimination). Most of the non-White ethnic minority population of Hong Kong consists of low-income South Asians and Southeast Asians, with some ethnic groups (e.g., Nepalese) reported to reside in socially segregated districts. Furthermore, scholars have highlighted that current social policy in Hong Kong appears to be partially or completely different from Western-based approaches to multiculturalism, necessitating further examination to promote social inclusion. To fill this gap, this study explores the perspectives of Chinese and non-Chinese individuals regarding multiculturalism in Hong Kong. The study adopts a qualitative research design and includes interviews with twenty ethnically Chinese and non-Chinese teachers serving minorities in Hong Kong. Three themes emerge in this study: 1) a general understanding of multiculturalism as diverse cultural/ethnic backgrounds, mutual understanding and acceptance, and inclusive social harmony and social justice; 2) perceptions of Hong Kong-based multiculturalism and the perceived hierarchy of ethnic groups; and 3) the main differences between Western and Hong Kong-based multiculturalism, including more acceptance of diversity in the West and geographic location. In sum, this study provides recommendations to ensure a respectful and ethical inclusion of non-White ethnic minorities in Hong Kong, such as developing a tailor-made policy.

Do compact cities have higher efficiencies of agglomeration economies? A dynamic panel model with compactness indicators

Compact development is proposed to preserve land resources as well as promote agglomeration economies. This paper adopts a multi-indicator system of compact cities, including population density, boundary limitation, and road density, to examine the relationship between the compact city and urban efficiency through agglomeration economies. We empirically examine the relationships between compact city indicators and comprehensive/technical efficiency measures of the cities through GMM regression with panel data of 226 prefectural and upper-level cities in China during 2001–2015. We find the answers heterogeneous for each indicator-efficiency pair for each city type. Higher population density and compact urban form are beneficial to the urban economic efficiencies of large cities, but not for the technical efficiency of small cities. Road density is conducive efficiencies for small and medium cities, but not technical efficiencies for large cities. We confer that the heterogeneity may be explained by the economic structure compositions of cities of different sizes. Based on our findings, we propose tailor-made policy suggestions regarding urban compactness and economic efficiencies for cities of different sizes.

An improved method for investigating urban municipal infrastructures carrying capacity

Urban municipal infrastructures play an essential role in urban social and economic development. However, the imbalance between the supply and demand of urban municipal infrastructures appears a common problem in cities. This presents an urgent need for a proper method to investigate the carrying capacity of urban municipal infrastructures in the process of pursuing sustainable urban development. In line with this background, this paper defines the concept of urban municipal infrastructures carrying capacity (UMICC) and establishes an improved method for investigating this capacity. The performances of UMICC are designed to four levels, namely, Low-Utilization, Medium-Utilization, High-Utilization, and Over-Utilization. The effectiveness of this method is proven through an empirical analysis by using the data collected from 35 large cities in China. The empirical results reveal that the utilization intensity of UMICC has been decreasing in recent years in the large Chinese cities, in which UMICC carrier has been increasing at a higher speed than that of UMICC load. In particular, some better-developed cities present a “Low-Utilization” performance level, which is considered that urban policy-makers in some metropolises in China should pay more attention to the better utilization of existing municipal infrastructures. By applying the improved UMICC method introduced in this study, decision-makers can identify the specific areas that affecting the UMICC performance, thus tailor-made policy can be designed for improving UMICC performance by adjusting UMICC carrier and load.

Perils of an open Arctic

Perils of an open Arctic

Evaluation Method for Urban Public Service Carrying Capacity (UPSCC): A Qualitative-Quantitative Bi-Dimensional Perspective.

Urban Public Service Carrying Capacity plays an essential role in urban social and economic development. However, existing study has been focused on the evaluation of UPSCC from a quantitative perspective. It is necessary to evaluate UPSCC from a qualitative–quantitative bi-dimensional perspective. This paper establishes an innovative evaluation method for UPSCC based on a qualitative–quantitative bi-dimensional (QQBD) perspective. The proposed QQBD-based UPSCC evaluation method can help identify the weak areas of public services. The conclusions of this study are as follows. Firstly, public services are people-oriented social resources, which should be evaluated from both quantitative and qualitative perspectives. Secondly, the quantitative measurement of public service carrying capacity needs to consider both UPSCC load and carrier, while the qualitative measurement needs to consider the satisfaction among stakeholders. Thirdly, the demonstration of the case study cities shows the effectiveness of the qualitative–quantitative bi-dimensional UPSCC evaluation method. By applying the QQBD-based UPSCC evaluation method introduced in this study, decision makers can identify the specific areas that affect the UPSCC performance, and thus tailor-made policy can be designed for improving UPSCC performance by adjusting UPSCC quantity and quality.

Why Should Different City Characteristics Customize the Rate of Pollution Charge? Evidence of Factors Affecting Willingness-to-pay for Wastewater Management in Thailand

A challenge for wastewater management is enhancing the efficiency of resource allocation. Polluter Pays Principle is a wastewater charge collection approach that could help support the financial burden faced by many countries. Tailor-made policy implementation based on city characteristics is critical to the success of implementing a national policy to fit well in different local contexts. This study examined gaps for improving municipal wastewater management systems in Thailand through in-depth interviews and a questionnaire survey to identify the factors influencing households’ perception and willingness to pay in three different cities. A contingent variation method technique was used to evaluate the preferences of residents. The study revealed that different cities have different factors that influence willingness-to-pay decisions as well as pay-out levels. A single common factor positively affecting willingness-to-pay preference in all three cities is perception and engagement of wastewater treatment service. Citizens with a positive perception of receiving wastewater service are not only more likely to pay the wastewater charge, but also at a higher amount.

A note on the configuration of the digital ecosystem in Latin America

We evaluate the main characteristics of the digital ecosystem of North American (USA and Canada) and 16 Latin American economies for 2019. By employing the ‘benefit of the doubt’ model rooted in non-parametric techniques to scrutinize a composite indicator designed to assess the digital ecosystem (i.e., the Digital Platform Economy (DPE) index), the analysis allows the computation of endogenous (country-specific) weights that can be used for developing more informed policy making. The results show that countries prioritize different aspects of their digital ecosystem which confirms that, contrary to homogeneous prescription, tailor-made policy is a more desirable approach if the objective is to optimize the resources deployed to enhance the countries’ digital ecosystem.

How to address properly the scale of urban infrastructures? –An empirical study of 35 large Chinese cities

Infrastructure provision is widely emphasised amid industrialisation, modernisation and urbanisation, for which plenty efforts have been devoted across countries globally. Nevertheless, it should be noted that the shortage or over-supply of urban infrastructures has already induced various urban symptoms, such as urban storm water runoff, urban heat island effect, and habitat destruction, and this is particularly the case in the context of some emerging economies. China, the largest-volume developing country worldwide, has witnessed an unparalleled urbanisation process since the post-reform era, whilst is simultaneously being challenged with critical urban problems triggered by the inappropriate expansion of urban infrastructures. These urban problems manifest more explicitly in mega cities. It is considered essential for these large cities to address properly the scale of urban infrastructures (UIS) by underpinning the understanding of the driving factors for UIS expansion, so that proper planning and construction strategies can be designed and implemented. Extant literature presents inherent limitations in duly exploring the driving factors of UIS expansion, and in filling this research gap, this study therefore aims to investigate the driving factors of UIS expansion in the context of 35 Chinese large cities. Kaya identity and Logarithmic Mean Divisia Index (LMDI) method are applied collectively for conducting the research. The findings from this study can be highlighted as follows: Utilisation efficiency (UE) is found inhibits UIS expansion in 77% (27/35) surveyed Chinese large cities; economic output (EO) and population (P) present significant role in stimulating UIS enlargement across all the surveyed large cities. Tailor-made policy recommendations have been synthesised by drawing upon the understanding of UIS expansion driving factors, which can facilitate local urban governors to address appropriately the scale of urban infrastructure construction and delivery, and further contribute to the sustainability improvement of urbanisation paradigm across the country of China.

THE DIGITAL ECOSYSTEM AROUND THE WORLD: A COMPOSITE INDICATOR ANALYSIS

This study employs the “Benefit of the Doubt” method rooted in non-parametric techniques to evaluate the digital ecosystem of 116 countries for the year 2019. By scrutinizing the relative efficiency of countries’ digital ecosystem based on the Digital Platform Economy index (DPE index), the proposed analysis of composite indicators allows the computation of endogenous (country-specific) weights that can be used for developing a more informed policy. The results show that countries prioritize different aspects of their digital ecosystem. Additionally, the findings reveal significant differences in the configuration of the digital ecosystem around the world. These results confirm that, contrary to homogeneous prescription, tailor-made policy is necessary if the objective is to optimize the resources deployed to enhance the digital ecosystem.

Study on the Matching Degree between Land Resources Carrying Capacity and Industrial Development in Main Cities of Xinjiang, China

The contradiction between industrial development (ID) and land resource carrying capacity (LRCC) is increasingly intensified with the rapid advancement of urbanization globally. This typical phenomenon exists particularly in these developing countries or regions. This study investigated the matching degree (MD) between ID and LRCC by using a coupling coordination degree model (CCDM) with referring to the main cities of Xinjiang, China. The data used in this study was collected from 16 sample cities in Xinjiang for the period of 2009–2018. The research findings reveal that (1) MD average value between 16 sample cities has been gaining steady growth; (2) although MD value in all sample cities has been increasing, there still exists a big room for improvement towards a well matching state; (3) the differences in MD values among all sample cities are very small; (4) the MD performance in the northern cities in Xinjiang is better than that in southern Xinjiang. This is mainly because of the radiation effect of Urumqi in northern cities. It is therefore suggested developing such a radiation city in southern Xinjiang in order to improve MD performance in southern Xinjiang. These research findings can provide policymakers in Xinjiang and other backward cities globally with valuable references in understanding the status of MD between ID and LRCC in the local cities, thus tailor-made policy instruments can be designated for the mission of sustainable development.

The digital ecosystem around the world: a composite indicator analysis

This study employs the ‘benefit of the doubt’ method rooted in non-parametric techniques to evaluate the digital ecosystem of 116 countries for the year 2019. By scrutinizing the relative efficiency of countries’ digital ecosystem based on the Digital Platform Economy (DPE) index, the proposed analysis of composite indicators allows the computation of endogenous (country-specific) weights that can be used for developing more informed policy. The results show that countries prioritize different aspects of their digital ecosystem. Additionally, the findings reveal significant differences in the configuration of the digital ecosystem around the world. These results confirm that, contrary to homogeneous prescription, tailor-made policy is necessary if the objective is to optimize the resources deployed to enhance the digital ecosystem.

A population-based study on mortality among Belgian immigrants during the first COVID-19 wave in Belgium. Can demographic and socioeconomic indicators explain differential mortality?

IntroductionBelgium has noted a significant excess mortality during the first COVID-19 wave. Research in other countries has shown that people with migrant origin are disproportionally affected. Belgium has an ethnically diverse and increasingly ageing population and is therefore particularly apt to study differential mortality by migrant group during this first wave of COVID-19.Data and methodsWe used nationwide individually-linked data from the Belgian National Register providing sociodemographic indicators and mortality; and the administrative census of 2011 providing indicators of socioeconomic position. Age-standardized all-cause mortality rates (ASMRs) were calculated during the first COVID-19 wave (weeks 11–20 in 2020) and compared with ASMRs during weeks 11–20 in 2019 to calculate excess mortality by migrant origin, age and gender. For both years, relative inequalities were calculated by migrant group using Poisson regression, with and without adjustment for sociodemographic and socioeconomic indicators.ResultsAmong the middle-aged, ASMRs revealed increased mortality in all origin groups, with significant excess mortality for Belgians and Sub-Saharan African men. At old age, excess mortality up to 60% was observed for all groups. In relative terms, most male elderly migrant groups showed higher mortality than natives, as opposed to 2019 and to women. Adding the control variables decreased this excess mortality.DiscussionThis study underlined important inequalities in overall and excess mortality in specific migrant communities, especially in men. Tailor-made policy measures and communication strategies should be set-up taking into account the particular risks to which groups are exposed.

Capability Maturity Model (CMM) method for assessing the performance of low-carbon city practice

Carbon emissions are considered as major factor affecting sustainable urban development. Cities have been promoting low carbon city (LCC) strategies to reduce carbon emissions and various methods have been introduced to assess the performance of LCC strategies. However, most of the existing assessment methods focus on overall LCC performance at city level, but the effects of individual dimensions like industrial structure and energy efficiency are ignored. The research question in this study therefore is whether an alternative method can be established to measure both the overall and dimensional LCC performance. This paper introduces a method for assessing LCC performance by using Capability Maturity Model (CMM), which is called LCC-CMM. The proposed method of LCC-CMM can help identify LCC maturity grade through assessing the performance of individual LCC dimensions which contributes to overall performance. There are four procedures in applying LCC-CMM, including to identify the Key Process Areas (KPAs) in the context of LCC, denoted as LCC-KPAs, to define the indicators for measuring the performance of LCC-KPAs, to calculate the performance score for each LCC-KPA, and to define criteria for specifying different grades of LCC capability maturity. The proposed method is proven effective through a case demonstration. The method can help policy makers to identify weak areas in LCC practice and introduce tailor-made policy measures to improve the weak areas.