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This paper attempts to examine which theory is best at explaining the geographic concentration in Java, an island in which most of the Indonesia’s large and medium manufacturing industries have located overwhelmingly. Our previous studies on Java have found that there was a stable – albeit increasing trend – and persistent geographic concentration in Java over the period 1976‐1995. Yet some critical questions exist: Why geographic concentration in Java persisted during this period? To what extent relevant theories and empirical literature can be used as an explicit test of competing theories on agglomeration forces? In answering those questions, we compare the three major grand theories of geographic concentration: Neo‐Classical Theory (NCT), New Trade Theory (NTT) and New Economic Geography (NEG). Using the regional specialization index as a measure of geographic concentration of manufacturing industry and pooling data over the period 1991‐002, our econometric analysis integrates the perspectives of industry, region (space) and time. We further explore the nature and dynamics of agglomeration forces underpinning the industrial agglomeration in Java by testing some key variables. Our econometric results rejected the NCT hypotheses and showed that the NTT and NEG can better explain the phenomena. It’s apparent that manufacturing firms in Java seek to locate in more populous and densely populated areas in order to enjoy both localization economies and urbanization economies, as shown by the significance of scale economies and income per capita. The former is associated with the size of a particular industry, while the latter reflects the size of a market in a particular urban area. More importantly, the results suggest that there is a synergy between thickness of market and agglomeration forces. The interplay of agglomeration economies is intensified by the imperfect competition of Java’s market structure. We find that Java’s market structure may restrict competition so that firms tend to concentrate geographically. Instead of providing some important recommendations for local and central governments and practical implications for investors and manufacturing firms, this paper gives empirical evidence with respect to path dependency hypothesis. The finding supports the NEG’s belief that history matters: older firms tend to enhance regional specialization.

The focus of this article is to examine the relationship between local economic growth and development and local government revenue capacity. A model is established to determine the relationship between the number of agricultural, manufacturing, service, and retail establishments per capita and employees per capita on real local government property tax capacity per capita. High property tax levies are highly negatively correlated with tax capacity. Population density, the general price level, and the presence of local retail sales taxes also play a role in determining tax capacity. New business creation in the service industry does appear to have a positive impact on local government tax capacity, while increases in agricultural, manufacturing, and retail activity do not. Although increasing concentration in the number of service establishments has a positive impact on tax capacity, increasing concentration in the number of service workers alone does not seem to lead to increases in tax capacity.

Clearly defined information is essential for rational decision‐making, planning and control, at all management levels. The current climate in the UK National Health Service dictates that clinicians should be more actively involved in management. However, no relevant and accurate information is routinely available on either the workload or work patterns of individual hospital departments. If clinicians were supplied with this they would then be in a better position to manage their own services. This paper provides a synopsis of the philosophy behind the design of management information systems and presents the results of a pilot study, which was undertaken in a hospital neurology department. The general guidance which emerges is that analysts must always concentrate on ivhat information is needed and the uses to which it will be put. A systems approach to design helps to: (i) define the information required; (ii) establish processes for data capture and analysis; and (iii) establish standards with which actual service performance can be compared (feedback control feature). The pilot study provided information on all stages of development. The systems approach employed could be applied within any clinical department, but doctors must be actively involved. Information derived from running the prototype provided insight into many aspects of work activity, organisation and use of resources within a neurology specialty. A comparison between actual service performance and standards of service as perceived by the consultant neurologists involved, was also undertaken.

This paper aims to propose that firms located in science and technology parks (STP) developing corporate social responsibility practices can attract talented workers as an effective knowledge management spillover mechanism.

A longitudinal study has been carried out from the Spanish Panel of Technological Innovation database (PITEC). The statistical method used for data treatment has been a logistic regression for panel data.

Empirical results show a positive moderating effect of corporate social responsibility practices on the relationship between the firm’s belonging to a STP and talent attraction.

This research follows previous claim for additional research on the phenomenon of talent management and clusters and STP. In that sense, and to the best of the authors’ knowledge, there is no previous empirical research about the complementarily effect of corporate social responsibility practices and the belonging to a STP in talent attraction.

Statistics from Eurostat show that several European countries have an increasing proportion of elderly people, making their housing situation of increasing interest. For many years, it has been policy in Sweden to help elderly people remain in their current homes for as long as possible. This paper aims to find reasons why people want to move at different stages in life and investigate whether the pattern follows the life cycle in housing. Earlier research has been performed in the USA (Gibler and Clements III, 2011) and in China (Jia and Heath, 2016), but these questions remain understudied in Sweden.

A model of the demand for adapted houses is designed and tested on data gathered in Gävle in 2012. The method uses a binary choice model with stated preference data.

The results of this study show that earlier preferences and age determine the future living situation, but that senior living (rental or condominium) is most popular as a future home.

Not everyone has the economic resources to move according to their preferences; reasons include high monthly costs and taxes. Changes in the tax system may produce better moving chains and increase the supply of affordable housing.

The model in this paper could guide future studies within the area.

Outlines previous research on business failure prediction models and investigates the impact of serial correlation and non‐stationarity in financial variables on models based on linear discriminant analysis, logit and cumulative sums using 1974‐1991 data from a sample of failed and non‐failed US firms, plus a similar 1992 sample. Presents and discusses the time series behaviour of the explanatory variables, the estimation of the three types of models and their error rates over time. Concludes that models based on variables with strong positive serial correlation deteriorate over time in their forecasting power; and calls for research to develop stationary models.

This study aims to analyse the intellectual property rights (INPR), foreign direct investment (FDI) inflows and technological exports of 32 developing and developed countries for the period of 2006–2020.

Diagnostic tests were used to confirm the panel least squares, fixed effect, random effect, feasible general least squares, dynamic ordinary least squares and fully modified ordinary least squares estimator results as well as to increase the robustness.

According to the findings for the developing countries, trademark, patent and industrial design applications, each had a significant positive long-run effect on FDI inflows. In addition, there was a significant positive long-run relationship between patent applications and medium- and high-technology exports. Meanwhile, trademark and industrial design applications had a significant negative long-term effect on medium- and high-technology exports. In developed countries, patent and industrial design applications each have a significant negative long-term on medium- and high-technology exports. Furthermore, patent and trademark applications each had a significant negative long-run effect on FDI inflows.

This study contributes significantly to the focus that host countries evaluate the technology gaps between domestic and foreign investors at different industry levels to select the best INPR rules and innovation process by increasing international cooperation. Furthermore, the host countries should follow the structure–conduct–performance paradigm based on analysis of the market structure, strategic firms and industrial dynamics systems.

The purpose of this paper is to analyze the dynamic asymmetric relationship between financial technology (FinTech) adoption and poverty alleviation on annual data for the Sub-Saharan Africa (SSA) region over the period from 2004 to 2020.

This study adopted the general method of moments (GMM) method on annual data for 127 countries including 45 countries from the SSA region over the period from 2004 to 2020.

The study’s findings show that improvement in FinTech may initially decrease the rate of extreme poverty, leading to a decrease in total poverty as a percent of the population. While there is an initial decrease in the rate of extreme poverty with improvements of FinTech, once the FinTech index reaches its threshold level of 37.18 points, further improvement in FinTech tends to decrease as penetration increases, giving rise to an decrease in the rate of poverty alleviation.

Policymakers should design more aggressive and comprehensive policies directed at recouping the maximum gains of FinTech adoption, with a reasonable threshold target.

Policymakers in the SSA region must be aware of a FinTech threshold level of 37.18 points. To ensure the highest reduction in extreme poverty, policymakers must keep investing in FinTech to reach this threshold level.

FinTech improvement leads to poverty alleviation. Policymakers in the SSA region can fully recoup the benefits of FinTech by achieving a pre-set threshold level.

This paper addresses that gap in the literature by studying the impact of FinTech, instead of the traditional financial inclusion measures, on poverty in the 45 countries in the SSA region, exploring the potential dynamic asymmetry of this poverty-FinTech link, and testing the presence and statistical significance of the threshold level of FinTech.

Energy security has been talked about by governments and policymakers because the global energy market is unstable and greenhouse gas emissions threaten the long-term health of the global environment. One of the most potent ways to cut CO₂ emissions is through the production and consumption of renewable energy. Thus, the purpose of this paper is to highlight the drivers that, if ambitious environmental policies are implemented, might improve energy security or prevent its deterioration.

The study uses a balanced panel data set for Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam that covers a period of 30 years (1990–2020). The pooled panel dynamic least squares is used in this study.

The findings show that renewable energy consumption is positively related to gross domestic product per capita, energy intensity per capita and renewable energy installed capacity. Wherein renewable energy use is inversely related to per capita electricity consumption, CO₂ emissions and the use of fossil fuel electricity.

There is a lack of research identifying the factors influencing energy security in the ASEAN region. Therefore, this study focuses on the drivers that influence energy security, which are explained by the proportion of renewable energy in final energy consumption. Without identifying the demand and supply sources of energy, especially electricity production based on renewable energy techniques, it is hard for policymakers to achieve the desired renewable energy-based outcome.

The purpose of this paper is to empirically examine the effectiveness of foreign aid in improving economic growth prospects in the sub-Saharan Africa (SSA) region from 1993 to 2017.

A sample of 45 SSA countries for the period 1993–2017 is considered for this study. The study uses various econometrics tools such as Pedroni and Kao’s cointegration test, Johansen-Fisher Panel cointegration test, FMOLS and PDOLS in order to ascertain the long-run and short-run dynamics among the variables under consideration.

The empirical results find that long-run and short-run relationships exist among foreign aid, economic growth, investment, financial deepening, price stability and trade openness of the SSA economies. The authors also find unidirectional causality running from foreign aid to economic growth. The policymakers in these countries are well-advised to implement suitable policy measures to build on the growth momentum created by foreign aid inflows.

The study uses a dynamic macroeconomic modeling framework to assess the impact of aid flows on economic growth in the SSA region. Taking into account the diversity of level of growth experienced by the 45 countries in the region, the study uses an appropriate regression technique, i.e., panel dynamic OLS whose results are robust. The finding is also supported by the Granger-causality test and robust cointegration techniques.