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This paper considers locating congested fast charging stations (FCSs) and deploying chargers in a stochastic environment, while the related studies have predominantly focused on problems in deterministic environments. Reducing the inconvenience caused by congestion at FCSs is an important challenge for FCS service provider. This is the underlying motivation for this study to consider a problem for FCS network design with the congestion restriction in a stochastic environment. We proposed a maximal coverage problem subject to budget constraints and a congestion restriction in order to maximize the demand coverage. With the derivation of the congestion restriction in the considered stochastic environment, the problem is formulated into an integer programming model. A real-life case study is conducted and managerial implications are drawn from its results.

Describes how the 1986 Financial Services Act gives the FSA power to pursue not only those breaching its rules but others who become involved in breaches by being “knowingly concerned”; the FSA can apply to the courts for an injunction or for a restitution order, and if the person is in fact a bank it has a new extra‐judicial power to make it disgorge the profits and/or compensate for the loss. Explains at length what “knowingly concerned” means in the context of the criminal and civil law. Shows how banks are now under significant obligation to obtain information about their clients, and this results in knowledge for the purpose of “knowingly concerned” liability; they also have to report suspicions of money laundering and generally cooperate with the FSA.

Recently, blockchain technology (BT) has resolved healthcare data management challenges. It helps healthcare providers automate medical records and mining to aid in data sharing and making more accurate diagnoses. This paper attempts to identify the critical success factors (CSFs) for successfully implementing BT in healthcare.

The paper is methodologically structured in four phases. The first phase leads to identifying success factors by reviewing the extant literature. In the second phase, expert opinions were solicited to authenticate the critical success factors required to implement BT in the healthcare sector. Decision Making Trial and Evaluation Laboratory (DEMATEL) method was employed to find the cause-and-effect relationship among the third phase’s critical success factors. In phase 4, the authors resort to validating the final results and findings.

Based on the analysis, 21 CSFs were identified and grouped under six dimensions. After applying the DEMATEL technique, nine factors belong to the causal group, and the remaining 12 factors fall under the effect group. The top three influencing factors of blockchain technology implementation in the healthcare ecosystem are data transparency, track and traceability and government support, whereas; implementation cost was the least influential.

This study provides a roadmap and may facilitate healthcare professionals to overcome contemporary challenges with the help of BT.

This paper appraises the effects of monetary policy on trade in value-added (TiVA) using a panel of 38 developing countries spanning the period 1990 to 2019. Specifically, the authors subsequently summon the theory of trade in intermediate products within the New Keynesian framework for open economies that comprises price rigidity to verify this relationship and thereon control for robustness by correcting for endogeneity and unbalanced panel effect.

The authors mobilize the within estimator corrected for cross sectional dependence as well as the two-stage-least squares fixed effect estimator which corrects for endogeneity. For robustness, the authors also use the Hausman–Taylor estimator to control for endogeneity and random effects in annualized data and the least squares dummy variable corrected estimator.

Results suggest that the monetary policy instruments such as inflationary gaps and anticipatory inflationary outcomes significantly affect TiVA in developing countries only in the short term with no long-term effect. In addition to contributing to the scanty empirical literature, the authors provide relevant insights on monetary policy tools that can be mobilized in fashioning a global value chain penetration and upgrading strategies.

The authors convoke the theory of trade in intermediate products casted into the New Keynesian framework comprising price rigidity to verify the relationship between TiVA and monetary policy (b) verify for robustness by correcting for endogeneity and unbalanced panel effect.

The purpose of this paper is to estimate the impact of the COVID-19 pandemic on the patterns of convergence/divergence among the districts in India. Specifically, this paper investigates if the impact is heterogeneous among different cohorts of districts (based on income distribution). The differential impact may lead to heterogeneous long-run growth paths, resulting in unbalanced development across regions within the country. A study of convergence can ascertain the possible trajectory of such development across regions. Investigation of this phenomenon is the primary aim of this study.

This paper uses the panel regression method for estimation. This paper uses high-frequency nighttime light intensity data as a proxy for aggregate output.

The authors observe a significant reduction in the convergence rate as a result of the pandemic. Across the cluster of districts, the drop in ß-convergence rate, compared to the pre-pandemic period, varied from approximately 33% for the poorer districts to close to zero for the richest group of districts. These findings suggest that the pandemic may lead to a wider disparity among different regions within the country.

This paper contributes to the literature in the following ways. First, to the best of the authors’ knowledge, this is the first paper to investigate the impact of COVID-19 on the convergence rate. A detailed look into the possible disparity in convergence among various regions is critical because a larger drop in convergence, especially among the poorer regions, may call for policy attention to attain long-term equitable development. The authors perform this exercise by dividing the districts into four quantile groups based on the distribution of night-light intensity. Second, while previous studies on convergence using nighttime light data have used a cross-sectional approach, this study is possibly the first attempt to use the panel regression method on this data. The application of this method can be useful in tackling district-level omitted variables bias. Finally, the heterogeneity analysis using different quantiles of the distribution of night-light intensity may help in designing targeted policies to mitigate the disparity across districts due to the shock.

This paper investigates the asymmetric impact of the real effective exchange rate (REER) on Egypt's real domestic output from 1960 to 2020.

A Nonlinear Autoregressive Distributed Lag (NARDL) model is utilized to isolate real currency depreciations from appreciations and account for the potential asymmetry in the impact of the REER. The analyses account for the various channels via which the REER could affect domestic output.

Results show evidence of a long-run asymmetry in the output effect of REER changes in which only real currency depreciations have a contractionary impact on output, while the REER has no impact on output in the short run.

The Egyptian monetary authority cannot rely on domestic currency depreciation as a policy instrument to boost domestic output.

Unlike most of the previous studies, which assume linearity in the impact of the REER on output, we relax this assumption and hypothesize that the REER changes have an asymmetric effect on the Egyptian domestic output in Egypt. We use a long time span from 1960 to 2020 and control for the potential structural breaks in the REER-output nexus and the various channels through which the REER can affect domestic output.

This study aims to explore potential paradigm shift in how “global economies” react to adverse macroeconomic conditions from key dominant economies such as the US and the Chinese economies. This is done by examining how economic activities within key economies around the world react to, or are impacted by, modeled adverse macroeconomic condition emanating from the Chinese and the US economies.

To verify potential paradigm shift in how external macroeconomic uncertainty impacts “global” industrial productivity and overall gross domestic product (GDP) growth within selected economies, this study opts for seemingly unrelated regression (SUR) model. Adoption of this method has been influenced by the potential for correlated error terms between modeled adverse macroeconomic condition, industrial productivity and GDP growth variables being tested in a two-equation system.

Empirical results based on SUR analysis find no evidence of this potential paradigm shift within the time frame examined in the study. Estimated results suggest that notwithstanding the recent growth surge of the Chinese economy, macroeconomic happenings within the US economy still exert significantly more influence on key economies around the world. For instance, this study finds that macroeconomic uncertainty associated with the US economy significantly constrains both industrial productivity and overall GDP growth within most of the economies tested, whereas the same condition emanating from the Chinese economy seems to rather have a weak positive impact on the same macroeconomic variables.

Research results are strictly limited to the focus time frame for this study; it is likely that expanded data involving more years beyond what was analyzed in this study could yield different results.

This study is an original research based on data from a reputable US federal institution.

The purpose of this paper is to examine the effect of investor protection on earnings management before and after IFRS adoption.

A sample of 106 companies listed on Germany, France and Belgium stock markets for the pre-IFRS (2000-2004) and post-IFRS (2006-2011) periods was used. This research is based on a comparative study between the pre- and the post-IFRS periods.

The results showed that investor protection better explains earnings management after the transition to IFRS. The findings revealed that international standards and investor protection are significant in jointly explaining earnings management for the second reporting period.

The study gives rise to a score that is considered as a proxy of investor protection that regroups several macroeconomic indexes.

This study seeks to examine the extent to which strands of inflationary related conditions (inflation expectations, inflation uncertainty and realized inflation); macroeconomic uncertainty and the likelihood of recessionary conditions influence performance indicators in the US banking sector over a specified time period.

The study adopts seemingly unrelated regression model (SUR) advanced by Zellner (1962) in its examination of how specific strands of inflationary conditions, and other adverse macroeconomic conditions influence performance dynamics in the US banking sector.

Empirical evidence suggest that among various adverse macroeconomic conditions examined, inflation expectations and macroeconomic uncertainty tend to have significant constraining impact on key performance indicators in the US banking sector than other conditions examined. Comparatively, this study finds that inflation expectations and macroeconomic uncertainty tend to have much more constraining impact on return on equity, than on return on assets in the US banking sector. Results further suggest that among the three bank performance indicators examined, net interest margin is the least vulnerable bank performance indicator to various adverse macroeconomic conditions examined in the study.

Apart from the various empirical results noted above, this study's findings are projected to help inform strategic planning decisions among institutions in the banking sector. The various findings could, for instance, inform policies and operational strategies geared toward reducing vulnerability associated with specific performance indicators such as return on equity. This reduction could be achieved by critically examining how the various performance indicators react to individual adverse macroeconomic conditions examined in this study. The process could ultimately help in developing tailored measures/procedures aimed at reducing how susceptible key performance indicators are to the various adverse macroeconomic conditions. This study's findings could also provide the platform for more adaptive policies aimed at minimizing the effects of noted macroeconomic conditions on operational efficiency in the banking sector.

The uniqueness of this study, compared to related ones found in the literature, stems from its treatment of three variant of related strands of macroeconomic condition (different variant of inflationary conditions) in the same framework in its empirical analysis.

本研究旨在探討與通貨膨脹有關的狀況的組成部分(通脹預期 、通脹不確定性及體現了的通脹), 宏觀經濟不確定性及經濟衰退狀況的可能性、在一段特定時間內對美國銀行業的表現指數有何種程度的影響。

研究採用塞爾納 (Zellner) (1962) 提出的看似無關迴歸模型 (SUR)，去探討通脹狀況的特定組成部分及其它不利的宏觀經濟狀況如何影響美國銀行業內的績效動態。

實證證據暗示在被研究的各個不利宏觀經濟狀況中，通脹預期及宏觀經濟不確定性，對美國銀行業內的主要業績指標的約束影響, 與其它被探討的狀況相比，往往會較重大。相對地、本研究結果顯示通脹預期及宏觀經濟不確定性，對美國銀行業資本回報率的約束影響、往往遠多於資產收益率。研究結果進一步顯示，在被探討的三個銀行業績指標中，就本研究所探討的各個不利的宏觀經濟狀況而言，淨息差是脆弱性最小的銀行業績指標。

除了上述各實證結果外，本研究結果預期會給銀行業內機構間作戰略規劃的決定時提供資料，譬如，各項研究結果或可在制定旨在減少與特定業績指標如資本回報率相聯繫的脆弱性的政策和經營策略時提供資料。這脆弱性的減少，是透過嚴謹地研究各個業績指標，如何對在本研究中被探討的個別不利宏觀經濟狀況作出反應而達致的。這程序或許最終會幫助建立一個以減少各個不利宏觀經濟狀況對主要業績指標的影響為目的的量身定制措施／程序。本研究的結果，或許亦可為更多旨在減弱眾所周知的宏觀經濟狀況對銀行業運營效率的影響的適應性政策提供平台。

與文獻中可見的相關研究比較，本研究的獨特性源於其實證分析，是涉及在同一個構架內處理宏觀經濟狀況相互有關的組成部分的三個變體 (通脹狀況的不同變體) 。

The significant economic weight of the Eurozone in the globe caused the contagion of the Eurozone debt crisis on the emerging markets. The Eurozone debt crisis caused the sudden plummeting of the cross-border bank credit (BC) to India causing a significant impact on bank lending in India. Essentially, the purpose of this study is to find an answer to the question: Did the decline in cross-border cross-credit from Eurozone had an impact on domestic BC in India?

Using the data for the period from 2000 to 2013 sourced from Bank for International Settlements international banking statistics consolidated data sets, the novel specification of the study captures the impact of Eurozone cross-border credit on India by developing two regression frameworks that capture the pre-Euro debt crisis period scenario and post-Euro debt crisis period scenario.

The results offer a very interesting analogy of the behavior of BC and cross-border credit during the pre and post-Eurozone crisis scenarios of analysis. During the pre-Eurozone crisis period, cross-border credit displayed a significant negative relationship with BC indicating that cross-border credit to the Indian firms indirectly benefitted the banks by creating increased demand for domestic BC. The post-Eurozone crisis period witnessed a nexus between cross-border credit and BC during the pre-Eurozone crisis period, which gradually disappeared largely because of the onset of the Eurozone crisis.

This study is a first of its kind in investigating the impact of the Eurozone crisis on an emerging economy like India. This study supports the hypothesis of the existence of the transmission of financial shocks through the balance sheets of international banks. The findings conform to the policy concerns of most of the emerging economies that international banks transmit financial shocks from their home countries. The implication for India and other emerging economies is that international credit growth deserves careful monitoring.