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1 – 10 of over 1000Yukun Hu, Suihuai Yu, Dengkai Chen, Jianjie Chu, Yanpu Yang and Qing Ao
A successful process of design concept evaluation has positive influence on subsequent processes. This study aims to consider the evaluation information at multiple stages and the…
Abstract
Purpose
A successful process of design concept evaluation has positive influence on subsequent processes. This study aims to consider the evaluation information at multiple stages and the interaction among evaluators and improve the credibility of evaluation results.
Design/methodology/approach
This paper proposes a multi-stage approach for design concept evaluation based on complex network and bounded confidence. First, a network is constructed according to the evaluation data. Depending on the consensus degree of evaluation opinions, the number of evaluation rounds is determined. Then, bounded confidence rules are applied for the modification of preference information. Last, a planning function is constructed to calculate the weight of each stage and aggregate information at multiple evaluation stages.
Findings
The results indicate that the opinions of the evaluators tend to be consistent after multiple stages of interactive adjustment, and the ordering of design concept alternatives tends to be stable with the progress of the evaluation.
Research limitations/implications
Updating preferences according to the bounded confidence rules, only the opinions within the trust threshold are considered. The attribute information of the node itself is inadequately considered.
Originality/value
This method addresses the need for considering the evaluation information at each stage and minimizes the impact of disagreements within the evaluation group on the evaluation results.
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Kumar Shaurav, Abdhut Deheri and Badri Narayan Rath
The purpose of this research is to evaluate corruption in the context of India, spanning the period between 1988 and 2021. Additionally, it aims to provide an in-depth…
Abstract
Purpose
The purpose of this research is to evaluate corruption in the context of India, spanning the period between 1988 and 2021. Additionally, it aims to provide an in-depth comprehension of the factors that drive its prevalence and to propose policy directives for addressing these underlying issues.
Design/methodology/approach
The study instead of relying on perception-based measures, takes a distinct approach by formulating a corruption index derived from reported instances, thus ensuring a more objective assessment. Furthermore, we employ stochastic frontier analysis to tackle the issue of under-reporting within the corruption index based on reported cases. Subsequently, an auto regressive distributed lag (ARDL) methodology is applied to ascertain the principal drivers of corruption, encompassing both long and short factors.
Findings
This study reveals that corruption in India is notably influenced by economic growth and income inequality. Conversely, government effectiveness and globalization display a tendency to mitigate corruption. However, our rigorous analysis demonstrates that financial development does not wield a substantial influence in our study. Moreover, our inquiry uncovers a nonlinear relationship between economic growth and corruption. Additionally, we ascertain that the long run and short run impacts of corruption remain relatively stable across both models utilized in our study.
Originality/value
This study differs from previous research in the subsequent manners. Primarily, we employed an objective measure to formulate the corruption index, coupled with addressing the underreporting issues via stochastic frontier analysis. Moreover, this study pioneers the identification of a non-linear relationship between corruption and economic growth within the Indian context, a facet unexplored in previous investigations.
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Mario Gómez and Oluwasefunmi Eunice Irewole
Unemployment is one of the major challenges facing most countries, including Africa as a continent. Seeking how to reduce unemployment, debt, inflation and increase gross domestic…
Abstract
Purpose
Unemployment is one of the major challenges facing most countries, including Africa as a continent. Seeking how to reduce unemployment, debt, inflation and increase gross domestic product (GDP), foreign direct investment (FDI) and gross capital formation in the continent has been an agenda of governments, policy makers and economists to. This study examines the relationship between economic growth, inflation, debt, FDI, gross capital formation, labor force, population and unemployment in Africa.
Design/methodology/approach
An updated panel dataset of 29 African countries was selected from different regions from 1991 to 2019. These countries were selected based on their unemployment, population growth and inflation rates. The Pesaran cross-sectional dependence and panel unit root test (the Dickey–Fuller cross-sectional supplemented and the Im-Pesaran-Shin cross-sectional) were applied. Further, the panel Autoregressive Distributed Lag (ARDL) model (Bounds test) and pooled mean group (PMG) estimator were utilized in this work.
Findings
This shows that economic growth, debt, labor force and population have a positive relationship with unemployment in the long run. Therefore, an increase in these variables generates an increase in the selected African countries' unemployment growth. In contrast, inflation, FDI and gross capital formation have a negative relationship with unemployment in the long run, which implies that an increase in these variables reduces unemployment in the selected African countries.
Research limitations/implications
This study has potential limitations because some data from the countries are not up to date and some years are missing from the data.
Practical implications
This study contributes to understanding unemployment and Okun's law in the African economy. This study shows that an increase in economic growth leads to a rise in unemployment, while an increase in inflation leads to a decrease in unemployment.
Originality/value
This paper provides an insight into the major factors that increase and reduces unemployment for government and policy marker to take the adequate measure.
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This study aims to explore the long- and short-run effects of daily confirmed cases of COVID-19 (Ct) on daily stock returns (Rt) for Kuwait. This is the first study that was…
Abstract
Purpose
This study aims to explore the long- and short-run effects of daily confirmed cases of COVID-19 (Ct) on daily stock returns (Rt) for Kuwait. This is the first study that was applied to the case of Kuwait.
Design/methodology/approach
We employed the autoregressive distributed lag (ARDL) model of Pesaran et al. (2001) and the nonlinear autoregressive distributed lag (NARDL) model of Shin et al. (2001) for daily data over the period March 2020 to August 2021.
Findings
The findings first document the existence of a long-run relationship (cointegration). Second, the findings of the ARDL model show a significant positive long-run effect of daily confirmed cases of COVID-19 (Ct) on daily stock returns (Rt) but a significant negative short-run effect. As for the NARDL model, the findings showed that the increase and decrease of daily confirmed cases of COVID-19
Originality/value
To the best of the author’s knowledge, this is the first study that was applied to the case of Kuwait.
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Md Badrul Alam, Aziz Ullah Sayal, Muhammad Naveed Jan and Muhammad Tahir
This research paper attempts to empirically examine the relationship between the performance of the banking industry and foreign direct investment (FDI), thereby helping the…
Abstract
Purpose
This research paper attempts to empirically examine the relationship between the performance of the banking industry and foreign direct investment (FDI), thereby helping the readers contemplate one of the least explored areas of the existing literature associated with the idiosyncratic characteristics of FDI resulting from its interaction with the efficient banking performance of the host country. The study has focused on the economy of Bangladesh because of its significant amount of FDI inflows from the rest of the world and its adoption of many liberalization policies, especially in the banking sector and in the areas of international business and trade.
Design/methodology/approach
The study, to produce unbiased estimates, employed the autoregressive distributed lag (ARDL) model for analyzing the time series data collected from reliable sources.
Findings
The key outcomes of the study reveal that the sound performance of the banking industry appears to be counterproductive for FDI inflows, which is a bit unconventional insight. In the context of Bangladesh, trade openness, inflation rate and infrastructural development seem to be the dominant factors behind the rising inflows of FDI. Market size appears to be an insignificant determinant of FDI inflows.
Originality/value
This is a unique study because of its focus on the unexplored area in the literature.
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As supply chain excellence matters, designing an appropriate health-care supply chain is a great consideration to the health-care providers worldwide. Therefore, the purpose of…
Abstract
Purpose
As supply chain excellence matters, designing an appropriate health-care supply chain is a great consideration to the health-care providers worldwide. Therefore, the purpose of this paper is to benchmark several potential health-care supply chains to design an efficient and effective one in the presence of mixed data.
Design/methodology/approach
To achieve this objective, this research illustrates a hybrid algorithm based on data envelopment analysis (DEA) and goal programming (GP) for designing real-world health-care supply chains with mixed data. A DEA model along with a data aggregation is suggested to evaluate the performance of several potential configurations of the health-care supply chains. As part of the proposed approach, a GP model is conducted for dimensioning the supply chains under assessment by finding the level of the original variables (inputs and outputs) that characterize these supply chains.
Findings
This paper presents an algorithm for modeling health-care supply chains exclusively designed to handle crisp and interval data simultaneously.
Research limitations/implications
The outcome of this study will assist the health-care decision-makers in comparing their supply chains against peers and dimensioning their resources to achieve a given level of productions.
Practical implications
A real application to design a real-life pharmaceutical supply chain for the public ministry of health in Morocco is given to support the usefulness of the proposed algorithm.
Originality/value
The novelty of this paper comes from the development of a hybrid approach based on DEA and GP to design an appropriate real-life health-care supply chain in the presence of mixed data. This approach definitely contributes to assist health-care decision-makers design an efficient and effective supply chain in today’s competitive word.
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Ketki Kaushik and Shruti Shastri
This study aims to assess the nexus among oil price (OP), renewable energy consumption (REC) and trade balance (TB) for India using annual time series data for the time period…
Abstract
Purpose
This study aims to assess the nexus among oil price (OP), renewable energy consumption (REC) and trade balance (TB) for India using annual time series data for the time period 1985–2019. In particular, the authors examine whether REC improves India's TB in the context of high oil import dependence.
Design/methodology/approach
The study uses autoregressive distributed lags (ARDL) bound testing approach that has the advantage of yielding estimates of long-run and short-run parameters simultaneously. Moreover, the small sample properties of this approach are superior to other multivariate cointegration techniques. Fully modified ordinary least square (FMOLS) and dynamic ordinary least squares (DOLS) are also applied to test the robustness of the results. The causality among the series is investigated through block exogeneity test based on vector error correction model.
Findings
The findings based on ARDL bounds testing approach indicate that OPs exert a negative impact on TB of India in both long run and short run, whereas REC has a favorable impact on the TB. In particular, 1% increase in OPs decreases TBs by 0.003% and a 1% increase in REC improves TB by 0.011%. The results of FMOLS and DOLS corroborate the findings from ARDL estimates. The results of block exogeneity test suggest unidirectional causation from OPs to TB; OPs to REC and REC to TB.
Practical implications
The study underscore the importance of renewable energy as a potential tool to curtail trade deficits in the context of Indian economy. Our results suggest that the policymakers must pay attention to the hindrances in augmentation of renewable energy usage and try to capitalize on the resulting gains for the TB.
Social implications
Climate change is a major challenge for developing countries like India. Renewable energy sector is considered an important instrument toward attaining the twin objectives of environmental sustainability and employment generation. This study underscores another role of REC as a tool to achieve a sustainable trade position, which may help India save her valuable forex reserves for broader objectives of economic development.
Originality/value
To the best of the authors’ knowledge, this is the first study that probes the dynamic nexus among OPs, REC and TB in Indian context. From a policy standpoint, the study underscores the importance of renewable energy as a potential tool to curtail trade deficits in context of India. From a theoretical perspective, the study extends the literature on the determinants of TB by identifying the role of REC in shaping TB.
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Claire Nolasco Braaten and Lily Chi-Fang Tsai
This study aims to analyze corporate mail and wire fraud penalties, using bounded rationality in decision-making and assessing internal and external influences on prosecutorial…
Abstract
Purpose
This study aims to analyze corporate mail and wire fraud penalties, using bounded rationality in decision-making and assessing internal and external influences on prosecutorial choices.
Design/methodology/approach
The study analyzed 467 cases from 1992 to 2019, using data from the Corporate Prosecution Registry of the University of Virginia School of Law and Duke University School of Law. It examined corporations facing mail and wire fraud charges and other fraud crimes. Multiple regression linked predictor variables to the dependent variable, total payment.
Findings
The study found that corporate penalties tend to be lower for financial institutions or corporations in countries with US free trade agreements. Conversely, penalties are higher when the company is a U.S. public company or filed in districts with more pending criminal cases.
Originality/value
This study’s originality lies in applying the bounded rationality model to assess corporate prosecutorial decisions, unveiling external factors’ influence on corporate penalties.
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William Obeng-Amponsah and Erasmus Owusu
This study examines the effect of foreign direct investment (FDI) on employment and economic growth in Ghana and examines the role of technology in these relationships.
Abstract
Purpose
This study examines the effect of foreign direct investment (FDI) on employment and economic growth in Ghana and examines the role of technology in these relationships.
Design/methodology/approach
This study applied the autoregressive distributed lag (ARDL) bounds testing approach to cointegration and Granger causality tests to data from 1995 to 2017.
Findings
Based on the empirical analysis, the key findings are as follows: FDI does not affect economic growth or employment in Ghana. However, technology moderates the relationship between FDI and economic growth and FDI and employment in the short run. The study also finds that technology exerts a positive effect on economic growth in both short and long run, whereas trade has a significantly negative effect on economic growth in Ghana.
Research limitations/implications
The greatest constraint that faced the authors is the nonavailability of data,.
Practical implications
The transfer of technology agreement enshrined in the GIPC Act should be made more robust and unambiguous, to make it a strict requirement for MNEs to be allowed to operate in Ghana. This increases Ghana's gains from FDI inflow.
Social implications
The GIPC should tighten its monitoring regime so that MNEs do not exceed their expatriate employment quotas. This will ease the burden of unemployment among the youth in Ghana.
Originality/value
This study adds a new dimension to the literature on the impact of FDI on emerging economies by examining the role of technology in the association between FDI and growth, and FDI and employment.
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Arshdeep Singh, Kashish Arora and Suresh Chandra Babu
Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate…
Abstract
Purpose
Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.
Design/methodology/approach
This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.
Findings
The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.
Originality/value
The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.
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