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Article
Publication date: 1 December 1999

M.R. Rotab Khan

A methodology of structuring a garment production simulation model using a spreadsheet is described to minimize the average daily production cost through the investigation…

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Abstract

A methodology of structuring a garment production simulation model using a spreadsheet is described to minimize the average daily production cost through the investigation of various man‐machine combinations. The capability and usability of an easily available modern spreadsheet Excel 7.0 to simulate a simple garment production system is accessed with an attempt to demonstrate the simulation model building in a user friendly environment rather than learning and using costly simulation programming languages or simulation software packages. Simulation has evaluated the resource utilization and measured the system performance and developed strategies for taking operational decisions in a logical and better way to minimize the garment production cost. It may also assist and benefit the garment production managers to plan, design and operate their systems in an efficient manner in a competitive environment.

Details

International Journal of Clothing Science and Technology, vol. 11 no. 5
Type: Research Article
ISSN: 0955-6222

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Article
Publication date: 26 August 2022

Samson Edo, Oluwatoyin Matthew and Ifeoluwa Ogunrinola

The purpose of this study is to determine the impact of disaggregate official development aid (ODA) on economic growth, and ascertain whether bilateral and multilateral…

Abstract

Purpose

The purpose of this study is to determine the impact of disaggregate official development aid (ODA) on economic growth, and ascertain whether bilateral and multilateral aid played complementary role with private sector, government sector and external sector in driving growth of sub-Saharan African economies.

Design/methodology/approach

The role of bilateral and multilateral aid in economic growth of sub-Saharan Africa (SSA) is investigated in this study. The vector error correction model (VECM) and generalized method of moments (GMM) techniques are employed in estimating the short-run and long-run impacts, over the period 1980–2020.

Findings

The estimation results reveal that the effect of bilateral aid is positive, and more significant than multilateral aid. Their effect on economic growth is, however, less significant than the effects of domestic private investment and government spending. Nonetheless, aid complemented private and government sectors in facilitating growth. External trade is the only exogenous variable in estimation that is insignificant. The results further reveal that economic growth is unable to significantly respond to its own lag. Generally, the estimation results conform to theoretical expectations.

Practical implications

One major implication of the findings is that SSA countries have benefited substantially from development aid. It is, therefore, important for these countries to develop stronger institutions that would attract more inflows of development aid.

Originality/value

The study was motivated by the fact that less attention has been given to the role of disaggregate ODA in economic growth of African countries. Previous research works have tended to focus more on aggregate ODA. Furthermore, adequate research has yet to be done on how ODA complements the private sector, government sector and external sector in facilitating growth of African countries. These issues are investigated in the study.

Details

African Journal of Economic and Management Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-0705

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Book part
Publication date: 18 July 2022

Payal Bassi and Jasleen Kaur

Introduction: The insurance industry has unprecedented growth, and the demand for insurance has outgrown in the recent past due to the prevailing pandemic. The companies…

Abstract

Introduction: The insurance industry has unprecedented growth, and the demand for insurance has outgrown in the recent past due to the prevailing pandemic. The companies have a large base of the data set at their disposal, and companies must appropriately handle these data to come out with valuable solutions. Data mining enables insurance companies to gain an insightful approach to map strategies and gain competitive advantage, thus strengthening the profits that will allow them to identify the effectiveness of back-propagation neural network (BPNN) and support vector machines (SVMs) for the companies considered under study. Data mining techniques are the data-driven extraction techniques of information from large data repositories, thus discovering useful patterns from the voluminous data (Weiss & Indurkya, 1998).

Purpose: The present study is performed to investigate the comparative performance of BPNNs and SVMs for the selected Indian insurance companies.

Methodology: The study is conducted by extracting daily data of Indian insurance companies listed on the CNX 500. The data were then transformed into technical indicators for predictive model building using BPNN and SVMs. The daily data of the selected insurance companies for four years, that is, 1 April 2017 to 21 March 2021, were used for this. The data were further transformed into 90 data sets for different periods by categorising them into biannual, annual, and two-year collective data sets. Additionally, the comparison was made for the models generated with the help of BPNNs and SVMs for the six Indian insurance companies selected under this study.

Findings: The findings of the study exhibited that the predictive performance of the BPNN and SVM models are significantly different from each other for SBI data, General Insurance Corporation of India (GICRE) data, HDFC data, New India Assurance Company Ltd. (NIACL) data, and ICICIPRULI data at a 5% level of significance.

Book part
Publication date: 19 July 2022

Jasleen Kaur and Payal Bassi

Introduction: The insurance industry is one of the lucrative sectors of the economy. However, it is volatile because of the large chunk of data generated by the…

Abstract

Introduction: The insurance industry is one of the lucrative sectors of the economy. However, it is volatile because of the large chunk of data generated by the transactions taking place daily. However, every bit of it is responsible for creating market trends for stock investors to predict the returns. The specialised data mining techniques act as a solution for decision-making, reducing uncertainty in decision-making.

Purpose: There are limited studies that have examined the efficiency and effectiveness of data mining techniques across the companies in the insurance industry to date. To enable the companies to take exact benefit of data mining techniques in insurance, the present study will focus on investigating the efficiency of artificial neural network (ANN) and support vector machine SVM across insurance companies of CNX 500.

Method: For predictive models, various technical indicators were considered independent variables, and change in return, i.e. increase and decrease, was deemed a dependent variable. The indicators were transformed from daily raw data of insurance company’s stock values spanning four years. We formed 90 data sets of varied periods for building the model – specifically six months, one year, two years, and four years for selected six insurance companies.

Findings: The study’s findings revealed that ANN performed best for the ICICIPRULI data model in terms of hit ratio. Whereas the performance of SVM was observed to be the best for the ICICIGI data model. In the case of pairwise comparison among the six selected Indian insurance companies from CNX 500, the extracted data evaluated and concluded that there were eight significantly different pairs based on hit ratio in the case of ANN models and nine significantly different pairs based on hit ratio for SVM models.

Book part
Publication date: 21 October 2019

Peterson K. Ozili

This chapter provides a discussion on some issues in blockchain finance that regulators are concerned about – an area which bitcoin promoters have remained silent about…

Abstract

This chapter provides a discussion on some issues in blockchain finance that regulators are concerned about – an area which bitcoin promoters have remained silent about. Blockchain technology in finance has several benefits for financial intermediation in the financial system; notwithstanding, several issues persist which if addressed can make the adoption of blockchain technology in finance easier and accepted by regulators. The blockchain issues discussed in this chapter are relevant for recent debates in blockchain finance.

Details

Disruptive Innovation in Business and Finance in the Digital World
Type: Book
ISBN: 978-1-78973-381-5

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Book part
Publication date: 19 October 2020

Pablo Estrada and Leonardo Sánchez-Aragón

Financial contagion refers to the propagation of shocks that can generate widespread failures. The authors apply a financial contagion model proposed by Elliott, Golub…

Abstract

Financial contagion refers to the propagation of shocks that can generate widespread failures. The authors apply a financial contagion model proposed by Elliott, Golub, and Jackson (2014) to a cross-shareholding network of firms in Ecuador. The authors use a novel dataset to study the potential channels for contagion. Although diversification is not high, results reveal enough conditions for a contagion event to occur. However, the low level of integration attenuates the effects of shocks. The authors run simulations affecting a particular firm at the time, and find that two firms coming from the finance and trade industry cause the highest contagion. In addition, when an entire industry receives a shock, trade and manufacturing industries contagion more companies than the rest. Finally, the model can assist policymakers to monitor the market and evaluate the fragility of the network in different scenarios.

Details

The Econometrics of Networks
Type: Book
ISBN: 978-1-83867-576-9

Keywords

Book part
Publication date: 23 October 2017

Julius Horvath and Alfredo Hernandez Sanchez

In the domestic credit market creditor and debtor rights are clearly defined. In contrast, sovereign debt repayment is largely contingent on the debtor government’s…

Abstract

In the domestic credit market creditor and debtor rights are clearly defined. In contrast, sovereign debt repayment is largely contingent on the debtor government’s willingness to repay as enforcement of contracts at the international level is limited. In this chapter we explore different sources of sovereign debt crises as opportunistic and myopic behavior by debtor nations, over-consumption of imported goods, credit temptation by lenders eager to allocate savings surpluses, and unexpected consequences of initially seen appropriate policies. We explore how these factors have played out in the Euro-debt crisis and outline a framework for creditor responsibility to complement debtor self-restraint.

Details

Economic Imbalances and Institutional Changes to the Euro and the European Union
Type: Book
ISBN: 978-1-78714-510-8

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Book part
Publication date: 24 October 2019

Deniz Ilalan and Burak Pirgaip

Since the famous tapering talk of Bernanke, US Dollar (USD) made a significant appreciation on emerging market local currencies. When the stock indices are adjusted to…

Abstract

Since the famous tapering talk of Bernanke, US Dollar (USD) made a significant appreciation on emerging market local currencies. When the stock indices are adjusted to USD, a negative relationship is usually the case. USD index is a natural candidate for measurement of these effects. It is seen that some emerging stock indices exhibit negative causality with USD index in Granger sense. Moreover, the authors take into account rolling correlations of USD index and the relevant stock indices and examine them on the investment horizon beginning from tapering talk. The authors deduce that Granger causality test and correlation results are coherent with each other which sheds light to the famous discussion whether causality implies correlation or vice versa.

Book part
Publication date: 3 October 2022

Taufik Faturohman and Rashifa Qanita Noviandy

Capital structure is vital to every company because it has a huge impact on the company’s financial decisions. The ultimate goal of the company is to effectively mix the…

Abstract

Capital structure is vital to every company because it has a huge impact on the company’s financial decisions. The ultimate goal of the company is to effectively mix the debt-to-equity ratio (DER) to maximize the shareholder value. When the Covid-19 pandemic was officially announced in early March 2020, widespread negative effects started to affect almost all industries in Indonesia. The hotel, restaurant, and tourism industry is considered to be one of the most severely affected industry categories. It is important to pay attention to the role of this industry in Indonesia’s overall economy as it contributes to Indonesia’s gross domestic product at 6.1% in 2019. The objective of this study was to address the effects on the formation of capital structure of firm-specific characteristics among a sample of 26 active hotels, restaurants, and tourism companies listed on the Indonesia Stock Exchange. The authors used the data from the second and third quarters of 2019 to represent the period before the pandemic. Meanwhile, the period during the pandemic is represented by the data from the second and third quarters of 2020. Using the random-effects model to test the hypotheses, the authors found that asset tangibility, tax shield, and earnings volatility had significant positive correlations with book leverage. Furthermore, tax shield and earnings volatility had significantly positive relationships with DER. The authors also detected that size and earnings volatility had significant negative correlations with net equity. However, the authors found no significant relationship between capital structure and the pandemic dummy. It was inferred from the results that the pandemic had no effect on capital structure within the research period.

Details

Quantitative Analysis of Social and Financial Market Development
Type: Book
ISBN: 978-1-80117-921-8

Keywords

Book part
Publication date: 2 September 2020

Ercan Özen and Metin Tetik

Introduction – Emerging markets are under the influence of many external factors in global market conditions. International interest rates and price fluctuations in major…

Abstract

Introduction – Emerging markets are under the influence of many external factors in global market conditions. International interest rates and price fluctuations in major stock market indices are also among these factors. The FED policies shape the international capital movements in particular, which significantly affects the emerging markets. For this reason, emerging stock markets may show different reactions especially in times of crisis.

Purpose – The purpose of this study is to investigate whether the BIST30 index acted in accordance with the overreaction hypothesis (ORH) against the return changes in the Dow Jones Industrial Average (DJIA) index in the process of the 2008 global financial crisis.

Methodology – The data set of the study was analysed by dividing it into two periods. The first period is the monetary expansion period between 17 August 2007, when the Federal Reserve (FED) reduced the interest rate for the first time, until 22 May 2013 when the FED announced that it would reduce the bond purchases. The second period is the monetary contraction period including the dates between 23 May 2013 and 1 June 2017. An error correction model (ECM) was established in both periods for the indices, determined as cointegrated. The validity of the ORH was tested by Cumulative Abnormal Return (CAR) Analysis.

Findings – According to the ECM, the authors identified that the effect of short-term changes in the DJIA return in the monetary expansion period on BIST30 index return was higher than that in the monetary contraction period. However, according to the findings obtained from the CAR analysis results, the BIST30 index did not generally act in accordance with the ORH against the DJIA. Findings can be appreciated as a decision-making tool especially for investment specialists and investors interested in securities investments.

Details

Contemporary Issues in Business Economics and Finance
Type: Book
ISBN: 978-1-83909-604-4

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