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Cross Country Analysis of Online Banking Service Quality in South Africa and Indonesia
Johan W de Jager, Nuri Wulandari, and Elizma Wannenburg
DOI: 10.15604/ejef.2020.08.04.001
Abstract
Since the introduction of automatic teller machines, the online banking industry have evolvedrapidly in order to stay abreast of today’s digital savvy customers. By keeping up to date with changes in the external environment as well as consumer needs can elevate the competitive advantage of banks. With that in mind, banks need to ensure that the service quality of the online banking services meets the expectations of its customers. The objective of the study is to evaluateand investigate the online banking customers’ perceptions of the service quality of banks in SouthAfrica (SA) and Indonesia (INA). A survey was conducted among more than 300 respondents from both countries. The results revealed that within the eight dimensions of online bankingservice quality, each of the countries have different experiences when it comes to “high tech” versus “high touch”. The study has also found significant differences between the perceptions of both SA and INA’s banking customers. By understanding the perceptions of online bankingcustomers in two developing countries can assist financial institutions with the development of new services or technologies that will enhance the online banking experience.
Keywords: Service Quality, Online Banking, Service Marketing, South Africa, Indonesia
Regional Technological Learning in Turkish Cement Industry
Gurkan Calmasur and Meryem Emre Aysin
DOI: 10.15604/ejef.2020.08.04.002
Abstract
The learning curve reflects the reduction in average costs as the company’s cumulative production increases. These curves are utilized when measuring company performance, managing production processes, and planning. In terms of cost reduction and profitability, the impact of learning is particularly important. The learning curves have been traditionally used in industries. In this study, the learning curves concerning the cement industry are examined. The cement sector inherits a high export potential in Turkey. Additionally, it is the industry branch that supplies the raw materials needed by countries’ construction industries. On the other hand, the construction sector is a leading sector that mobilizes other markets. This sector is a major contributor to production, investment, and employment and plays a vital role in the development of the country. This paper aims to make a detailed analysis of the learning curves regarding the Turkish cement industry at the regional level covering the 2000-2018 period. In order to realize this aim, the linear and cubic learning models have been applied and the technological learning values for regions from 2000 to 2018 have been calculated. For the analysis, data of 68 factories operating in the Turkish cement industry obtained from Turkey Cement Manufacturers’ Association have been used. The estimated results suggest that cubic models explain technological learning better than the linear models. The results indicated that learning levels differed across regions and times. While the highest learning level was observed in 2004, the highest level of forgetting was recorded in 2018. Finally, we can state that the learning curve of the Turkish cement industry between 2000 and 2018 is convex.
Keywords: Learning Curve, Technological Learning, Cement Industry, Turkey
A Reconsideration of the Health Status – Economic Growth Nexus: Evaluation of the Gender Differential Effect in Nigeria
Olufunmilayo Olayemi Jemiluyi and Ifeoluwa Alao-Owunna
DOI: 10.15604/ejef.2020.08.04.003
Abstract
It is tempting to say that the health status-economic growth literature in Nigeria is exhaustive due to the large body of extant studies. However, gaps exist on the gender perspective to the relationship between health status and economic growth in Nigeria as the literature largely examined the relationship at the aggregate. Therefore, this study seeks to explore the gender dimension to the health-economic growth nexus in Nigeria using gender-disaggregated data on longevity. Applying the dynamic ordinary least square (DOLS) to the time series for the period between 1981 and 2018, the findings suggest there is gendered difference in the effect of male and female life expectancy at birth on economic growth. Specifically, the results show that male life expectancy at birth is positively correlated to economic growth while there is evidence of a negative relationship between female life expectancy at birth and economic growth. Also, foreign investment and credit to private sector were found to be negatively correlated with economic growth while the urbanization rate was found to have economic growth premium in the study period.
Keywords: Health Status, Economic Growth, Female Life Expectancy at Birth, Male Life Expectancy at Birth, Nigeria
Implications of Capital Flows for Domestic Credit Growth: Evidence from Panel Data Analysis
Aylin Soydan and Serap Bedir Kara
DOI: 10.15604/ejef.2020.08.04.004
Abstract
Following the 2007-2009 global crisis, high credit growth became an issue of concern with an emphasis on its relationship with capital flows. It is argued that large and volatile international capital flows lead to credit expansion, which in turn, may cause economic and financial instabilities when it reaches excessive levels, particularly in developing countries. This paper aims to investigate the association between credit growth and capital inflows in the context of developing countries by using panel data analysis. The methodology employed in the study offers a number advantages by allowing for heterogeneity and cross-sectional dependence in the panel, while also considering the endogeneity issue. The overall results of the study provides evidence for the impact of capital inflows, more particularly other capital inflows, on credit growth in the sample. This finding suggests a more direct relationship between capital inflows and credit creation as other inflows mostly comprise international banking and trade credits. It is not surprising given the fact that banking sector has a critical role in the financial systems of developing countries. The significance of international dimension for credit creation through other capital inflows and the intermediary role of the banking system should have monetary policy implications, in the macroprudential or more conventional fashion.
Keywords: Credit Growth, Capital Flows, Developing Economies, Common Correlated Effects Estimator
Limited Availability in Crowdfunding Projects – Guarantee for Profitability?
Alexander Fox and Jana Neuland
DOI: 10.15604/ejef.2020.08.04.005
Abstract
Scarcity is an instrument that is often used in crowdfunding. Crowdfunding is an alternative form of financing, especially for entrepreneurs in the early-stage development phase. This paper deals with the characteristics of profitable crowdfunding projects. Hereby, we examine the impact factors of crowdfunding’s profitability, with a special focus on limited availability (scarcity), depth of project description and the size of pledging goals as follows. Therefore, we analyze data from kickstarter.com, one of the world’s largest crowdfunding platforms, and used 494 projects and 4,224 pledge levels from the broad category technology as our database. Technology projects lend themselves particularly well to the study, as they usually contain the project result as a tangible return, thus facilitating or even enabling the monetary evaluation of the success in contrast to, for example, cultural projects. Hence, our sample includes 32% of pledge levels with limited availability. We provide empirical evidence that the limited availability in the crowdfunding projects in terms of scarcity management is positively related to the profitability of the included pledge levels. We conclude that crowdfunding projects with limited availability on pledge levels are more profitable for investors.
Keywords: Crowdfunding, Scarcity Management, Profitability, Determinants
Remittances and Economic Development: Evidence from SADC Countries
Courage Mlambo and Forget Kapingura
DOI: 10.15604/ejef.2020.08.04.006
Abstract
This study sought to examine the effects of remittances on economic development on selected SADC states. Remittances are important for the survival of poor individuals, households and societies around the world. The funds sent by migrants are a crucial means of survival that can assist families in buying food, sending children to school and building basic shelter. Given the poor economic development in these SADC countries and the probable development outcomes of remittances, remittances income should be critical to the SADC countries. However, literature shows that relationship between remittances and development is not always clear. Remittances may bring positive or negative effects. It is against this background that this study sought to examine the effects of remittances on economic development on selected SADC states. The study used panel data and the sample included five SADC countries (Zimbabwe, Mozambique, Lesotho, Eswatini and DRC) for the years 2005-2015. The study used a Fixed effects model, random effects model and a GMM approach to estimate the effects of remittances and economic development. Results showed that remittances have a positive effect with economic development. This finding suggests that remittance inflows are able to stimulate economic development. The study recommended that the government put in place policies that enhance the remittances transformation to economic development.
Keywords: Remittances, Economic Development, Poverty, Cross Border Income, Migration
Problems of Small and Mid-Sized Enterprises in Japan’s Software Industry
Mita Takahashi
DOI: 10.15604/ejef.2020.08.04.007
Abstract
This paper examines the reasons that most small and mid-sized enterprises (SMEs) in Japan’s software industry do not develop into large firms. Thousands of SMEs are informally organized under several large companies. Those SMEs have experienced difficulty developing into large firms. This industrial structure has remained for several decades. Several papers have already suggested reasons for this phenomenon, but each paper in the literature has given few reasons. This paper analyzes the issue more comprehensively. First, this article surveys the literature and determine several factors that contribute to the issue. Then, this paper demonstrates how they complicate the issue and make it difficult to solve. Finally, the paper illustrates several approaches in an effort to find solutions. The first method is introducing agile modeling and other iterative software development processes. Agile modeling adjusts design change more easily compared with other software development processes. Other iterative software development processes also adjust design change easily compared to the waterfall model. By using these processes, software engineers can avoid long overtime work, which contributes to the difficulties in securing human resource. The second method is for software firms to demand appropriate compensation for each design change. If many Japanese firms did this, overtime work would be shorter, and the working environment of SMEs would improve. Then, SMEs obtain excellent workers. This will help SMEs to grow to large firms.
Keywords: Software Industry, SMEs, Japan, Custom Software
Determinants of Sovereign Credit Ratings: An Application of the Naïve Bayes Classifier
Oliver Takawira and John W. Muteba Mwamba
DOI: 10.15604/ejef.2020.08.04.008
Abstract
This is an analysis of South Africa’s (SA) sovereign credit rating (SCR) using Naïve Bayes, a Machine learning (ML) technique. Quarterly data from 1999 to 2018 of macroeconomic variables and categorical SCRs were analyzed and classified to predict and compare variables used in assigning SCRs. A sovereign credit rating (SCR) is a measurement of a sovereign government’s ability to meet its financial debt obligations. The differences by Credit Rating Agencies (CRA) on rating grades on similar firms and sovereigns have raised questions on which elements truly determine credit ratings. Sovereign ratings were split into two (2) categories that is less stable and more stable. Through data cross-validation for supervised learning, the study compared variables used in assessing sovereign rating by the major rating agencies namely Fitch, Moody’s and Standard and Poor’s. Cross-validation splits the dataset into train set and test set. The research applied cross-validation to reduce the effects of overfitting on the Naïve Bayes Classification model. Naïve Bayes Classification is a Machine-learning algorithm that utilizes the Bayes theorem in classification of objects by following a probabilistic approach. All variables in the data were split in the ratio of 80:20 for the train set and test set respectively. Naïve Bayes managed to classify the given variables using the two SCR categories that is more stable and less stable. Variables classified under more stable indicates that ratings are high or favorable and those for less stable show unfavorable or low ratings. The findings show that CRAs use different macroeconomic variables to assess and assign sovereign ratings. Household debt to disposable income, exchange rates and inflation were the most important variables for estimating and classifying ratings.
Keywords: Sovereign Credit Rating, Naïve Bayes, Machine Learning, Macroeconomic Variables
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