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5G and banking
(PressAcademia, 2021-12-31) Teker, Suat; Teker, Dilek; Orman, Irmak
Purpose- Technological developments in mobile telecommunications have evolved immensely after the transition from analog technologies that were widely used in 1980s to digital technologies connecting to globe with wireless cellular technologies. This study intends to review telecommunication technologies starting 1970s (1G technology) through 2020s (5G technology) and analyze the expected effects of 5G technology on the future of banking sector. In addition, it is envisioned how 5G technology will shape the future of the banking industry. Methodology- The study is conducted by having a comparative review of digital technology developments in the last 50 yearsThis study examines the effects of developments in communication technologies on the banking sector and banking services. The research design of this study is the relationship between the advancements in telecommunication technologies and the future of banking sector. The following section cover the comparison of 1G-2G-3G-4G-5G Technologies. Findings- 5G banking featuring video communication, data protection and digital wallets will create a permanent shift for banking customers and their habits. Globally, bank customers are adopting to digital apps as their primary touchpoint for their banks and this transformation will change the structure of bank branches as well as financial services industry. As a result of the analysis, it has been observed that an important innovation and structural transformation period has been entered in the banking sector with the use of 3G and 4G compared to the year before 2000, which we define as traditional banking era. Conclusion- With the wide use of 5G technology after year 2022, the banking sector is expected to enter a new and disruptive restructuring and service innovation. 5G is expected to carry the banking industry to another level where automation and machine-to-machine communication act as a game changer.
5G technology and future of banking
(The Brooklyn Research and Publishing Institute, 2021-12) Teker, Suat; Teker, Dilek; Orman, Irmak
This study examines the effects ofdevelopments in communication technologies on the banking sector and banking services. In addition, it is envisioned how 5G technology will shape the future of the banking industry. As a result of the analysis, it has been observed that an important innovation and structural transformation period was lived in the banking sector with the use of 3G and before 2000, which we define as traditional banking era. It is concluded that with the expected wide use of 5G technology after year 2022, the banking sector is expected to enter a new and disruptive restructuring and service innovation.
AB-27 ülkeleri ve Türkiye'de ekonomik büyümeyi etkileyen faktörlerin belirlenmesi: statik panel veri modeli uygulaması
(2014) Pala, Aynur; Teker, Dilek
Bu çalışmada, 2000-2011 yıllarına ilişkin EU-27 ülkeleri ve Türkiye için ekonomik büyümeyi etkileyen faktörlerin belirlenmesi amaçlanmıştır. Analizde, gayri safi milli hasıla (GSYİH) büyümesi, nüfus artışı, bankacılık sektörünün yurtiçine sağladığı kredilerinin GSYİH'ye oranı, özel sektör kredilerinin GSYİH'ye oranı, dış ticaret hacminin GSYİH'ye oranı, tüketici enflasyonu ve net tasarrufların Gayri Safi Milli Hasıla (GSMH)'ya oranı değişkenleri kullanılmıştır. Ekonometrik model statik panel veri regresyonu ile tahmin edilmiştir. Model sonuçlarına göre, ekonomik büyüme üzerinde, nüfus artışı, özel sektör kredilerinin GSYİH'ye oranı, net tasarrufların GSMH'ye oranı değişkenleri pozitif yönde etkili iken, tüketici enflasyonu ve bankacılık sektörünün yurtiçine sağladığı kredilerinin GSYİH oranı gibi değişkenler negatif yönde etkilidir.
Backcasting Bitcoin prices: implementation with ARCH & GARCH models
(International Journal of Economics, Commerce and Management, 2024-12) Teker, Dilek; Teker, Suat; Demirel Gümüştepe, Esin
Bitcoin, the first decentralized cryptocurrency, has gained popularity among investors for several reasons. Its potential for high returns makes it attractive to those seeking alternatives to traditional investments. Bitcoin's volatility provides both risk and reward, drawing in speculative investors. Moreover, Bitcoin operates independently of central banks or governments, appealing to those wary of inflation and economic instability. As more businesses and financial institutions adopt Bitcoin as an investment tool and a medium of exchange, its appeal continues to grow. For institutional investors, Bitcoin offers a way to diversify portfolios amid low interest rates and geopolitical uncertainty. However, the volatility in Bitcoin markets tends to be a risk exposure, so developing models to understand Bitcoin fluctuations is crucial to determining more about market behavior. Accurate financial models help predict price movements, manage risk, and identify macroeconomic correlations. Given its complexity, these models are essential for long-term investors to navigate volatility and optimize their investment strategies. This research employs ARCH and GARCH models to forecast Bitcoin volatility. The outputs indicate that ARIMA is the best fit model that explains Bitcoin’s price fluctuations in the selected data period.
Backcasting Bitcoin volatility: ARCH and GARCH approaches
(Suat Teker, 2024-12-31) Teker, Dilek; Teker, Suat; Demirel Gümüştepe, Esin
Purpose- The primary purpose of this study is to model Bitcoin price volatility and forecast its future price returns using advanced econometric models such as ARCH and GARCH. The study aims to enhance risk management strategies and support informed investment decisions by addressing the time-varying nature of Bitcoin’s volatility. The research explores the persistence of volatility shocks and the clustering of price movements to provide insights into market dynamics. Methodology- This research examines daily Bitcoin closing prices over the period from January 2020 to October 2024. The data was preprocessed to ensure reliability, including applying logarithmic transformations to standardize the data and eliminate trends. Stationarity tests, such as the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), and KPSS tests, were conducted to confirm the series' stationarity. The ARCH-LM test was utilized to detect volatility clustering which is essential for validating the use of ARCH and GARCH models. Following this, ARIMA models were employed to define mean equations and GARCH models were used to estimate conditional variance and capture volatility dynamics. The dataset was split into training and validation subsets with data from July to October 2024 reserved for validation. Findings- The findings demonstrate that Bitcoin’s price movements exhibit significant volatility clustering and persistence of shocks which are key characteristics effectively captured by ARCH and GARCH models. These models provide valuable insights into the volatility patterns of Bitcoin, supporting their application in cryptocurrency analysis. Despite their robustness, the models face limitations in precise return forecasting during highly volatile periods, suggesting the need for further refinement or integration with advanced approaches. Conclusion- The research concludes that ARCH and GARCH models are effective tools for understanding and forecasting Bitcoin’s volatility. The study underscores the importance of acknowledging volatility persistence and clustering effects when analyzing cryptocurrency price behavior. However, it also highlights areas for improvement in econometric modelling by including the exploration of hybrid models and the integration of macroeconomic factors to enhance forecasting accuracy.
Causal relations among macroeconomic variables under various exchange rate levels: an implementation of threshold vector autoregression model
(EconJournals, 2018-07-04) Teker, Dilek; Teker, Suat; Aykaç, Alp, Elçin
The paper examines interaction between selected macroeconomic determinants such as exchange rates, stock exchange market indexes, gold prices, money supply and inflation rates. Considering a nonlinear relationships in various macroeconomic indicators, a threshold vector autoregression (AVR) model is implemented. The data covers a period from 2003:01 to 2017:07. The results of the analysis points out the relationship between those macroeconomic indicators above and below the specific threshold value for exchange rate. The estimations indicate that policy maker may use monetary variables as policy variable for the stability of this system if they do not ignore the level of exchange rate.
A comparative study for appoinment procedures of university presidents
(European Journal of Business and Social Sciences, 2013-11) Teker, Suat; Teker, Dilek; Sayan, Pınar
The administration structure plays a central role in the development of a university, both academically and administratively, and both for attracting qualified academic staff and students. The role of presidents (chancellors/ rectors) and their selection procedures are crucial in the organizational structur e of a university. Considering that selection processes provide critical clues about the democratic culture of institutions in the name of representativeness, accountability, transparency, and participation; the issue demands more attention since these values should constitute the fundamental basis of all universities. This study deals with this important aspect of the administration structure and aims to explore the selection procedures of university presidents in the United States and the United Kingdom, and then compare these procedures with the ones in Turkey, underlying the similarities and differences.
The Covid 19 effect on macroeconomic indicators
(PressAcademia, 2020-12-31) Deniz, E. Asena; Teker, Dilek
Purpose- From the moment covid 19 started to spread in the world, its effects began to be seen simultaneously in financial markets and economy.The purpose of this study is to observe Covid 19 effect on EURO/USD,gold ,oil and wheat prices. Methodology- The database includes the Daily prices of EUR/USD, wheat ,gold , brent oil prices and COVİD 19 numbers between the period of 31.12.2019-04.09.2020 which consist of 180 daily data. Natural logaritm for each indicator is used. First, the stationarity of the series were analyzed with ADF (Augmented Dickey Fuller) unit root test. Lag lengths are determined. Interactions between the series were analyzed by theARDL, Impulse- Response Function and Variance Decomposition method. Findings- The series are found out to not to be stationary as a result of Unit root test.After, the lag length criteria using VAR models were checked and this lag length criteria for them were determined as one . According to the ARDL test result, cointegration could not be found between our data. Impulse response graphs indicate that all variables respond in a reducing way to reducing shocks occurred in each indicator. Shocks have lost their effect on average in 2 days. Conclusion- The results indicate that the effect of COVID 19 on EUR/USD , gold , brent oil and wheat prices do not have a strong effect. The results may be beneficial for only literatüre.
Crypto currency applications in financial markets: factors affecting crypto currency prices
(PressAcademia, 2020-07-30) Deniz, E. Asena; Teker, Dilek
Purpose- As the cryptocurrency market is beginning to attract investors, a new portfolio of cryptocurrencies has been published in the literature on macro-economic factors affecting these currencies. This research also aimed to identify the interaction between gold, brent oil, Bitcoin, Ethereum and Ripple. Methodology- The database includes the Daily prices of Bitcoin, Ethereum, Ripple, gold and brent oil prices between the period of 03.04.2018-31.12.2020 which consist of 500 daily data. Natural logaritm for each indicator is used. First, the stationarity of the series were analyzed with ADF (Augmented Dickey Fuller) unit root test. Lag lengths are determined. Interactions between the series were analyzed by the Johansen Cointegration test, Granger Causality test, Impulse- Response Function and Variance Decomposition method. Findings- The series are found out to be stationary at first difference. According to the cointegration test result, cointegration could not be found between our data. According to Granger causality analysis, only one-way relationship was found from bitcoin to gold. Impulse response graphs indicate that all variables respond in a reducing way to reducing shocks occurred in each indicator. Shocks have lost their effect on average in 2 days. Conclusion- The results indicate that the effect of gold and brent oil prices on bitcoin, ethereum, ripple daily prices do not have a strong effect. The results may be beneficial for investors to consider diversification for the portfolios.
Cryptocurrencies and regulations: a comparative framework for international implementations
(PressAcademia, 2023-02-01) Ozak, Ceyda; Teker, Dilek
Purpose- The recent developments in technology have created a remarkable increase in the financial markets. The decentralization of crypto assets and the price movements attract investors attention as an demanding financial instrument. Since the beginning of pandemics, inflation is one of the major macroeconomic issue in the globe that push the investors to seek for new investment opportunities. Perhaps the positive perception regarding the cryptocurrency investment is its protection from inflation. In addition cost-effective mode of transaction and easy transfer of funds make these instruments unique. On the other hand, it can also lead to unsolicited consequences such as money laundering, illegal purchases, and the elimination of corruption. In this context, regulations are being formed to bring crypto assets, which attract the attention of experts, into compliance with the tax and trade-related laws of countries in the financial system. In this study, it is aimed to convey the importance of regulation and regulations on the world. Methodology- Since the first launch of Bitcoin as a cryptocurrency in 2009; the recent discussion came forward on how to regulate this market. Understanding cryptocurrency takes time and effort while they are extremely volatile investment. The crypto money applications of the countries and their taxation and approaches towards these applications have been evaluated by examining the official reports of the countries. Findings- Countries' perspectives on crypto money, the concept and definitions of crypto money vary. Some accept the cryptocurrencies as legal investment tools and draw a legal framework, while some announce that they eliminate these investments. Perhaps developing a framework can help to regulate both actors and also the transactions in the crypto ecosystem. National authorities plan to take a position how technology can be used to create cryptoassets. Conclusion- Regulations are important for making the financial system safe, protecting individual investors and ensuring an orderly environment in enterprises. Countries need to accept the crypto currency system and keep up with the innovations of crypto money by changing the current standards if necessary.
Determinants of Bitcoin price movements
(Suat Teker, 2024-07-30) Teker, Dilek; Teker, Suat; Demirel, Esin
Purpose- Investors want to include Bitcoin in their portfolios due to its high returns. However, high returns also come with high risks. For this reason, the volatility prediction of Bitcoin prices is the focus of attention of investors. Because Bitcoin's volatility is used as an important input in portfolio selection and risk management. This means that the models to be used in predicting Bitcoin volatility increases the importance of performance. In this research; A comparative examination of the models applied for Bitcoin shows an effective performance in volatility prediction. It is very important for evaluation. The aim of this study is to model Bitcoin price returns and to examine future return predictions and return directions using historical Bitcoin prices. Methodology- Many models have been used in studies on financial instruments and price predictions. Models such as linear and nonlinear regression, Random Walk Model, GARCH and ARIMA fall into this category. Nonlinear econometric models such as ARCH and GARCH are used for financial time series with variable volatility. These models assume that the variance is not constant. In this study, first Bitcoin price returns for the period between January 2020 and December 2023 will be modeled with the GARCH model, and then the ARCH-GARCH models will be used for future prediction of returns for the period between January 2024 and June 2024. Finally, the actual values will be compared with the forecasted values. In other words, the primary aim of this study is to use the daily Bitcoin closing price between May 2020 and December 2023 to estimate the returns for the periods of 2024 and compare it with the actual returns. Findings- The analysis reveals that GARCH Model results showed that in the mean and variance equations, it is seen that all variables are except intercept of the mean equation significant according to the error level of 0.05. Namely, the reaction and persistence parameters are significant accourding to 0.05 in the variance equation. Both the coefficient of the reaction parameter and the coefficient of the persistent parameter are higher than zero (positive). Also, the coefficient of the reaction parameter plus the coefficient of the persistent parameter approximately equals 0.72. That is, it is lower than 1 and higher than zero (positive). The level of persistence is not too high. So, we do not think about non-stationary variance in the model. Reaction parameter’s coefficient is 0.13. And persistence parameter’s coefficient is 0.58. As we can see, persistent parameter is much higher than reaction parameter. That is, when there is a new shock that creates the persistent parameter, that shock will be in effect for a long time, it will not disappear immediately. That is, a significant part of the shock that occurs in one period flows into the next period. After determining the appropriate mean and variance models, a forecast is made using Automatic ARIMA forecasting for BITCOIN return forecasting. This forecast is made for the first five months of 2024, without adding the actual values of the first five months of 2024 to the data. The program ranks the most appropriate model. The program chose GARCH(3,3) as the most appropriate model in "bitcoin return prediction". Conclusion- The results of the test applied in the study can be summarized that the unit root test results showed that it was necessary to work with return series. GARCH(1,1) model results show when there is a new shock that creates the persistent parameter, that shock will be in effect for a long time, it will not disappear immediately. That is, a significant part of the shock that occurs in one period flows into the next period. According to GARCH automatic forecasting results, the best GARCH model that models Bitcoin return is the GARCH(3,3) model. According to these model results, although the slopes of the actual and forecasted return series move in the same direction, the model remains weak for forecasting. In future studies, it may be recommended to estimate Bitcoin returns with non-linear models.
Determinants of Bitcoin prices
(PressAcademia, 2019-12-30) Deniz, E. Asena; Teker, Dilek
Purpose - The increase in the popularity of cryptocurrency market, various literature figure out the macroeconomic factors that effect the price movements of cryptocurrencies. This research aims to identify the interaction between gold, brent oil and bitcoin. Methodology - The database includes the Daily prices of Bitcoin, gold and brent oil prices between the period of 28.04.2013-23.07.2019 which consist of 484 daily data. Natural logaritm for each indicator is used. First, the stationarity of the series were analyzed with ADF (Augmented Dickey Fuller) unit root test. Lag lengths are determined. Interactions between the series were analyzed by the ImpulseResponse Function and Variance Decomposition methods. Findings- The series are found out to be stationary at first difference. Impulse response graphs indicate that all variables respond in a reducing way to reducing shocks occurred in each indicator. Shocks have lost their effect on average in 5 days. Conclusion- The results indicate that the effect of gold and brent oil prices on bitcoin daily prices do not have a strong effect. The results may be beneficial for investors to consider diversification for the portfolios.
Determinants of cryptocurrency market: an analysis for Bitcoin, Ethereum and Ripple
(Center for Promoting Ideas (CPI), 2020-11) Deniz, Asena; Teker, Dilek
One of the most important innovations brought by digitalization is crypto money known as virtual money. Cryptocurrencies, which have been discussed in recent years and especially a new portfolio for investors, are very popular. Bitcoin is the most well-known of these cryptographic systems, which do not depend on a central authority and have maximum reliability. The effects of various financial indicators on cryptoparas were examined in this study. The model includes a daily database in between April 3, 2018 to December 31, 2019. Initially stationarity is tested with unit root tests. Then cointegration and causality tests are employed. Impulse response is also implemented and analysed.
Determinants of cryptocurrency price movements
(Higher Education and Innovation Group (HEAIG), 2019-11) Teker, Dilek; Teker, Suat; Özyeşil, Mustafa
Cryptocurrency is a recent and popular topic that attracts the interest of investors and fund managers. Beyond the market discipline, researchers question the interaction between cryptocurrecies and macroeconomic variables. This study we focus on how the changes in gold and oil prices effect the daily price movements of different cryptocurrencies. The daily database includes prices of the cryptocurrencies of Bitcoin, Tether, Ethereum Litecon and EOS for the period between August 1, 2017 and April 3, 2019. Initially the stationarity of the series is tested by Ng and Perron (2001) method. The existence of the cointegration relationship between the series is tested by Johansen (1988) technique. The presence of causality relationships between the series is investigated with the Dolado and Lütkepohl (1996) causality test. The paper explains the details of the empirical findings.
Determinants of foreign direct investments: comparative analysis for Brazil, China, South Korea and Turkey
(PressAcademia, 2021-07-30) Kılıç, Fatih; Teker, Dilek
Purpose- With the globalization race gaining momentum after 1980, investments in developing countries increased significantly with the removal of obstacles to capital flows. With the effect of the globalization phenomenon in the world economy, developing countries have sought to meet the capitals they need with foreign investments. Until the 1980s, foreign direct investments were subject to serious restrictions. The priority of foreign direct investment was South Korea and Brazil in the early days. These two countries were followed by many emergency countries with development potential, and Turkey was trying to be included in this group. In the early 2000s, the biggest factor behind China's huge growth was the directing of foreign investments to China. In this study, inflation rate, unemployment rate and the index of industrial production, foreign direct investment coming to Brasil, China, South Korea and Turkey are examined on whether this is effective. Methodology- The data used in statistical tests are foreign direct investments, inflation, unemployment and the industrial production index, which has the largest share in GDP and allows interpretation without GDP being announced. All monthly data used in the tests are gathered from the Reuters, Bloomberg, UCTAD and the World Bank that covers periods from January 2012 to December 2020. Initially, unit root tests were performed to determine whether the data was stable.There are 3 basic critical points to understand whether unit root tests are stationary or not. After that, the VAR model has been applied. But before that coordinates all selected variables together and examines the integrity of the system, it is required to determine the appropriate lag length in order to make assumptions correct. The are five most common methods for determining lag lengths. In order to understand whether there is a long-term relationship between variables or not that are determined to be stationary, Johansen Cointegration test has been applied. Trace Statistics and the Max-Eigenvalue statistics were used in this test. And also impulse-response functions are obtained. Variance decomposition investigates which percentage of the change in a variable is caused by itself and which percentage is caused by other variables. Findings- All data have been converted into percentages by taking changes compared to the previous month. It has been modeled by getting the absolute values and logarithms of the data. For all 4 countries the series are found out to be stationary at level. ADF unit root test performed, then the appropriate length level determined. According to LR Test Statistics, Final Prediction Error, Akaike Information Criteria, Hannan-Quinn Information Criteria and Schwarz Information Criteria, the appropriate lang length appears as 1. According to the cointegration test result, cointegration was determined between all countries and all data. Impulse response graphs were indicated that all variables respond in a reducing way to decreasing shocks occurred in each indicator. Shocks have lost their effect on average in 4-5 months. According to the variance decomposition results, variables were the power of explanation over each other. Conclusion- In the Brasil, China, South Korea and Turkish economy, it is seen that there is a close relationship between foreign direct investment and economic growth indicators inflation, unemployment, industrial production index in the long term. According to the output of analyses, it is necessary to create the appropriate physical environment for increasing foreign capital investments, to ensure domestic economic, political and legal stability, to make arrangements that encourage foreign capital. Especially, a policy should be followed to decrease inflation and unemployment rates, which are indicators of economic growth and GDP should be risen by increasing industrial production. Coming from the foreign investments should become from the type of foreign direct investment and it should be supplied that these investments both create new markets and new employment areas by establishing a new facility.
Deterrents affecting consumers’ organic product purchase
(International Journal of Economics, Commerce and Management, 2020-10) Yarman Ak, Anda; Teker, Dilek
Organic agriculture is becoming an important factor of the economy as years go by and as the awareness on the subject increases among consumers. Although the sector is very promising, the demand is still very low. The value added to be obtained by organic agriculture can be a strong factor of the economy, especially on local basis. Therefore consumers’ purchase behaviors must be examined thoroughly to figure out how the demand can be increased. This study is, hence, focused on the deterrents that prevent consumers to purchase organic foods. An online survey is employed to a sample size of 556 respondents out of 543 were selected based on answering all questionnaire. Two different question set is employed to buyers and nonbuyers to depict the reasons of buying and not buying organic food. This study demonstrates the deterrents for non buyers. The replies given to the hypothesis specific questions are tested by chi-square test. Regarding the outputs, the main deterrents for buying organic food is the lack of packaging and trust in the authenticity of the seller. However, cosmetic concerns are not examined as one of the deterrent for a buy decision. For elimination of these deterrents can convince the consumers to purchase organic foods, which in consequence increase the demand and cause value added for local economy.
Development of e-commerce in Turkiye: post COVID-19 era
(IJOPEC, 2024-11) Teker, Suat; Teker, Dilek; Orman, Irmak; Şimşek, Sidar Atalay; Puwanendram, Gayathri; Şiriner, İsmail
The COVID-19 pandemic catalyzed a significant transformation in consumer behavior, accelerating the adoption of e-commerce worldwide. This study focuses on the development and growth of e-commerce in Türkiye during the post-COVID-19 era, examining the sector's expansion from 2020 onwards. Key factors contributing to this growth include increased internet and smartphone penetration, advancements in digital payment systems, and heightened consumer reliance on online shopping duringlockdowns. The analysis highlights how these shifts have not only enhanced domestic retail e-commerce but also positioned Türkiye as a rapidly growing e-commerce market globally, with a projected compound annual growth rate of 11.6% between 2024 and 2029. Additionally, the article explores opportunities for Turkish businesses to leverage cross-border e-commerce for international market expansion, emphasizing the strategic role of digitalization, logistics improvements, and government incentives. By presenting key data and trends, the study underscores Türkiye’s potential to strengthen its presence in global trade through e-commerce, driving economic growth and fostering innovation in its digital economy.
Digital payment systems: a future outlook
(PressAcademia, 2022-07-30) Teker, Suat; Teker, Dilek; Orman, Irmak
Purpose- This study examines the development of digital payment systems with the evolution of communication technologies, financial institutions and fintech companies. Also, this study analyzes the expected effects of developing payment systems and fintech applications. Methodology- The study defines different types of digital payment systems, compares general characteristics of digital payments, provides a timeline of developments for digital payment systems and compares most used digital payment applications. Findings- The payments market is changing in line with consumer behavior. Cashless economies, mobile banking, instant payments, digital commerce, and the growing impact of regulatory agencies are a few trends affecting the payments market. Contactless payments also make the payment process easier and more convenient for consumers who benefit from shorter lines, cash-on-hand issue elimination, and faster moving queues.The Asia-Pacific region is anticipated to witness significant growth in the market such as China and India. Digital and mobile wallets account for 58% of regional e-commerce payments in the region and are expected to reach 68.2% by 2023. The e-commerce sector is witnessing a spike in demand as consumers order essential items such as food and clothes through e-commerce websites, where most consumers prefer the digital mode of payment.Transition towards the cashless economy, emergence of new online financial institutions, a decentralized monetary governance with the adoption of blockchain and cryptocurrencies are envisioned. Advancements in payment technologies as well as digital payment systems adoption will create momentum and create further investments towards digitalization of monetary exchange. Conclusion- It is concluded that evolution of digital payment systems will extend convenience, return, convergence, cross-border and timelimitless transaction. Inclusion of the unbanked is expected to drive growth and create new opportunities. There is a clear transition towards a cashless economy with the increasing adoption of digital payment systems by all spenders. Speed, privacy, convenience, security and decentralization will mean a wider inclusion for all global citizens; even including some unbanked population. Decentralization and blockchain will mean a blur in distribution of wealth, some money leaving the traditional banking systems. Digital payment systems provide a wide range of transaction options to its users; swiped credit cards, electronic checks, mobile wallets and contactless payment. By 2050s, the circulation of physical money is expected to vanish, leaving its place to virtual currencies changed on digital platforms.
Digital transformation and universities
(PressAcademia, 2022-07-30) Teker, Suat; Teker, Dilek; Tavman, Emine Başak
Purpose- This study aims to examine how digitalization has affected and changed higher education. It focuses on the current situation of universities and their current processes and what they need to do to become digital. It aims to present a roadmap for universities to integrate and organize these important changes into their strategies by examining the digital transformation that affects the vision of universities. Methodology- The study employs a literature review using secondary data analysis. Findings- The analysis reveals that the role of universities in many aspects such as society and economy has changed and is expected to change disruptively over the next decade. Universities need to make a differentiation through emerging business models in such a competitive higher education sector. Higher education institutions have to adapt to technological changes for sustainabilty. The pandemic dramatically accelerated the pace of technological adoption worldwide. The drivers of digital transformation in universiteis can be summarized as the increase compteteiveness, user experience and agility while reduction in operating expenses. Conclusion- It may be concluded that a university should be part of present technological trends and include digitalization in their strategies to be competitive in the future. Universities need to focus mainly on exploring more innovative measures to create technology development centres through research to deal with skills shortages. Universities should support those academics who lead the improvement of digital skills and innovative teaching methods, promote digital literacy in the academia and encourage the use of learning platforms. It is important to set a clear policy to adopt digital age in higher education. Universities will be competing globally for students, academic staff and funding. Adoption and implementation of new technologies in universities are inevitable.
Digital transformation in businesses: the process and its outcomes
(PressAcademia, 2022-07-30) Teker, Suat; Teker, Dilek; Örendil, Emre
Purpose- The purpose of this study is to serve as an extensive outlook about digital transformation. Its content comprises the elements of digital transformation, the ways of adapting to digital transformation, reasons for failure, means of digital transformation, and insights and discussions on new business environment. Methodology- In this study, a comprehensive literature review is followed to learn about the current business circumstances regarding digital transformation and have a deep understanding on the previous studies conducted about digital transformation. Findings- The literature review reveals that digital transformation has provided positive impract on businesses at different levels. Although challenges against digital transformation may arise, they can be tackled if the nature of digital transformation is understood well. The success of digital transformation is dependent on numerous factors from different aspect which should be studied carefully before and during the adoption of digital transformation. Conclusion- It may be concluded that the COVID-19 pandemic has accelerated the digital agenda of businesses. At first, it should be understood that digital transformation is not a mere upgrade of technology or technical equipment within an organization but requires time, curiosity, creativity, recognition of opportunities, and cultural transformation. A successful adoption of digital transformation requires the recognition of means of digital transformation, the steps for adaptation to digital transformation, the analysis of failure, the outcomes of digital transformation. The recent evolutions related to digital transformation is evident in different aspects of business. The most recent observed changes in businesses are required skills of employees, organisational culture, business models, and customer relationship management practices.

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