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With the irresistible growth in digitization, data backup policies become essential more than ever for organizations seeking to improve reliability and availability of organizations' information systems. However, since backup operations do not come free, there is a need for a data-informed policy to decide how often and which type of backups should be taken. In this paper, the authors present a comprehensive mathematical framework to explore the design space for backup policies and to optimize backup type and interval in a given system. In the authors' framework, three separate cost factors related to the backup process are identified: backup cost, recovery cost and data loss cost. The objective function has a multi-criteria structure leading to a backup policy minimizing a weighed function of these factors. To formalize the cost and objective functions, the authors get help from renewal theory in reliability modeling. The authors' optimization framework also formulates mixed policies involving both full and incremental backups. Through numerical examples, the authors show how the authors' optimization framework could facilitate cost-saving backup policies.

The methodology starts with designing different backup policies based on system parameters. Each constructed policy is optimized in terms of backup period using renewal theory. After selecting the best back-up policy, the results are demonstrated through numerical studies.

Data backup polices that are tailored to system parameters can result in significant gains for IT (Information Technology) systems. Collecting the necessary parameters to design intelligent backup policies can also help managers understand managers' systems better. Designed policies not only provides the frequency of back up operations, but also the type of backups.

The original contribution of this study is the explicit construction and determination of the best backup policies for IT systems that are prone to failure. By applying renewal theory in reliability, the authors present a mathematical framework for the joint optimization of backup cost factors, i.e. backup cost, recovery time cost and data loss cost.

This study examines the impact of raising the ceiling value of Electronic Commerce Custom Declarations (ECCD) on Turkey's export performance processed via ECCD during the COVID-19 period.

This paper examines the impact of the pandemic conditions on Cross-Border Electronic Commerce (ECCD) exports from Turkey to 47 countries over 42 months before and during the pandemic. An empirical analysis using the Pooled Mean Group (PMG) and Mean Group (MG), Panel Autoregressive Distributed Lag (ARDL) approach was conducted to identify the factors affecting export flows.

The findings suggest that raising the ceiling of the ECCD trade is a vital factor in increasing exports. and this result is robust after controlling for pandemic conditions. On the other hand, although the COVID-19 shock mitigates the export volume of ECCD in the short run, it changes by reversal and increases the export level in the long run. Additionally, the number of COVID-19 cases and deaths in Turkey have a significant and negative impact on export flows in the short run, while they have a positive and significant effect in the long run.

The results of this study have practical implications for policymakers, emphasizing the potential and significance of Cross-Border E-Commerce (CBEC) trade.

The study is a pioneering effort in the literature of CBEC to explore how changes in the upper limit on customs declarations can affect export flows, taking into account the impact of the COVID-19 pandemic.

This study aims to examine the performance and volatility of Turkey Real Estate Investment Trusts (Turkish REITs) as the world is adjusting to the new normal situation in every aspect of REITs' business activities.

The prices of REITs were acquired from 26 Turkish REITs in this study, but owing to autocorrelation difficulties, 14 Turkish REITs were employed in the analysis. The ten-year long-term bond of the Turkish Government was also utilized and the period of data obtained was based on availability. The performance of Turkish REITs was evaluated using Sharpe's ratio and Treynor's ratio, and the volatility was assessed using MGARCH-BEKK.

The authors found out that Turkish REITs are constantly underperforming and the REITs' returns remain highly volatile and persistent. In addition, findings showed evidence of volatility clustering and the asymmetric impact of shocks. This study further revealed the uniqueness of each of the Turkish REITs due to the lack of evidence of multicollinearity.

However, the limitation of this study is the constraint in obtaining more macro-economic variables of more than ten-years of Turkey's Government bond and the study focused mainly on Turkish REITs.

The result suggests that since Turkish REITs are not mandatory to payout 90% of taxable earnings as dividends, high performance and an appropriate risk management approach are expected. The need for timely revealing performance of T-REITs and associated uncertainty may trigger better performance as discussed in the relationship between disclosure and performance which is recently emphasized in a recent study by Koelbl (2020). With current performance and associated uncertainty in Turkish REITs, the need to protect Turkish REITs investors is highly essential. The result further educates REIT investors that diversification benefits of REITs tend to reduce in extremely risky situations.

This is the first study in the context of Turkish REITs that comprehensively integrated market capitalization of REITs and simultaneous evaluation of performance and the volatility of the Turkish REITs as the world adjusts to the new normal.