Dilara Berrak TARHAN
Ankara Medipol University, Faculty of Economics, Administrative and Social Sciences, Department of International Trade and Finance, Türkiye

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Beyond Oil Prices: A Comparative Analysis of the Indirect Effects of Energy Prices on Economic Growth in Türkiye and Russia Abdallah Abukalloub; Dilara Berrak TARHAN; Ayşe GÜNGÖR
Salus Publica: Journal of Community Service Vol. 4 No. 2 (2026): August 2026
Publisher : Salus Publica: Journal of Community Service

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saluspublica.v4i2.624

Abstract

This study examines the impact of energy prices on economic growth through a comparative analysis of Türkiye and Russia. The analysis uses annual data covering the period 2000-2024. The primary empirical assessment employs a multiple linear regression (OLS) model, with panel data techniques used as complementary methods to analyze long-run relationships and test the robustness of the findings. Brent crude oil prices are used as a proxy for energy prices, and the GDP growth rate serves as the indicator of economic growth. Unemployment, inflation, exchange rate, trade volume, and gross capital formation are included in the model as control variables. The findings indicate that Brent oil prices have a negative and statistically significant effect on economic growth. Moreover, the adverse effects of unemployment and exchange rate fluctuations on growth are stronger, whereas gross capital formation contributes positively to economic growth. The results of the interaction model reveal that the effect of oil prices does not differ significantly between the two countries. In conclusion, the impact of energy prices on economic growth is not direct but is shaped by macroeconomic conditions and varies with country-specific structural characteristics.
Managing Product Returns at the Source: Associations between SCOR Processes and Return Performance - Multimethod Evidence from the Gaziantep Carpet Manufacturing Industry Dilara Berrak TARHAN; Hasan Aksoy
Whoosh: Journal of Transportation and Logistics Vol. 1 No. 2 (2026): August 2026
Publisher : Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/whoosh.v1i2.792

Abstract

Product returns are not merely a post-sale reverse-logistics activity; they can also represent the visible outcome of deficiencies in planning, sourcing, production, delivery, and supply chain governance. This study examines associations between the Plan, Source, Make, Deliver, and Enable processes in the SCOR Model 12.0 and a perception-based Return construct and identifies processes that merit managerial attention for return prevention. A multimethod design is employed. A total of 119 valid questionnaires collected from carpet manufacturing firms operating in Gaziantep, Türkiye, were analyzed via exploratory factor analysis, correlation analysis, and multiple linear regression. Evaluations of 28 SCOR metrics obtained from 10 supply chain managers were then weighted via the entropy method, and semistructured interviews with four stakeholders connected to one large carpet manufacturer were used for contextual interpretation. Because the survey is cross-sectional and all the constructs were measured from the same respondents at one measurement occasion, the regression coefficients are interpreted as associations rather than causal effects, and common-method variance cannot be ruled out. The main regression model accounts for 75.7% of the variance in the Return construct (R² = .757; adjusted R² = .747; p < .001). Plan is the strongest predictor (β = -.559; p < .001), followed by Enable (β = -.253; p = .004), Make (β = -.200; p = .017), and Deliver (β = -.170; p = .021); Source is not statistically significant (β = -.091; p = .115). Exploratory item-level regressions identify supply chain data and information management (β = -.668; p < .001) and engineer-to-order production (β = -.546; p < .001) as the strongest nominal associations, but these item-level p values are unadjusted for multiple testing and are treated as hypothesis-generating. Within the 10-manager panel, entropy-derived weights rank Plan first, and an indicator-count-normalized sensitivity check also leaves Plan first, although the ordering of intermediate processes changes. Overall, the findings are consistent with a preventive, upstream approach to returns centered on planning, information governance, customized production, and fulfillment control.