The term "emerging markets" refers to countries that are undergoing economic and financial development. As financial development progresses in these nations, the capital available for international trade and the expansion of logistics infrastructure grows as well. This increased capital enables the financing of international trade activities and facilitates the execution of necessary logistics operations efficiently and effectively. Additionally, with enhanced financial development, it becomes easier to secure the capital required to improve logistics infrastructure and make it more functional. In this study, analyses are conducted using the Panel autoregressive distributed lag method in emerging market countries to evaluate the direct and indirect effects of financial development on logistics performance. The results reveal that increased access to financial institutions and markets positively affects logistics performance in both the short and long term. Among financial variables, the depth of financial institutions exhibits the strongest long-term influence, suggesting that a stable financial system is crucial for logistics efficiency. These insights provide valuable guidance for decision-makers aiming to strengthen logistics infrastructure and trade capabilities. By recognizing the role of financial development in supporting logistics performance, policymakers can craft strategies that support sustainable economic growth through improved logistics processes.

This research assesses Turkey's sustainable development performance from 2011 to 2021 through an innovative integrated multi-criteria decision-making (MCDM) framework. The methodology integrates three objective weighting methods [SIWEC-M, MEREC, and Standard Variance (SV)] with the RAWEC method for the purpose of ranking alternative years. The SIWEC-M method, an enhancement of the SIWEC, was designed to address the zero-weight limitation present in the original method, thereby providing more balanced and reliable criteria weighting. The results indicate that inflation is the primary factor influencing Turkey's sustainability trajectory, whereas the Social Development Index (SDI) has the least impact. The analysis identifies 2011 as the apex year for Turkey's sustainable development, succeeded by 2013, 2015, and 2016, while 2021 is noted as the year of lowest performance. A sensitivity analysis based on Monte Carlo simulation further confirms the robustness of the results across different criterion weights. The consistency of the proposed methodology was validated through a comparison of outcomes with established MCDM techniques, including ARAS, COPRAS, and WASPAS, which yielded identical rankings. This study enhances the SIWEC-M model methodologically and provides empirical insights for policymakers regarding Turkey’s sustainable development dynamics, highlighting the significance of macroeconomic factors such as inflation. The study identifies structural vulnerabilities in Turkey's sustainability performance, informing future policy interventions to enhance economic and social resilience.

The macroeconomic performance of nations provides valuable insights into the knowledge economy and the governance structures that sustain its development. This study formalizes a framework for evaluating knowledge flows and innovation capacity through multi-criteria decision analysis (MCDA) using open World Bank data. The analysis employs the Logarithmic Decomposition of Criteria Importance (LODECI) method in conjunction with the Preference Selection Index (PSI) to determine objective weights, while the Weighted Euclidean Distance-Based Approach (WEDBA) is applied to rank the G7 countries and Türkiye in 2023. Knowledge flows, as represented by exports and foreign direct investment (FDI), serve as proxies for cross-border knowledge exchange, while inflation, unemployment, and economic growth are assessed within a reproducible, policy-driven framework. The weighting procedure assigns the greatest aggregate importance to inflation and the least to unemployment. The resulting rankings place the United States first, followed by Japan in second place, Türkiye fourth, and the United Kingdom last. The analysis further highlights how factors such as price stability, external openness, and investment dynamics shape national knowledge creation, diffusion, and organizational learning processes. By focusing on the utilization of open data, explicit knowledge representation, and transparent multi-criteria methodologies, the proposed framework strengthens digital knowledge infrastructures and facilitates actionable crosscountry benchmarking. The findings have important policy implications, particularly in understanding how national macroeconomic variables influence innovation capacity. The framework is designed to be extensible, allowing for future adaptation to evaluate additional indicators, such as R&D intensity, high-tech export shares, and patenting activity. Furthermore, the approach is structured to support replication across various regions and timeframes, ensuring its broad applicability and scalability.

İşsizlik, birey, aile ve toplumun tamamı açısından önemli problemleri beraberinde getiren ekonomik bir sorundur. İstihdam ve işsizlik ekonominin kendi dinamikleri tarafından belirlenmektedir. Ancak deprem vb. tabii afetler ve savaş gibi fevkalade haller ekonomiyi etkilediği gibi işsizlik ve istihdam üzerinde de etkili olmaktadır. Bu çalışmada 6 Şubat 2023 tarihli Kahramanmaraş merkezli depremlerden en çok etkilenen illerden biri olan Malatya’da depremin istihdam üzerindeki etkisi İŞKUR kayıtları esas alınarak açıklanmaya çalışılmıştır. Çalışmada betimsel istatistik yöntemi kullanılmıştır. Çalışmada, Malatya’nın deprem sonrası kaybedilen çalışma saatleri açısından deprem bölgesinde en çok etkilenen il olduğu tespit edilmiştir. Deprem sonrasında Malatya’da açık iş sayılarında önemli düşüşlerin olduğu, İŞKUR tarafından işe yerleştirme sayılarında önemli azalmaların olduğu tespit edilmiştir. Mesleki eğitim kursları ile işbaşında eğitim programlarına katılımın deprem sonrası dönemde azaldığı ve Malatya’da açık işler için aranan eğitim şartlarından daha fazla eğitim şartını yerine getiren işsizlerin bulunduğu tespit edilmiştir.

The increasing number of women in managerial positions and their active involvement in personnel selection processes make it important to identify the criteria they prioritize when selecting employees. The aim of this study is to explore and prioritize the personnel selection criteria considered important by women managers. The sample comprised seven women human resources managers from seven companies operating in different sectors. Two interviews were conducted with the relevant managers. In the first interview, women managers were asked about the criteria they consider important in personnel selection, and based on the data obtained, a pool of 43 items was developed. From the generated pool of criteria, the ten most important criteria were identified based on the opinions of two academics specializing in human resource management and organizational behavior and one human resource manager. The ten most important criteria identified were presented to the women managers in the second interview, and they were asked to rank these criteria in order of importance and to complete a nine-item questionnaire. The data obtained were analyzed using the IMF-SWARA (Improved Fuzzy Step-wise Weight Assessment Ratio Analysis) method, one of the MCDM (Multi-Criteria Decision-Making) techniques. According to the analysis results, the most important criterion that women managers consider in personnel selection was identified as “being trustworthy and moral,” while the least important criterion was identified as “analytical thinking and problem-solving.” These findings indicate that women managers consider being trustworthy and moral more important than factors such as knowledge, skills, experience, and communication in personnel selection.

Siber fiziksel sistemler Dördüncü Sanayi Devrimi sürecinde öne çıkan ve dijital dönüşüm sürecini başlatan önemli bir faktördür. Akıllı teknolojiler ve üretken yapay zekâ ile bu süreç, çalışanlar ve işverenler için hem fırsatları hem de tehditleri içermektedir. Bu bakımdan çalışmanın amacı, Türkiye’de çeşitli sektörlerde faaliyet gösteren işletmelerde çalışan ve dijital dönüşüm süreçlerinde deneyim sahibi olan uzmanların görüşleri doğrultusunda çalışma hayatında dijital dönüşümünün önündeki engelleri belirlemektir. Bu çerçevede çalışmada dört uzman ile görüşülmüş ve Gri SIWEC yöntemi kullanılmıştır. Bulgulara göre uzmanlar dijital dönüşümün önündeki en büyük engeller olarak veri güvenliği ve Kişisel Verilerin Korunması Kanunu (KVKK) endişeleri, teknolojik altyapı ve entegrasyon sorunları ile strateji belirsizliği olduğunu göstermiştir.