PurposeThis study aims to examine the relationship between market orientation and product innovation and the mediating role of technological capability in this relationship. It also aims to examine the effect of market orientation on product innovation within the framework of technological intensity classification of the fields of business activity.Design/methodology/approachThe research data were obtained from 186 senior and mid-level managers of 627 manufacturing firms that are widely considered to be innovative, and that are ranked among Turkey's largest 1,000 manufacturing firms (ISO 1000). The data were analyzed using partial least squares structural equation modeling.FindingsCustomer orientation and interfunctional coordination, two distinct dimensions of market orientation, had positive effects on product innovation. Technological capability played a mediating role in the effect of customer orientation and interfunctional coordination on product innovation. In addition, interfunctional coordination positively affected product innovation in firms with low technological intensity, whereas customer orientation positively affected product innovation in firms with medium-high technological intensity.Practical implicationsFor the success of product innovations, firms should establish mechanisms to obtain information about customer needs and expectations and to disseminate and effectively use this information among organizational functions. They also need to improve their technological capabilities to effectively transform market knowledge into product innovation.Originality/valueThe relationship between market orientation and product innovation has been examined in previous studies; however, there is an insufficient number of studies on the mediating role of technological capability in this relationship. This study aimed to eliminate the gap in the literature regarding the mediating role of technological capability. In addition, innovation activities of firms vary depending on the technological intensity, but only a limited number of evaluations have been conducted on this subject. This study contributes valuable knowledge to the relevant literature by examining the impact of market orientation dimensions on product innovation according to technological intensity.

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Öz: Bu çalışmanın amacı, yalın organizasyonda değer akışı haritalama uygulaması ile süreçlerin nasıl iyileştirildiğini açıklamaktır. Değer akışı haritalama, ürün değer akışını görmeye, süreçteki israf kaynaklarını anlamaya, ürün akışındaki iyileştirme noktalarını fark etmeye ve daha iyi süreçler geliştirmeye yardımcı olmaktadır. Değer akışı haritalama uygulaması, yalın organizasyon olan, değer akışı haritalama konusunda önemli bilgi ve tecrübesi bulunan ve otomotiv sektöründe yer alan XYZ işletmesinde yapılmıştır. XYZ işletmesi, ISO 500'de yer almakta ve 800'den fazla çalışanı bulunmaktadır. Bu çalışmada, değer akışı haritalama tek bir işletme seviyesinde uygulanmıştır. Ürün ailesi olarak seçilen arka koltuğa ilişkin mevcut durum haritası çizilmiş, mevcut durum haritasındaki değer akışı incelenmiş, gelecek durum haritası oluşturulmuş ve gelecek duruma ulaşmak için yapılan iyileştirmeler açıklanmıştır. Sonuç olarak işletmede çalışan sayısının azaldığı, alan tasarrufu sağlandığı, hataların azaldığı, üretim kapasitesinin arttığı, hat duruş zamanının azaldığı, akış süresinin kısaldığı, bitmiş ürün stokunun azaldığı ve üretimin dengelendiği belirlenmiştir. Değer akışı haritalamanın, süreçlerin iyileştirilmesinde önemli bir araç olduğu ve yalın organizasyon olmak isteyen işletmelere önemli faydalar sağlayabileceği değerlendirilmiştir.Abstract: The purpose of this study is to explain how the processes were improved in a lean organization through value stream mapping application. It is suggested that value stream mapping enables to observe product value stream, notice the sources of waste in the process, identify improve-ment points in product flow and develop more efficient processes. The application of value stream mapping was implemented in XYZ company, which is significant knowledge and expe-rience of value stream mapping in the automotive sector. XYZ company is on the ISO 500 and employs more than 800 employees. In this study value stream mapping was applied on a single company level. The current state map was drawn after selecting rear seat as product family; then the value stream in the current state map was examined, the future state map designed, and improvements explicated to reach a future state. It was concluded that the number of employees in the company decreased, space-saving was realized, defects diminished, produc-tion capacity increased, line stop time decreased, lead time shortened, finished product inven-tory decreased and production was balanced. It is suggested that value stream mapping may be considered as a significant tool in the improvement of processes and providing significant benefits to businesses planning to be lean organizations.

Objective: To identify which Machine Learning (ML) algorithms are the most successful in predicting and diagnosing breast cancer according to accuracy rates. Methods: The “College of Wisconsin Breast Cancer Dataset”, which consists of 569 data and 30 features, was classified using Support Vector Machine (SVM), Naive Bayes (NB), Random Forest (RF), Decision Tree (DT), K-Nearest Neighbor (KNN), Logistic Regression (LR), Multilayer Perceptron (MLP), Linear Discriminant Analysis (LDA), XgBoost (XGB), Ada-Boost (ABC) and Gradient Boosting (GBC) ML algorithms. Before the classification process, the dataset was preprocessed. Sensitivity, accuracy, and definiteness metrics were used to measure the success of the methods. Result: Compared to other ML algorithms used in the study, the GBC ML algorithm was found to be the most successful method in the classification of tumors with an accuracy of 99.12%. The XGB ML algorithm was found to be the lowest method with an accuracy rate of 88.10%. In addition, it was determined that the general accuracy rates of the 11 ML algorithms used in the study varied between 88-95%. Conclusion: When the results obtained from the ML classifiers used in the study are evaluated, the efficiency of the GBC algorithm in the classification of tumors is obvious. It can be said that the success rates obtained from 11 different ML algorithms used in the study are valuable in terms of being used to predict different cancer types.

Increasing dependence on Information and Communication Technologies (ICT) and especially on the Internet in Industrial Control Systems (ICS) has made these systems the primary target of cyber-attacks. As ICS are extensively used in Critical Infrastructures (CI), this makes CI more vulnerable to cyber-attacks and their protection becomes an important issue. On the other hand, cyberattacks can exploit not only software but also physics; that is, they can target the fundamental physical aspects of computation. The newly discovered RowHammer (RH) fault injection attack is a serious vulnerability targeting hardware on reliability and security of DRAM (Dynamic Random Access Memory). Studies on this vulnerability issue raise serious security concerns.  The purpose of this study was to overview the RH phenomenon in DRAMs and its possible security risks on ICSs and to discuss a few possible realistic RH attack scenarios for ICSs. The results of the study revealed that RH is a serious security threat to any computer-based system having DRAMs, and this also applies to ICS.