Browsing by Author "Yildiz, B."

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SUSTAINABLE MOBILITY AND ELECTRIC VEHICLE ADOPTION: A STUDY ON THE IMPACT OF PERCEIVED BENEFITS AND RISKS
(2024.01.01) Yildiz, B.; Çigdem, S.; Meidute-Kavaliauskiene, I.
The shift towards sustainable transportation is becoming increasingly important as the negative impact of traditional fuel-powered vehicles on the environment becomes more evident. Electric Vehicles (EVs) are considered a viable solution to this problem, and understanding the factors that influence consumer intention to purchase EVs is crucial for their widespread adoption. This study investigates the factors that influence individuals' intention to purchase EVs. 4 independent variables were considered: Perceived Environmental Benefit (PEB), Perceived Performance Benefit (PPB), Perceived Performance Risk (PPR), and Perceived Financial Risk (PFR). A survey was conducted with 398 respondents, and the data collected were analysed using Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modelling (SEM). The results indicate that PEB, PPB, PPR, and PFR have significant effects on Purchase Intention (PI). Specifically, PEB and PPB positively affect PI, while PPR and PFR negatively affect it. These findings suggest that improving the PEBs and PPBs of EVs and reducing perceived performance and financial risks could encourage more individuals to purchase them.
THE NEXUS OF BIG DATA ANALYTICS, KNOWLEDGE SHARING, AND PRODUCT INNOVATION IN MANUFACTURING
(2024.01.01) Yildiz, B.; Çigdem, S.; Meidute-kavaliauskiene, I.; Cincikaite, R.
In today's highly competitive business environments, manufacturers face stiff com-petition. As digital technologies have become more pervasive, many businesses in the manufacturing sector have begun to tap into the potential of big data analytics to gain an edge in their markets. Companies in the manufacturing sector can gain a significant competitive advantage by strategically utilizing big data analytics to uncover profound insights that have the potential to significantly enhance their capabilities in product innovation. This research delves into communication's role as a go-between for big data analytics and product innovations' success at manufacturing firms. The validity and reliability of the measurement scales were first thoroughly examined in this study. The research model was then tested using structural equation modeling and process macro analysis. The analytical findings unveil those big data analytics exert a pronounced, positive, and statistically significant impact on product innovation performance and information-sharing dynamics. Furthermore, it is discerned that information-sharing exerts a substantial and affirmative influence on the capacity for product innovation. Additionally, it is established that the impact of big data analytics on product innovation performance undergoes moderation by the infor-mation-sharing mechanism.
THE NEXUS OF BIG DATA ANALYTICS, KNOWLEDGE SHARING, AND PRODUCT INNOVATION IN MANUFACTURING
(Vilnius Gediminas Technical University, 2024) Yildiz, B.; Çiğdem, Ş.; Meidutė-Kavaliauskienė, I.; Činčikaitė, R.
In today’s highly competitive business environments, manufacturers face stiff com-petition. As digital technologies have become more pervasive, many businesses in the manufacturing sector have begun to tap into the potential of big data analytics to gain an edge in their markets. Companies in the manufacturing sector can gain a significant competitive advantage by strategically utilizing big data analytics to uncover profound insights that have the potential to significantly enhance their capabilities in product innovation. This research delves into communication’s role as a go-between for big data analytics and product innovations’ success at manufacturing firms. The validity and reliability of the meas-urement scales were first thoroughly examined in this study. The research model was then tested using structural equation modeling and process macro analysis. The analytical findings unveil those big data analytics exert a pronounced, positive, and statis-tically significant impact on product innovation performance and information-sharing dynam-ics. Furthermore, it is discerned that information-sharing exerts a substantial and affirmative influence on the capacity for product innovation. Additionally, it is established that the impact of big data analytics on product innovation performance undergoes moderation by the infor-mation-sharing mechanism.