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Through the study of leadership, the concept of leadership effectiveness and its importance has emerged. Effective leadership contributes to successful organizations (Amagoh, 2009; Leithwood, Jantzi, & Steinbach, 1999). According to Gordon & Yukl (2004), because of constantly changing environments, it is important to continue research in the leadership and leadership effectiveness fields, especially when it comes to leadership in academia. Using Seiler and Pfister’s (2009) Dynamic Five-Factor Model of Leadership as the theoretical frame, a qualitative study of leadership effectiveness influencers of Agricultural and Extension Education department heads was completed. The research looked at both internal and external influential factors.

This leadership education evaluation study explored the leadership development outcomes of potential county extension directors and the ways to improve the program. The leadership education program aimed to improve participants’ leadership abilities in understanding self, building relationships and managing resources. The analysis of quantitative and qualitative data confirmed that the leadership training institute was effective in building participants’ leadership skills and improving leadership behavior. The incorporation of participants’ learning needs into the program, use of hands-on experiential learning activities and problem solving activities combined with small group discussions were the contributing factors for the success of this leadership education program. The participants suggested the use of more hands-on and problem solving activities, team building exercises and condensing the time gap between the pre and post sessions as strategies for further improvement of this program.

This paper aims to investigate the influence of air and rail transportation on pollution in Turkey from 1970 to 2020.

Fourier Autoregressive Distributive Lags (ADL) and Fourier Fractional ADL cointegration tests (Banerjee et al., 2017; Ilkay et al., 2021) are employed to analyze the relationship be-tween the variables. Cointegration tests that take into account soft transitions under structural changes are implemented. Structural change issues are crucial for this topic since the changes in countries’ environmental policies and transportation habits are shaped by the decisions taken in relation to environmental regulations. Finally, for robustness purposes, we tested the estimated equation with a completely different methodology. Thus, a Machine Learning (ML) analysis is conducted, through a Ridge Regression (RR).

The findings obtained by applying Fourier Autoregressive Distributive Lags (FADL) and Fourier Fractional ADL cointegration tests, which can control for structural changes, reveal the existence of a long-term relationship between the variables. In addition, FMOLS estimates emphasize that economic growth and air transport can lead to increased pollution in the long run, while rail transport reduces it. Moreover, the statistically significant trigonometric terms indicate the existence of a smooth structural change among the variables. Robustness checks are performed through a Machine Learning (ML) analysis, which roughly confirms the previous results.

To our knowledge, existing research in Turkey focuses mainly on road transport, while the impact of rail and air transport on pollution has not yet been investigated. As such, this study will be a significant addition to the academic literature.