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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.

This paper proposes a set of recommendations based upon the limitations found with the application and assessment process to become a Special Constable (SC) with one of the 43 police forces in England and Wales.

Participants were recruited via online social media platforms Twitter and LinkedIn, as well as personal networks and the study was geared towards both respondents who had completed the whole of the application and assessment process, as well as those who may have withdrawn at a particular point or who failed an element of the assessment.

This study yielded several key findings. First, some respondents had limited to no knowledge of the role of the Special Constable, nor of the depth of police work that would be expected of them. Secondly, respondents indicated that they would have benefited from support during the application and assessment process, specifying the advantages that could be derived from a variety of sources such as local force input and workshop sessions. Finally, respondents stated that poor communication from recruiting teams impacted their experience of applying to the Special Constable programmes, causing them to rethink their decision to join.

This research proposes that a far greater input from serving Special Constables during the application and assessment process is key to improving the experiences of candidates, and to their chances of success with the programme.

The purpose of this study is to analyze the relationship between academic writing and generative artificial intelligence (AI).

This paper is characterized as exploratory and descriptive, with a qualitative approach. Two approaches were used: the first, a narrative review of the literature with a systematic search from which a data collection stage was carried out using asynchronous interviews by means of an online questionnaire.

The results indicate that generative AI should be seen as a complementary tool for creative and critical academic writing. The data collected also highlighted issues related to academic dishonesty and the new type of plagiarism – plagiarism made possible by technologies – as well as issues of authorship and legitimacy of work carried out with AI and the loss of reflective and critical thinking and creativity.

The considerable increase in resources using AI in all dimensions of human life.

The impact that the use of generative AIs can have on the creation of knowledge and the dissemination of scientific research.

The impact that the use of generative AIs can have on the creation of knowledge and on the dissemination of scientific research.

The need for academia to anticipate the use of AI in academic writing and to incorporate its benefits into this process, especially considering researchers in training.

El objetivo de este artículo es analizar la relación entre la escritura académica y la inteligencia artificial generativa.

Este artículo se caracteriza por ser exploratorio y descriptivo, con un enfoque cualitativo. Se utilizaron dos enfoques: el primero, una revisión narrativa de la literatura con una búsqueda sistemática, a partir de la cual se llevó a cabo una etapa de recogida de datos mediante entrevistas asincrónicas a través de un cuestionario online.

Los resultados indican que la IA generativa debe considerarse una herramienta complementaria para la escritura académica creativa y crítica. Los datos recogidos también pusieron de manifiesto cuestiones relacionadas con la deshonestidad académica y el nuevo tipo de plagio, el plagio posibilitado por las tecnologías, así como cuestiones de autoría y legitimidad del trabajo realizado con Inteligencia Artificial, la pérdida de pensamiento reflexivo y crítico y la creatividad.

La necesidad de que el mundo académico se anticipe al uso de la IA en la escritura académica e incorpore sus ventajas a este proceso, considerando principalmente a los investigadores en formación.

El considerable aumento de los recursos que utilizan la IA en todas las dimensiones de la vida humana.

El impacto que puede tener el uso de las IA generativas en la creación de conocimiento y la difusión de la investigación científica.

El impacto que puede tener el uso de las IA generativas en la creación de conocimiento y la difusión de la investigación científica.

O objetivo deste artigo é analisar a relação entre a redação acadêmica e a inteligência artificial generativa.

Este artigo é caracterizado como exploratório e descritivo, com uma abordagem qualitativa. Foram usadas duas abordagens: a primeira, uma revisão narrativa da literatura com uma busca sistemática, a partir da qual foi realizada uma etapa de coleta de dados usando entrevistas assíncronas por meio de um questionário on-line.

Os resultados indicam que a IA generativa deve ser vista como uma ferramenta complementar para a redação acadêmica criativa e crítica. Os dados coletados também destacaram questões relacionadas à desonestidade acadêmica e ao novo tipo de plágio - o plágio possibilitado pelas tecnologias, bem como questões de autoria e legitimidade do trabalho realizado com a Inteligência Artificial, a perda do pensamento reflexivo e crítico e da criatividade.

A necessidade de a academia antecipar o uso da IA na redação acadêmica e incorporar seus benefícios nesse processo, considerando principalmente pesquisadores em formação.

O aumento considerável de recursos usando IA em todas as dimensões da vida humana.

O impacto que o uso de IAs generativas pode ter sobre a criação de conhecimento e a disseminação de pesquisas científicas.

O impacto que o uso de IAs geradoras pode ter na criação de conhecimento e na disseminação de pesquisas científicas.

This paper aims to explore consumers’ post-pandemic (COVID-19) motivations for an e-retailer preference in an emerging market like India.

This study applied qualitative methodology to explore the research question, and 44 in-depth interviews were conducted with online consumers. The interviews were transcribed and analysed using open, axial and selective coding strategies.

This study identified seven post-pandemic motivations for consumers’ e-retailer preference, and the motivations were classified into: utilitarian (remote location and fast delivery, product choice and availability, comparative price and discounts and customer service), hedonic (aesthetics of the e-retailer store) and both utilitarian and hedonic (mobile-friendliness and user interface and interactivity).

Creating knowledge post-pandemic period is essential. This study communicates empirical evidence to suggest consumers are motivated through both utilitarian and hedonic motivation for an e-retailer preference in an emerging market. Furthermore, the researchers are encouraged to collect data from more developing countries and test the proposed e-retailer preference factors.

The study offers new knowledge to online retail managers to understand how emerging market consumers prefer an e-retailer and strive to attract and retain customers in the market.

Past studies have highlighted the importance of consumer online shopping motivations and channel preferences. However, there is limited literature investigating how consumers prefer an e-retailer over other e-retailers for online shopping. This study addresses the gap in the existing retailing literature and offers fresh insights into how consumers prefer an e-retailer post-pandemic from an emerging market context.

Effective management of risk and knowledge is critical to ensure the success of industry–university collaboration (IUC) projects. However, the intricate dynamics through which these factors influence the performance of IUC projects have yet to be fully investigated. The purpose of this study is to explore the interplay between risk management and knowledge management capabilities and their impact on IUC project performance.

A model was constructed and evaluated through the examination of a sample of 188 collaborative innovation projects located in the United Arab Emirates (UAE), utilizing structural equation models (SEM) and hierarchical regression analysis.

The findings indicate that social system risk, technical system risk and project management risk have a negative impact on the performance of university–industry collaboration (UIC) projects, while cultural, technical and structural knowledge management capabilities can mitigate the negative impact of these risks on the performance of IUC projects.

The study concludes with three recommendations aimed at improving the management of UIC projects, including the establishment of a distinct and precise management strategy, the deployment of a comprehensive and systematized management methodology and the adoption of a balanced management framework.

The originality and value of this study lie in its exploration of the interplay between risk management and knowledge management capabilities in IUC projects. While previous studies have examined either risk management or knowledge management in IUC projects separately, this study provides a comprehensive analysis of both factors and their combined impact on project performance. The study also contributes to the literature by highlighting the specific risks and knowledge management capabilities that are most relevant to the context of IUC projects in the UAE. The practical recommendations offered by the study can help project managers and stakeholders to improve the success of collaborative innovation projects.

The study aims to identify the practical borders of AI legal personality and accountability in human-centric services.

Using a framework tailored for AI studies, this research analyses structured interview data collected from auditors based in Poland.

The study identified new constructs to complement the taxonomy of arguments for AI legal personality: cognitive strain, consciousness, cyborg paradox, reasoning replicability, relativism, AI misuse, excessive human effort and substitution.

The insights presented herein are primarily derived from the perspectives of Polish auditors. There is a need for further exploration into the viewpoints of other key stakeholders, such as lawyers, judges and policymakers, across various global contexts.

The findings of this study hold significant potential to guide the formulation of regulatory frameworks tailored to AI applications in human-centric services. The proposed sui generis AI personality institution offers a dynamic and adaptable alternative to conventional legal personality models.

The outcomes of this research contribute to the ongoing public discourse on AI’s societal impact. It encourages a balanced assessment of the potential advantages and challenges associated with granting legal personality to AI systems.

This paper advocates for establishing a sui generis AI personality institution alongside a joint accountability model. This dual framework addresses the current uncertainties surrounding human, general AI and super AI characteristics and facilitates the joint accountability of responsible AI entities and their ultimate beneficiaries.

The purpose of this study is to identify the capacity needs of building professionals to deliver environmentally sustainable buildings (ESBs) globally, from a unique systems approach. Through a review of extant literature, this study contributes to knowledge of the global delivery of ESBs by identifying research trends and gaps that can be tackled in future research, and current hotspots in capacity building (CB) research within the built environment (BE). The adopted systems approach to CB postulates that the construction industry is systemized in nature, and thus, CB solutions within the industry should be approached from a systems approach.

A literature search was conducted using the Scopus search engine, augmented by Google Scholar and Web of Science, to produce 54 relevant articles for analysis. The scientometric analysis was undertaken with the use of VOSViewer to better understand the broad literature on CB in the construction industry which would not have been possible with traditional data analysis. The content analysis allowed, for a systematic review of selected articles, to reveal key themes in this study.

Through a content analysis, four levels of CB were identified within the construction industry; individual level, organizational level, industry level and state level. Nine sub-capacities were subsumed under the four identified levels adopted from Potter and Brough (2004), including but not limited to Performance capacity, Workload capacity, Supervisory capacity, Industry Role capacity and Systems capacity. Under each sub-capacity, key questions were posed to aid identify the capacity needs of BE professionals. A framework for identifying capacity needs in the BE is proposed.

The findings of this study serve as a useful reference for practitioners and policymakers to assess their level of commitment to CB efforts for ESB delivery. The findings of this study have revealed that building the capacities of BE professionals to deliver ESBs should be addressed as part of a broader framework, interdependent on the other levels of CB in the systemic construction industry.

As a review study identifying capacity needs for BE professionals to deliver ESBs, this study enhances knowledge of CB within the construction industry.