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This study examines the existing literature on generative artificial intelligence (Gen AI) and its impact across many sectors. This analysis explores the potential, applications, and challenges of Gen AI in driving innovation and creativity and generating ideas.

The study adopts a comprehensive literature review approach, carefully assessing current scientific articles on Gen AI published from 2022 to 2024. The analysis examines trends and insights derived from research.

The review indicates that Gen AI has significant potential to augment human creativity and innovation processes as a collaborative partner. However, it is imperative to prioritize responsible development and ethical frameworks in order to effectively tackle biases, privacy concerns, and other challenges. Gen AI is significantly transforming business models, processes, and value propositions in several industries, but with varying degrees of effect. Findings indicate also that despite the theory-driven approach to investigating Gen AI's creative and innovative potential, cutting-edge applications research prioritizes examining the possibilities of Gen AI models.

Although this review offers a picture of great possibilities, it concurrently underlines the necessity for a deep knowledge of Gen AI nuances to fully harness its capabilities. The findings indicate that continuous research and exploration efforts are required to address the challenges of Gen AI and assure its responsible and ethical implementation. Therefore, more study is needed on enhancing human-AI collaboration and defining ethical norms for varied circumstances.

This study presents a relevant analysis of Gen AI's transformational potential as an innovation catalyst. It emphasizes major potential, applications across industries, and ethical issues for responsible integration.

This study aims to answer the question of what characterizes organizations with future-potential, and with the help of a model introduced in this study, the authors propose what interventions can be identified and which improvements need to be made in traditional organizations so that they meet the requirements of future-potentiality.

A systematic literature review was conducted to identify management interventions. Citation and co-word analyses were also performed. Content analysis of 311 journal articles from the past five years was performed taking into account relevant keywords, and disciplinary narrowing was also applied. These articles were used to identify knowledge that could be used to suggest micro-, meso- and macro-level changes.

To develop the future potential of organizations, three organizational levels must be separated. The first is the micro level of relations between leaders and employees, where equity is a key value for future potentiality. It should be emphasized that not all employees’ organizational commitment is equally important for organizations with future potential, and leaders should strengthen their commitment according to individual needs and opportunities. The second is the meso level, where the decisive value is organizational moderation, and this suggests that a careful and restrained development is needed both in satisfying consumer needs and in innovation. The third is the macro level, where the defining value is responsibility and sustainability, which are necessary for achieving a state where the active development of national culture becomes possible.

Contrary to the authors’ expectations, it has been found that there are only a few studies dealing with change management for the purpose of achieving a future potential mode of organizational operation; thus, the results can be considered new and will contribute to the development of a cross-section of change management and future studies.

This paper aims to determine the key factors and provide an effective model to enhance the performance of sustainable supply chain management (SSCM).

Data were collected using a semi-structured interview technique, a snowball sampling method and qualitative study method. For this purpose, ten supply chain and food production managers and experts were interviewed semi-structured. The data were analyzed using open, central and selective coding methods with grounded theory approach. In the proposed model, 13 principal codes have been specified, including organizational productivity, sustainable supply chain (SSC), industry supply chain, macro policies, organizational performance, social factors, economic factors, organizational factors, political factors, technology, manufactured products, customer and supply chain failures.

The model and concepts obtained from the participants clearly show that several reasons and motivations are involved in increasing the performance of SSCM. Moreover, the designed model indicates that the motives and reasons for turning to this system are satisfactory when implemented.

The distinctive and knowledge-enhancing feature of this paper compared to previous studies is the focus on the selected background, intervening and causal factors with the influence of strategies designed to achieve a new and local model for the SSC model and assess its impact on organizational performance and productivity. The proposed components of this paper have not been investigated so far.