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As innovations introduce novel benefits to customers, they would need to be positioned in a way that sets them apart in the market. The purpose of this paper is to propose a novel approach for the positioning of innovations with the use of the customer imagination and, specifically, mental movies.

Using the schema approach as this study’s theoretical framework, the author proposes that innovations could be positioned using moving pictures (i.e. mental movies) instead of mental pictures (the approach traditionally taken).

A new conceptual framework for the positioning of innovations using mental movies is presented. In the framework, this study outlines how innovations can be positioned with the use of mental movies, and why such an approach would be beneficial. The framework outlines mixed reality, i.e. augmented reality, augmented virtuality and virtuality, as well as the metaverse and gaming as avenues for positioning innovations using mental movies. On the benefit side, the framework identifies successful market introductions, engagement and stickiness, memorability and positive emotions, uniqueness and differentiation and market share as the concrete benefits that can be achieved with this type of positioning.

The framework provides a novel approach for the positioning of innovations. It departs from existing literature by proposing that innovations can be positioned using mental movies. The framework also identifies why this approach would be beneficial for marketers and managers and provides concrete guidelines for how such a positioning can be achieved in the market.

Brand reputation (BR) is one of the most important factors that affect the consumer–brand relationship and give businesses a competitive advantage. Businesses with a strong BR can increase their market shares and product market prices, in addition to gaining a competitive advantage. In order for businesses to have these advantages, they need to know and analyze their consumers. This study aimed to develop an alternative analysis method by using classification algorithms and regression analysis to measure and evaluate the effect of consumers' BR perceptions on their willingness to pay premium prices (WPP).

The research data were collected from 483 participants by the online survey method due to the COVID-19 pandemic. The data were first analyzed with regression analysis, and the effect of BR on WPP was found to be significant. Then, using artificial intelligence (AI) methods that were not used in previous studies, consumers' perceptions of BR and WPP were clustered and classified.

The results revealed the highest and lowest customer groups with BR and WPP and empirically demonstrated that highly accurate practical classification models can be applied to determine strategies in line with these findings.

The model proposed in this study offers an integrated approach by using AI and regression analysis together and tries to fill the gap in the literature in this field. Therefore, the novelty of this study is to quantitatively reveal and evaluate the relationship between BR and WPP by using AI classification algorithms and regression analysis together.

The purpose of this article is to develop relationships between many major issues relevant to the agriculture supply chain.

With the purpose of gaining an all-encompassing understanding of the agriculture supply chain, this work uses 233 filtered research articles and three bibliometric analysis tools, namely VOSviewer, term frequency-inverse document frequency (TF-IDF) and Person correlation. The collected research publications were also catalogued using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA).

Using analytic techniques, a total of 12 keywords were obtained. The study found that agri-products are in dire need of digitisation via Internet of things (IoT) and blockchain due to the usage of economic variables and comprehensive management of total food waste throughout transportation, anchoring quality and the predominant variable.

The study was limited to the Scopus and Web of Science (WoS) indexing in order to assess the viability of the linked idea and problem.

This study aims to generate vital knowledge in the field of horticulture-focused agriculture supply chain based on previous justification and relationship formation.

The Russia–Ukraine war has disrupted the wheat supply worldwide. Given that wheat is one of the most important agri-food products in the world, it is necessary to pay attention to the wheat supply chain during the global crises. The use of resilience strategies is one of the solutions to face the supply chain disruptions. In addition, there is a possibility of multiple crises occurring in global societies simultaneously.

In this research, the resilience strategies of backup suppliers (BS) and inventory pre-prepositioning (IP) were discussed in order to cope with the wheat supply chain disruptions. Furthermore, the p-Robust Scenario-based Stochastic Programming (PRSSP) approach was used to optimize the wheat supply chain under conditions of disruptions from two perspectives, feasibility and optimality.

After implementing the problem of a real case in Iran, the results showed that the use of resilience strategy reduced costs by 9.33%. It was also found that if resilience strategies were used, system's flexibility and decision-making power increased. Besides, the results indicated that if resilience strategies were used and another crisis like the COVID-19 pandemic occurred, supply chain costs would increase less than when resilience strategies were not used.

In this study, the design of the wheat supply chain was discussed according to the wheat supply disruptions due to the Russia–Ukraine war and its implementation on a real case. In the following, various resilience strategies were used to cope with the wheat supply chain disruptions. Finally, the effect of the COVID-19 pandemic on the wheat supply chain in the conditions of disruptions caused by the Russia–Ukraine war was investigated.