Annals of Behavioural Science

Description

The developed system makes it possible to keep food from going bad at any point in its life cycle. Software, hardware, and information components ensure the system's operation. Databases related to the software are created and obtained from customers by filling out web forms or using a mobile app to create the information component. The region takes into account the social aspect of the system because it cannot be considered a full-fledged system without it. In turn, the type of consumer behavior influences the consumer's decision to participate in this system. The author looked into the idea of "consumer behavior" and thought about how it could be changed to get a better understanding of the social aspect of the developed system. The psychology and economics of how consumer behavior is formed are discussed in the paper. Consideration is given to the possibility of employing social engineering techniques to alter consumer behavior in order to encourage participation in the system for collecting information. It is described the phases of consumer choice during which it is possible to alter consumer behavior. In order to investigate consumer behavior, the author conducted interviews with 1,000 respondents. The author came up with a simulation model based on the survey results that shows how customers move through the store's trading hall.

Simulation Model

The simulation model is used to determine the main points of influence for the customer in the trading hall. Within the framework of the developed concept of smart packaging, the author has developed and recommended the application of strategies for modifying consumer behavior. To make better use of Augmented Reality (AR) by retailers, it is essential to comprehend the behavioral responses of customers. By providing consumers with engaging and immersive information about products and services, Augmented Reality (AR) enhances consumers' shopping experiences in both the online and offline retail markets. By measuring the impact that product involvement has on the AR flow experience, the authors of this paper measure consumers' behavioral responses to the experience. In order to accomplish this, the study employs a quantitative strategy based on information gathered between August and September 2022. According to the findings, consumers' involvement with products influences their AR flow experience as well as their behavioral intentions, such as their intention to make a purchase and visit the retailer's website to share or recommend the experience. Additionally, the latter two variables mediate the relationship between the augmented reality flow experience and customer loyalty, providing intriguing insights into products that involve a lot of the body.

The paper concludes by highlighting the primary theoretical and managerial ramifications of these findings and the potential for additional investigation. Consumer participation in the acquisition, use, and disposal of goods and services is necessary for the operationalization of Circular Economy (CE) strategies. However, it is still in its infancy to encourage CE-oriented consumer behavior and sustainable consumption patterns to enable the CE in practice. In relation to the 10R circular strategies, the purpose of this study is to define, frame, and quantify consumer contributions to the implementation of the CE: reduce, reevaluate, recycle, repurpose, remanufacture, rehabilitate, repair, reuse, and discard A conceptual analysis and semi-systematic literature review are used in the study to create a comprehensive framework for consumer behaviors that are related to CE perspectives in practice. The manuscript focuses on three objectives. First, a three-dimensional consumer role in supporting the CE transition is mapped, with the consumer acting as (i) a product customer who purchases goods or services, (ii) a product user who preserves the value of goods, and (iii) an end-of-life product holder who disposes of goods. To close the loop on products through (i) careful use and maintenance, (ii) proper collection, and (iii) reuse, repair, or recycling, it is essential to frame this three-dimensional contribution. Second, a CE-related product typology consisting of fifteen categories of circular products is proposed on the basis of the developed "closing–slowing and future–past" matrix. Thirdly, the fifteen identified circular product categories are ranked from more circular to less circular using a five-level hierarchical pyramid for CE-related products. As a result, the five levels of consumer contributions to the CE, ranging from low to high, correspond to the identified circular product categories.

Behavior Factors

To monitor and quantify consumer contributions to the CE at the product level, a novel product-centric framework of CErelated consumer behavior is developed. The resulting conceptual framework provides producers and policymakers with additional perspectives for managing the process of directing consumer behavior toward consumption alternatives that are more sustainable and circular. Using reactive, resilient, and digital methods, a circular economy can help lessen the impact of plastic waste. Additionally, it may make it easier to use less plastic. As a result, the implementation of a circular economy for plastic waste is anticipated to be most affected by consumer behavior and digitalization. The purpose of this paper is to learn how consumer behavior and digital ecosystem efficiency influence national plastic waste. This led to the use of international databases and the statistical technique known as Receiver Operation Characteristic (ROC) to investigate the amount of plastic waste produced in eight European nations. The generations of plastic waste served as the dependent actual state variable for this purpose, and the independent test variables were the digital ecosystem and consumer behavior factors. ROC plots were created between the aforementioned state and test variables in order to determine the Area Under the Curve (AUC) indices. A higher AUC (area under the curve) of 0.6 indicated that consumer behavior has a significant impact on the production of plastic waste in European nations. The findings indicate that the digital ecosystem factors associated with low plastic waste generation also controlled the amount of plastic waste produced in the study area (AUC 0.5). While the digital ecosystem context reduced plastic pollution, overall consumer behavior in the selected European nations demonstrated an unskilled role in the higher generation of plastic waste.

Some managerial recommendations for the circular economy of plastic waste in the context of consumer behavior and digitalization emerged from the confirmation of the research hypotheses. The findings suggest a more elaborate framework for the circular management of plastic waste that includes a reduction in waste generation, recycling in waste circulation, recovery in waste valorization, and resource efficiency through the digitalization of design technology and consumer behavior education. In developed nations, numerous studies on the SFSC that employs social commerce have been conducted; however, very little research has been done on this topic in developing nations. By considering information-seeking variables as components of knowledge formation and the perceived economic and social sustainability of SFSCs as advantages over long food supply chains. The alphabet theory and the theory of planned behavior served as the foundation for our conceptual framework, which included a perceived SFSC sustainability variable. The information was obtained from chat group members of social commerce SFSCs and agricultural product purchasers. Product knowledge's influence on perceptions of SFSC sustainability is positively correlated with informationseeking behavior, according to the findings. The intention to buy is influenced by attitude, which in turn is influenced by perceived sustainability of the SFSC. If there is a clear plan, customers are more likely to buy; for consumers with sufficient social media information, subjective norms have no effect on purchase intention. Because it is common practice to purchase agricultural products, perceived behavioral control has no effect on purchase intention.