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The global food waste and food scarcity paradox is steadfastly increasing. This study aims to examine the effects of digital nudging as forms of positive and negative reinforcement to change food waste behavior and found that nudging positive reinforcement modifies this habit.

A field experiment was conducted on 628 diners randomly split into experiment (n = 412) and control group (n = 216) in two separate dining locations over four weeks. Out of these, 412 diners were randomly subjected to tent cards with positive (n = 228) and negative (n = 184) reinforcement nudging and completed a questionnaire to ascertain if nudging affects their consumption behavior. Consumption waste per unit revenue was calculated from all 628 diners individually to analyze the financial impact between control and experiment groups.

SEM analysis reveals that positive reinforcement mediates between external motivators (social media and restaurant service) and reduction of food waste behavior. Further analysis also reveals that nudging has a higher three times effect on reducing food waste as compared with no nudging (control).

Positive messaging encourages behavior change more effectively as compared to negative ones. Gentle reminders of how everyone can personally be a “warrior” or “hero” in the fight against global food waste increases the likelihood of altruistic motivation in tackling these issues.

This study demonstrates how positive reinforcement in the form of nudges acts as key mediator to support reduction of consumer food waste on site, ultimately helping to reduce financial costs compared to those without nudges.

This conceptual chapter aims to understand the role of artificial intelligence (AI) in value co-creation phenomena in a healthcare service ecosystem, through a literature review and the definition of a conceptual framework. AI, as an operant resource, can stimulate a completely patient-centered, adaptive and resilient healthcare system, and governance models in healthcare based on data-driven decision-making (DDDM), ensuring faster choices, more timely diagnosis and more personalized treatment paths. However, the full implementation of AI in healthcare is inhibited by some frictions, mainly related to the risk that the AI black box may generate an inadequate automatic decision, also due to the quality of data used, often partial and unstructured given the reluctance to share them by patients concerned by privacy threats. The co-design (multi-part and multi-level) of a predictive decision model based on the functional transparency of the AI algorithm would allow for augmented decision as result of an effective human–machine interaction. Healthcare actors could thus make decisions using the information detected by the software (based on clear cause-and-effect correlations and modifiable variables in case of mistakes), integrated with their professional knowledge. This would also help to strengthen the patient’s perception of the decision’s reliability and accuracy and the safety of the tool (factors that can affect his/her trust). AI may be considered as a driver for value co-creation in healthcare, thanks to transparency. It would allow the promotion of collaborative behaviors involving actors by generating new institutions and new resource integration practices among them.

The purpose of this paper is to appraise and evaluate empirical research on circular economy in food systems, consolidating the existing knowledge and identifying shortcomings in this emerging body of research.

The authors conducted a systematic literature review of 136 studies from the electronic databases Scopus and Web of Science. The authors also developed a thematic analysis and summarized the results in a framework.

The authors identified seven critical issues for the transition to circular food systems: consumer behavior, multistakeholder coordination, business models, digital technologies, barriers, transition processes and performance and measurement systems. Moreover, the authors provide an agenda for future research on these topics.

While reviews on the circular economy are spreading rapidly, no reviews have comprehensively addressed the critical issues for the transition to circular food systems in the business, management, and organization domains.

In dynamic business environments, organizations must constantly adapt and learn. Nudging, a concept from behavioral economics, offers a novel approach to influence organizational behavior and learning. This article explores the integration of nudging within organizational learning, drawing from Thaler and Sunstein’s work and organizational learning theories. Also, To investigate nudging’s role in organizational learning and propose a practical nudging framework, while addressing ethical considerations.

The article combines theoretical insights from behavioral economics (Thaler and Sunstein; Kahneman) with organizational learning theories (Argyris and Schön). It discusses real-world nudging applications, like Google's health initiatives, and examines the ethical aspects of workplace nudging.

Nudging effectively influences organizational decisions and strategies by targeting rapid cognitive processes. It finds application in training, performance management, and decision-making, with a critical focus on ethical implications, especially regarding autonomy and non-manipulation.

This study highlights the potential of behavioral economics in reshaping organizational learning, emphasizing the importance of ethical application in developing adaptive, learning-focused organizational cultures.

Nudging offers a promising method for enhancing organizational learning. Applied ethically, it can improve workforce engagement, performance, and adaptability. Future research should focus on nudging's long-term organizational impacts and ethical boundaries.

Merging library traffic from dispersed service points into a combined services desk is not new, and many reasons prompt this move. George Mason University, Virginia’s largest public research institution, combined a total of 10 service desks located in four libraries on three distributed campuses. To consolidate services and reduce costs, the Mason Libraries established a “one-stop” service point in each library. With the goal of “one-stop” service point in each facility, the Mason Libraries recrafted physical spaces, reviewed policies, procedures, and workflows as well as revised staff roles and responsibilities.

This chapter explores why institutions embark on redesigning the traditional library service desk; discusses how changing service needs impact desk space; and addresses the effect on public services personnel. Observations are based on highlights from the evolution of George Mason University Libraries’ goal of a “one-stop” service point in each library to provide more efficient and consistent user-focused interactions and services.

As a manager of one of the facilities, the author provides insights on achieving a “one-stop” service point.

This chapter considers library staff needs, in concert with internal effort to not only refine user services influencing changes, but also revisit policies, procedures, and workflows to align staff roles and responsibilities. Mason Libraries is one of a few university library systems trying to implement single service points in all libraries.

Multi-criteria methods represent an adequate tool for solving complex decision problems that provide real support to the decision maker in the choice process. This paper analyzes a decision problem that recurs over time using one of the newer methods as the Parsimonious AHP.

In this paper we integrated the P-AHP with: (1) the weighted average which takes into account the objectivity of the data; (2) ordered weighted average (OWA) aggregation operators that address the subjective nature of the data; (3) the Choquet integral and (4) the Sugeno integral which also considers the uncertain nature of the final ranking as it is defined on a fuzzy measure.

The present paper proves that variations in the final ranking, due to the different mathematical properties of the selected aggregators, are fundamental to select the best alternative without neglecting any characteristic of the input data. In fact, it is discussed and underlined how and why the best alternative is one that never excels but has very good positions with respect to all aggregation operator rankings.

The aim and innovation presented in this work is the use of the Parsimonious AHP (P-AHP) method in a dynamic way with the use of different aggregation techniques.

The purpose of this paper is to consider the factors that influence food plate waste in a UK university food service setting and the insinuated intention to waste food among staff and students.

The study conducted empirical research using an online questionnaire (n=260) at the university. The data were analysed descriptively and inferentially by IBM SPSS Statistics version 22.

Multiple factors influence the level of food plate waste including gender, different categories of food, plate size, portion size and palatability. Two recommendations to reduce plate food waste in the university food service setting include providing a variation in plate size and pricing strategy by portion rather than a whole meal, and communicating with staff and students in the food service setting.

The research contributes, along with previous studies, by focussing here on participants’ food waste intention in food service settings and evidencing the factors of influence.

The research contributes to understanding on participants’ food waste intention in food service settings.

A central question of public administration is how political principals secure the cooperation of administrators within organisational frames and contexts; increasingly, rational influences are being considered alongside bounded rationality and non-rational influences. This paper aims to explore the intent of New Zealand’s Public Service Act 2020 in managing administrative behaviour.

The methodology is primarily ethnographic, combining emic and etic perspectives. A mixed-methods approach comprises participant observer field notes and meeting documentation, substantiated by official documents; documents were analysed thematically and triangulated with other data sources.

The Public Service Act introduces new bounds on administrative behaviour. The stated rationale for these changes reveals an attempt to set limits on the principal–agent relationship between politicians and administrators and causes predictable deviations from rational behaviour by cultivating public service motivation and a unified public service identity.

As the legislation in question was only passed in 2020, it is too early to definitively assess the ultimate impact of legislation on administrative behaviour. This case study demonstrates that behavioural approaches to public administration are being applied intentionally by governments. The choice architecture created in the case study blends rational, bounded, and non-rational influences. Together, this produces a bricolage of semi-relevant theories from other disciplines, especially psychology, to explain administrative behaviour. Further refinement is needed to develop a cohesive and comprehensive theory of administrative behaviour that can account for contemporary practice.

Administrators act as agents of political principals, within ethical and rules-based limitations and influenced by public service motivation and social identity. Shifting from implicit to explicit choice architecture does not negate possible tensions between bounds and can signal them more explicitly. Shared symbols are sometimes intended to influence identity and therefore adherence to behavioural norms.

This paper explores the manipulation of choice architecture as a viable strategy for altering behaviour for the better and, to the best of the authors’ knowledge, is the first known instance of choice architecture being “legislated in” rather than merely “showing through”. This study illustrates the blending of rational, boundedly rational and non-rational factors into a choice architecture for public administrators that help mediate the biases and challenges of principal–agent relationships (which form a cascade in New Zealand’s public administration system).