Food waste, power, and corporate social responsibility in the Australian food supply chain

By examining corporate social responsibility (CSR) and power within the context of the food supply chain, this paper illustrates how food retailers claim to address food waste while simultaneously setting standards that result in the large-scale rejection of edible food on cosmetic grounds. Specifically, this paper considers the powerful role of food retailers and how they may be considered to be legitimately engaging in socially responsible behaviors to lower food waste, yet implement practices that ultimately contribute to higher levels of food waste elsewhere in the supply chain. Through interviews with key actors in the Australian fresh fruit and vegetable supply chain, we highlight the existence of a legitimacy gap in corporate social responsibility whereby undesirable behaviors are pushed elsewhere in the supply chain. It is argued that the structural power held by Australia’s retail duopoly means that supermarkets are able to claim virtuous and responsible behaviors, despite counter claims from within the fresh food industry that the food supermarkets’ private quality standards mean that fresh food is wasted. We argue that the supermarkets claim CSR kudos for reducing food waste at the expense of other supply chain actors who bear both the economic cost and the moral burden of waste, and that this is a consequence of supermarkets’ remarkable market power in Australia.

The selection, optimization, and compensation model in the work context: A systematic review and meta-analysis of two decades of research

Over the past two decades, the selection, optimization, and compensation (SOC) model has been applied in the work context to investigate antecedents and outcomes of employees' use of action regulation strategies. We systematically review, meta-analyze, and critically discuss the literature on SOC strategy use at work and outline directions for future research and practice. The systematic review illustrates the breadth of constructs that have been studied in relation to SOC strategy use, and that SOC strategy use can mediate and moderate relationships of person and contextual antecedents with work outcomes. Results of the meta-analysis show that SOC strategy use is positively related to age (rc = .04), job autonomy (rc = .17), self-reported job performance (rc = .23), non-self-reported job performance (rc = .21), job satisfaction (rc = .25), and job engagement (rc = .38), whereas SOC strategy use is not significantly related to job tenure, job demands, and job strain. Overall, our findings underline the importance of the SOC model for the work context, and they also suggest that its measurement and reporting standards need to be improved to become a reliable guide for future research and organizational practice.

Ship collision avoidance and COLREGS compliance using simulation-based control behavior selection with predictive hazard assessment

This paper describes a concept for a collision avoidance system for ships, which is based on model predictive control. A finite set of alternative control behaviors are generated by varying two parameters: offsets to the guidance course angle commanded to the autopilot and changes to the propulsion command ranging from nominal speed to full reverse. Using simulated predictions of the trajectories of the obstacles and ship, compliance with the Convention on the International Regulations for Preventing Collisions at Sea and collision hazards associated with each of the alternative control behaviors are evaluated on a finite prediction horizon, and the optimal control behavior is selected. Robustness to sensing error, predicted obstacle behavior, and environmental conditions can be ensured by evaluating multiple scenarios for each control behavior. The method is conceptually and computationally simple and yet quite versatile as it can account for the dynamics of the ship, the dynamics of the steering and propulsion system, forces due to wind and ocean current, and any number of obstacles. Simulations show that the method is effective and can manage complex scenarios with multiple dynamic obstacles and uncertainty associated with sensors and predictions.