Stakeholder Involvement in Evaluation: Does it Affect Observers' Perceptions of an Evaluation? And Which Stakeholder Group(s) Do People Think Should to Participate?

A Technology Aid to Help People with Blindness and Moderate Intellectual Disability Retrieve Common Objects from Storage Units: A Proof-of-Concept Study

BACKGROUND

People with blindness and intellectual disability can have problems locating, identifying, and retrieving objects needed for daily activities (e.g., clothes and food items) from familiar storage contexts, such as cupboards and cabinets.

OBJECTIVE

This preliminary study assessed a technological system designed to help three people with those problems improve their performance.

METHODS

The technological system, which involved the use of tags with radio frequency identification codes, a smartphone, and a tag reader, aimed to guide the participants in searching and retrieving objects from three different storage units. In practice, the system provided different feedbacks depending on whether the participants were searching (a) in a wrong storage unit, (b) in a wrong shelf/drawer of the right storage unit, or (c) in the right shelf/drawer of the right storage unit.

RESULTS

All participants were successful in retrieving objects correctly with the technological system. The results also showed that (a) the participants preferred using the system over a control strategy, (b) were able to switch on and off the system independently, and (b) staff rated the system positively.

CONCLUSIONS

These preliminary findings suggest that the system might be a useful support tool for people with blindness and intellectual disability.

Multistage Supply Chain Channel Principal-Agent Model in the Context of e-Commerce With Fairness Preference

This research aims to investigate information asymmetry in e-commerce supply chain channels and the impact of the fair preference model on the behavior and returns of channel members. Therefore, by contrasting it with the model in the completely rational case, this research establishes a more realistic principal-agent model and incorporates the fair preference model into the e-commerce supply chain channel. According to the model's analysis, the effort level of the retailer at each stage is positively correlated with the e-commerce efficiency coefficient, and the incentive coefficient of manufacturers is positively correlated with the e-commerce efficiency coefficient in the case where all rationality is assumed. Manufacturing companies' anticipated profits are positively correlated with the e-commerce efficiency coefficient. According to the fair preference model, retailers will put forth more effort to sell products when their fixed income from manufacturers is higher and their optimal effort level is positively correlated with that income. When e-commerce's efficiency coefficient is higher than 1, the retailer's revenue and effort exceeded those of traditional channels. Manufacturers and retailers both experience Pareto improvements in their earnings after the fair preference model is introduced.