Intentions to Create Green Start-Ups for Collection of Unwanted Drugs: An Empirical Study

Abstract

Drug waste poses a real threat to human health and the environment. Therefore, recycling and sustainability scholars have recently sought practical solutions to the drug waste problem. Furthermore, several governments have made significant efforts to reduce the negative effects of waste, such as establishing programs to take back unwanted drugs (expired and unused) for recycling (i.e., drug reuse or drug redispersing). However, many of these programs have failed to achieve their goals. In this context, it is expected that creating green start-ups to collect unwanted drugs will contribute to solving this problem. Accordingly, this study aims to investigate the antecedents of intentions to create green start-ups for collecting unwanted drugs. To this end, the authors integrate start-up self-efficacy and drug waste collection-related knowledge constructs into the theory of planned behavior (TPB). Using a self-administered paper questionnaire and relying on a convenience sample, data were collected from 328 students in six Algerian universities. A hierarchical multiple regression was conducted to test the proposed study model. Theresults revealed that perceived behavioral control (PBC)(β = 0.187, p< 0.001), attitudes (β = 0.182, p = 0.002), start-up self-efficacy (β = 0.169, p = 0.001), drug waste collection-related knowledge (β = 0.161, p< 0.001), and subjective norms (β = 0.088, p< 0.05) have a positive significant effect on the intention to create a start-up to collect unwanted drugs. In conclusion, this paper contributes to reducing drug waste by investigating the drivers of intention to create green start-ups for collecting unwanted drugs. Therefore, our study is expected to provide valuable insights for hospitals, pharmacies, pharmaceutical manufacturers, environmental protection associations, and stakeholders interested in reverse logistics.

Investigating Farmers’ Intentions to Reduce Water Waste through Water-Smart Farming Technologies

“…Furthermore, the variance inflation factor (VIF) and tolerance tests were employed to address the issue of multicollinearity. Next, following the studies of Njoku et al [68] and Russell and Knoeri [52], hierarchical regression analysis was used to test the hypothesized relationships between antecedents and farmers' intentions, confirming the feasibility of adding additional lenses to the original TPB model.…”

“…Additionally, Cronbach's alpha coefficients were calculated to check reliability. The skewness and kurtosis tests were also used to ensure that the data followed a normal distribution [68]. Furthermore, the variance inflation factor (VIF) and tolerance tests were employed to address the issue of multicollinearity.…”

“…In their meta-analysis, Ruzzante et al [28] found that the adoption of agricultural technology was associated with farmers' education level. In the context of start-up medication waste collection projects, Njoku et al [68] found that the intention to create such projects was influenced by knowledge about medication waste collection. According to Li et al [33], knowledge about waste minimization is a strong predictor of construction waste reduction behavior.…”

“…As in many previous studies related to sustainable behavior [52,68], the authors relied on a self-reported questionnaire as a data collection tool. The authors also used a five-point Likert scale to measure responses, with a score of "1" indicating "completely disagree" and a score of "5" indicating "completely agree".…”

“…Additionally, the PBC scale was drawn from Mouloudj et al [19] and Wang et al [53], and the perceived usefulness scale was obtained from Li et al [66]. As for the water waste reduction-related knowledge scale, it was modified from the scales used by Njoku et al [68] and Zhang et al [75]. Finally, farmers' intentions to reduce water waste were measured using a scale adapted from Borusiak et al [76] and Mouloudj et al [19].…”