Factors influencing the online apparel recycling behavior in China: a multiple stage analysis using PLS-SEM and fsQCA

Purpose – As the major apparel manufacturer and exporter, China is under the pressure to tackle the environmental issue brought by the over-consumption of apparels, as the apparel and textile waste is one of the main sources of landfill contributing to solid waste. Disposing used clothes appropriately such as recycling can alleviate the problem posted by discarded apparel. This study aims to ascertain factors that influence consumers’ online recycling behavioral intentions. Design/methodology/approach – This research proposed a theoretical framework via the combination of theory of planned behavior (TPB) and technology acceptance model (TAM). With 294 data collected online, the study used partial least squares structure equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to carry out analysis to examine research hypotheses. Findings – The study results revealed that perceived behavioral control, attitude and perceived ease of use (PEU) along with perceived usefulness (PU) can affect people’s recycling behavioral control. Moreover, PEU and PU can positively influence consumers’ attitudes toward recycling apparel online. Furthermore, the fsQCA analysis revealed heterogenous configurations to generate recycling behavioral intention, notably revealing that the environmental concern alone may not be sufficient to predict people’s recycling behavioral intention, since the combined effects of environmental concern along with other proposed variables have an impact on people’s decision. Practical implications – The findings would assist the policymakers and apparel industry in better understanding consumers’ online recycling behaviors and attitudes. Moreover, the authors indicated the importance of reducing barriers and difficulties for people to engage in recycling. Originality/value – Current literature is deficient in understanding consumers’ online apparel recycling behavior. As such, this study suggests policymakers and the apparel industry providing user-friendly and convenient technology for consumers to deal with unwanted clothes. Moreover, clear departure from previous research, this study combined PLS-SEM and fsQCA analysis, deriving unique insights into the complex variable relationships. The fsQCA analysis revealed heterogenous configurations to generate online apparel recycling behavior. The joint analysis revealed that consumers’ environmental concern alone will not induce their recycling behaviors. With the support of empirical data, this research contributes to a broader understanding of consumers’ behavior and factors influencing their intention to recycle apparel online.