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The purpose of this study is to identify the accelerators of sharing economy that lead to sustainability by adopting green consumption. Nostalgia is studied as a mediator along with social connectedness and past orientation. Specifically, the study is based upon a framework to explore the outcomes of sharing economy through an individual's green consumption behavior from the perspective of mortality anxiety.

Quantitative research technique was employed by collecting data from 537 households through snowball sampling. The model was tested using partial least squares (SEM-VB). The validity of the theoretical and measurement model was assessed.

The results revealed that nostalgia positively influences social connectedness and past orientation, whereas social connectedness and past orientation accelerate green consumption. However, it was confirmed that nostalgia decreases green consumption.

The drivers of sharing economy lead toward environmentally friendly consumer behavior by providing opportunities for different agents to increase the usage of shared consumption. The model can be improved by introducing other mediating variables to enrich understanding.

The study may provide opportunities for practitioners and the government to identify the key factors in a sharing economy, specifically with reference to green consumption and social connectedness. It is predicted that it will help reduce environmental deterioration.

This study identifies the role of mortality anxiety and nostalgia toward green consumption, predominantly in the context of a sharing economy. It is a forward to collaborative consumption.

This study relies on an integrated model to study the role of instant mobile messaging apps in the pandemic. The COVID-19 pandemic is reshaping different forms of businesses; one of them is digital marketing. Many aspects of digital marketing augmented in response to the consequences of the virus. A comparative study between Pakistan and Iraq is conducted to investigate the resistors of innovation with the mediation of intention toward actual system usage. It examines the behavioral intentions and actual behavior of individuals in response to the resistance toward innovation.

A total of 800 responses were collected through a convenient sampling method from individuals residing in Pakistan and Iraq in the first wave of COVID-19. The data was analyzed through covariance-based structural equation modeling; SPSS and Smart PLS 3.0 were used as efficient data analysis tools in the study.

The results inferred that individuals are faced with resistance to innovation when they adopt innovative technology. It was inferred that technology adoption is not poised through image both in Pakistan and Iraq. Intention toward actual behavior was determined to be a potential mediator, which enhances the stature of the integrated model.

The significance of this study considering practical and theoretical implications is incorporated for marketer’s policymakers and consumers, along with recommendations for future research.