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Given the concept of loafing at work and its IT equivalent, cyberloafing, we propose the concept of BallotLoafing to metaphorically describe a similar phenomenon occurring during political elections. BallotLoafing describes how employees’ attention can become absorbed by discussions, debates or following news related to an election, shifting focus away from work tasks. This study aims to investigate the effects of attitude, subjective norm and perceived behavioral control on employees’ intention to engage in BallotLoafing behaviors through the lens of the theory of planned behavior. Additionally, the research explores the moderating role of political belief in the relationship between these variables.

The statistical population of this research was the employees of public organizations in Isfahan, Iran. We conducted a two-wave lagged survey. The data were collected during the 2024 elections for the 12th convocation of the Islamic Parliament of Iran. This study used structural equation modeling to examine the proposed model.

Employees’ attitude, subjective norm and perceived behavioral control positively impacted employees’ intention to engage in BallotLoafing. In addition, behavioral intention positively impacted actual BallotLoafing behaviors. Finally, the results showed that the political belief did not play a moderating role in the relationship between these variables.

Managing or reducing BallotLoafing involves addressing the key factors that influence such behavior: attitudes, subjective norms and perceived behavioral control.

This research introduces a novel concept: BallotLoafing, which captures employee distraction during elections.

In today’s competitive business landscape, organizations are increasingly recognizing the strategic advantage of implementing sustainable practices to gain a competitive edge. This study aims to investigate the effect of green artificial intelligence (AI) on achieving a green competitive advantage, examining the mediating roles of green organizational learning, green product innovation and green process innovation. Additionally, the research explores the moderating role of perceived green climate in the relationship between green AI and these mediating factors.

This research examined companies in Isfahan, Iran, that have varying levels of artificial intelligence adoption within their business processes. The target population consisted of 148 senior managers from these companies. This study uses structural equation modeling to examine the proposed model.

Green AI positively impacted green organizational learning and green process innovation but not green product innovation. In addition, the results showed that green organizational learning, green product innovation and green process innovation had positive effects on green competitive advantage. Finally, the results showed that the perceived green climate did not play a moderating role in the relationship between green AI and these mediating factors.

Organizations should prioritize green AI initiatives, foster a culture of green learning and invest in green innovation to achieve sustainable growth and outpace competitors in the environmentally conscious marketplace.

This study positions itself at the forefront of research on green AI and green competitive advantage. It offers a unique framework by examining the combined effects of green AI, green learning and both product and process innovation on achieving a sustainable competitive advantage.