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Hedonic value is commonly conceded as a determinant of behavioral intentions toward location-based advertising (LBA). However, the careful consideration of a mechanism behind hedonic motivation and its subsequent impact on continuance intention is inadequate. This study aims to explore the formation of hedonic value and its motivation for prolonged usage toward LBA.

A sample of 486 mobile users was recruited to evaluate the research model using structural equation modeling (SEM).

Results reveal that perceived utility and promotional offers are the strongest indicators of hedonic value. Moreover, social support and contextual convenience play an essential role in heightening hedonic value. Furthermore, the research lenses attempt to clarify the direct, indirect influences of hedonic value, irritation and perceived credibility on continuance intention.

The findings offer practitioners an understanding of how to improve hedonic value and continuance intention and develop effective LBA strategies in emerging markets.

This study narrows the gap of current literature by formulating a hedonic value-based continuance intention model based on uses and gratifications theory (UGT). Additionally, this work illuminates the insights into hedonic value toward LBA by identifying its motivations, including perceived utility, promotional offers, social support and contextual convenience.

Mobile location-based service (m-LBS) seems like a new class of personalized service due to location positioning technologies. This work aims to investigate consumer readiness (RED) toward m-LBS based on integrating pull effect- and push effect-related factors into the technology acceptance model (TAM).

An online survey collected data from 423 participants, and the research framework was analyzed using structural equation modeling (SEM).

The results divulge that consumer RED is determined by TAM antecedents, including usefulness (USE) and ease of use (EOU). EOU motivates USE in m-LBS. Regarding pull effect-related factors, absorptive capacity (ABC) is the strongest positive factor influencing consumer RED to use m-LBS, followed by technology willingness (TWI) and innovativeness (INN). Moreover, INN, trust (TRU) and perceived risk (RIS) significantly influence USE and EOU.

This work endeavors to explicate customer RED toward m-LBS by incorporating some meaningful pull effect-related dimensions (i.e. ABC, TWI and INN) and pushing effect-related dimensions (i.e. RIS) into crucial antecedents rooted in TAM. Thus, the findings assist practitioners in developing marketing strategies by boosting pull effects and controlling push effects on customer engagement in m-LBS.