The influence of theocratic rule and political turmoil on tourists’ length of stay

Abstract

The average tourist’s length of stay (LOS) is in a global decline. This downward trend underscores the need to study the factors that affect this variable in order to enable more effective management and marketing. This paper moves beyond the literature by investigating the determinants of international tourists’ LOS in a Muslim destination amid political crisis. LOS was evaluated using a survival analysis approach with data from 726 international tourists in Tabriz, Iran to ascertain the significant factors influencing trip length. The results reveal that the determinant factors are as follows: socio-demographic profiles, trip characteristics, and destination attributes. In addition, political turmoil and religious regulations are pivotal factors in LOS. The empirical findings provide valuable theoretical contributions to researchers and actionable guidance to tourism managers and marketers.

Impact of the length of stay at hotels on online reviews

“…Previous studies have attempted to ascertain the determinants of the LoS of tourists to provide useful insight into how to increase the LoS effectively. Practitioners need to understand the determinants of LoS to develop effective target marketing strategies (Hateftabar and Chapuis, 2020; Hateftabar, 2021). For example, Wang et al (2018) revealed the determinants of LoS in the context of a gaming destination, Macao.…”

“…Numerous studies have examined how the LoS directly contributes to profitability (Weatherford, 1995). In addition, previous studies have attempted to reveal the determinants of LoS to provide useful insights for practitioners to formulate effective target marketing strategies (Hateftabar and Chapuis, 2020; Hateftabar, 2021). As a result, various socioeconomic factors were found to be closely related to the LoS.…”

Analysis of Tourists’ Length of Stay in Pokhara, Nepal

“…Furthermore, LOS studies differ in terms of geographical location, influencing variables, and methodologies (Hateftabar & Chapuis, 2020). Previous studies have covered several geographical locations, as discussed in the introduction section; they include Spain, the southern coast of Portugal, the Atlantic coast of the United States, Norway, and the mountains of Italy.…”

“…Previous studies have covered several geographical locations, as discussed in the introduction section; they include Spain, the southern coast of Portugal, the Atlantic coast of the United States, Norway, and the mountains of Italy. In addition, various methodological approaches, such as survival analysis (Aguilar & Díaz, 2019;Hateftabar & Chapuis, 2020), count regression (Nicolau et al, 2018), OLS regression (Thrane, 2015), and logit regression (Alegre & Pou, 2006) have been adopted to model LOS.…”

“…However, Thrane (2012Thrane ( , 2015 criticized the survival and count regression models and proposed ordinary least squares (OLS) regression, which produces similar results to the ZTNB regression and survival models. Critics of the OLS regression argue that LOS is a strictly positive variable; a negative fitted LOS value does not have a valid meaning, and the OLS regression can produce negative fitted LOS values for shorter durations (Hateftabar & Chapuis, 2020). However, log transformation converts LOS into strictly positive values by eliminating the risk of negative fitted values (Thrane, 2015).…”