استفاده از یک روش ترکیبی از طراحی کمی و کیفی در توضیح انگیزه سفر گردشگران فیلم در بازدید از یک مقصد تیراندازی فیلم
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|39984||2015||12 صفحه PDF||سفارش دهید||11260 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Tourism Management, Volume 46, February 2015, Pages 136–147
This study aims to: 1) describe the travel motivations of the types of film tourists proposed by Macionis (2004), specifically, serendipitous tourists, specific film tourists, and general film tourists, in visiting a film-induced tourist destination; and 2) empirically test the assumption that film tourism is incidental and neither the main nor the sole motivation of most tourists traveling to a film destination. A mixed method of quantitative and qualitative (a series of self-complete questionnaire surveys over a period of eleven months and a longitudinal study of interviews and participant observations over a period of four years) was used in the study. Out of 1852 samples, the numbers of specific film tourists (10.5%) and general film tourists (19.5%) are less than serendipitous tourists (70%). Though both business and leisure tourists can be specific film tourists, their number is very small. Furthermore, serendipitous tourists can be distributed into almost equal numbers, namely, “incidental serendipitous tourists,” “disinterested serendipitous tourists,” and “sightseeing serendipitous tourists.” While successful films create destination awareness among all types of film tourists, an individual's favorite film, rather than a successful film, motivated most specific film tourists to take a pilgrimage film trip. This study also highlights the value of the mixed method, of a quantitative and qualitative approach, in explaining film tourism, in regards to unusual behavior of outliers. Whereas the quantitative design increases the generalization of the findings, the qualitative method provides better understanding of contradictory findings without having to eliminate outliers from analysis.