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This article presents Benford's Law applied for the first time to the tourism context, focusing on tourism demand. This law states that in sets of random numbers of natural events, the probability of the first digit of these numbers being 1 is approximately 30%, of being 2 is 18%, and so on until reaching 9 with 4.6% probability. In this context, the objective is to verify if Benford's Law applies to the monthly numbers of overnight stays registered in the accommodation establishments of the Island of Sal, in the period between 2000 and 2018, to test the data reliability. This research focus on data provided by the National Statistics Institute of Cape Verde. The Chi-Square test (χ 2 ) was used to assess the discrepancy between the observed and expected relative frequencies. The results show that the observed χ 2 value is higher than the χ 2 critical value (5% significance level), meaning that the number of monthly overnight stays recorded in accommodation establishments on the Island of Sal does not follow Benford's Law. However, certain possible data disturbances must be considered, such as the occurrence of specific events during that time period. Other factors that could influence the results are the size of the data set and a sub notification in the data collection process. These circumstances may be the cause of the non-adaptation of the number of overnight stays to Benford's Law. The implication of this fact on the estimation of tourism demand is crucial for the development and optimization of prediction models.
This article presents Benford's Law applied for the first time to the tourism context, focusing on tourism demand. This law states that in sets of random numbers of natural events, the probability of the first digit of these numbers being 1 is approximately 30%, of being 2 is 18%, and so on until reaching 9 with 4.6% probability. In this context, the objective is to verify if Benford's Law applies to the monthly numbers of overnight stays registered in the accommodation establishments of the Island of Sal, in the period between 2000 and 2018, to test the data reliability. This research focus on data provided by the National Statistics Institute of Cape Verde. The Chi-Square test (χ 2 ) was used to assess the discrepancy between the observed and expected relative frequencies. The results show that the observed χ 2 value is higher than the χ 2 critical value (5% significance level), meaning that the number of monthly overnight stays recorded in accommodation establishments on the Island of Sal does not follow Benford's Law. However, certain possible data disturbances must be considered, such as the occurrence of specific events during that time period. Other factors that could influence the results are the size of the data set and a sub notification in the data collection process. These circumstances may be the cause of the non-adaptation of the number of overnight stays to Benford's Law. The implication of this fact on the estimation of tourism demand is crucial for the development and optimization of prediction models.
Benford Yasası, doğal veri kümelerinde başlangıç rakamlarının belirli bir düzeni takip ettiğini ifade eden bir istatistik prensibidir. Finansal denetim sürecinde Benford Yasası kullanılarak finansal tablo verilerinde oluşabilecek potansiyel düzensizlik, hata ve hileler belirlenebilmektedir. Konaklama işletmeleri; mevsimsel talep değişiklikleri, maliyet yapısı, varlık değerlemesi gibi konularda diğer işletmelerden farklılık göstermektedir. Bu araştırmada, Borsa İstanbul’da faaliyet gösteren konaklama işletmelerinin dönen varlıklar, duran varlıklar, aktif toplam, uzun vadeli yükümlülükler, kısa vadeli yükümlülükler, özkaynaklar, satış gelirleri, satışların maliyeti, brüt kar, faaliyet karı, vergi öncesi kar, amortisman giderleri, işletme-yatırım-finansman faaliyetlerinden sağlanan nakit akışları ile nakit ve nakit benzerlerindeki net artış veya azalış kalemlerinin Benford Yasası’na uygunluğunun tespit edilmesi amaçlanmıştır. Bu amaç doğrultusunda konaklama işletmelerinin söz konusu finansal tablo kalemlerinin Haziran 2016 – Haziran 2023 dönemindeki rakamsal dağılımları Ki-Kare testi ile analiz edilmiştir. Yapılan analiz, dönen varlıklar, duran varlıklar, aktif toplam, uzun vadeli yükümlülükler ve özkaynaklar kalemlerinin Benford Yasası’na uymadığını gösterse de diğer kalemlerin uygunluk gösterdiğini ortaya koymaktadır.
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