Examining the role of the marketing activity and eWOM in the movie diffusion: the decomposition perspective

Beauty matters: reducing bounce rate by aesthetics of experience product portal page

“…The rise of some offline experience stores also illustrates this point. Previous scholars also mentioned that customers now pay more attention to hedonism when buying products (Zhang et al , 2020; Acuti et al , 2020; Weathers et al , 2007). Nelson (1970) has classified that all electrical products as experience products, but Jourdan (2000) also found that some electrical products can also be divided into search products from the perspective of economic information theory.…”

“…However, due to customers need more sensory experience to evaluate experience products, the internet is difficult to make up for the physical and direct contact experience brought by offline (Weathers et al , 2007). Customers who pursue hedonism also require sensory experience to make purchase decisions regarding experience products (Weathers et al , 2007; Zhang et al , 2020; Acuti et al , 2020). As a result, customers of experience products usually feel greater uncertainty about the fit between their tastes and the features of products being offered, which makes them need to make more efforts for cognitive evaluation, which leads to a higher bounce rate of experience products (Hu et al , 2008; Bae and Lee, 2011; Sun and Tyagi, 2020).…”

“…However, due to customers need more sensory experience to evaluate IMDS 121,8 experience products, the internet is difficult to make up for the physical and direct contact experience brought by offline (Weathers et al, 2007). Customers who pursue hedonism also require sensory experience to make purchase decisions regarding experience products (Weathers et al, 2007;Zhang et al, 2020;Acuti et al, 2020). As a result, customers of experience products usually feel greater uncertainty about the fit between their tastes and the features of products being offered, which makes them need to make more efforts for cognitive evaluation, which leads to a higher bounce rate of experience products (Hu et al, 2008;Bae Experience products Search products Definition Products that customers need more sensory experiences (also known as experience features) for evaluation and the evaluation process accounts for a larger portion of the whole life cycle of products (Nelson, 1970;Sun et al, 2019;Huck et al, 2016) Products that customers need more standardized information (also known as search features) to evaluate (Klein, 1998;Levin et al, 2005;Bae and Lee, 2011) Examples Books, guitars, wines, movies, food Mobile phones, cameras Characteristics Customers find it difficult to obtain all information compared with search products (Klein, 1998;Ochi et al, 2010) Search products are considered that the product information is adequate for evaluation (Weathers et al, 2007) Customers need more expensive or more difficult information search costs compared with search products (Klein, 1998) Search products are those products that can easily get information about the main attributes before buying (Bae and Lee, 2011;Klein, 1998) Information about the important attributes of experience products is difficult to find on the internet (Levin et al, 2005;Bae and Lee, 2011) Search products do not require customers to interact directly with the product to evaluate its most important attributes (Lim et al, 2015) Experience products can provide more attributes on experience and enjoyment for customers to choose, purchase and use (Cooper-Martin, 1991) Experience products cannot be evaluated for main attributes when customers have no direct experience (Hu et al, 2008;…”

The diffusion pattern of new products: evidence from the Korean movie industry

“…If new product diffusion pattern changes over time in a way that shows a growing level of the Bass model coefficients, diffusion of movies would not be an exception. However, even though various studies have applied box office data to the Bass model (Dellarocas et al, 2007 ; Lee et al, 2012 , 2017 , 2019 ; Marshall et al, 2013 ; Sawhney & Eliashberg, 1996 ; Zhang et al, 2020 ), studies focusing on chronological changes of movies diffusion are extremely scarce. Therefore, a meta-analytic approach is required to identify the evidence of the historical change in a single market.…”

“…Because the Bass model estimation is sensitive to the scale of data, we grouped the previous studies into two groups. Chang ( 2008 ) and Zhang et al ( 2020 ) used weekly box office data and the rest of the following studies use daily box office data of the Korean movie market. Chang ( 2008 ) collected 40 movies released from 2003 to 2004 to draw the mean values, 0.294 for p , 0.458 for q , and 1.732 for q / p .…”