Purpose The authors investigated the effects of the characteristics of reviews, reviewers and corporate factors on review helpfulness and assessed the role of culture in moderating these relationships. Design/methodol...
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Purpose The authors investigated the effects of the characteristics of reviews, reviewers and corporate factors on review helpfulness and assessed the role of culture in moderating these relationships. Design/methodology/approach A research model was established based on the elaboration likelihood and information adoption models. To empirically analyze this research model, 10,611 TripAdvisor reviews from 9 countries were collected. In addition, a zero-inflated negative binomial model and multilevel analysis were employed in consideration of the data characteristics. Findings The results revealed that review depth had a positive effect on review helpfulness, and review ratings and reviewer expertise had a negative effect. As a corporate characteristic, hotel size had a negative effect on review helpfulness. In addition, the effects of review rating, reviewer expertise and hotel rating exhibited significant differences based on the moderating effects of uncertainty avoidance and power distance level. Originality/value The results of this study expand the review helpfulness literature by explaining the inconsistent findings of previous studies via cultural theory. In addition, past research in this field has mainly focused on analyzing only review and reviewer characteristics, while this study demonstrated that company size negatively affects review helpfulness based on the signaling theory. Finally, this study contributes to cultural comparison literature by discovering that the processing of review information by consumers differs according to their cultural background.
We propose a simple model of columnar growth through diffusion limited aggregation (DLA). Consider a graph G(N) x N, where the basis has N vertices G(N) : = {1, ..., N}, and two vertices (x, h) and (x', h') ar...
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We propose a simple model of columnar growth through diffusion limited aggregation (DLA). Consider a graph G(N) x N, where the basis has N vertices G(N) : = {1, ..., N}, and two vertices (x, h) and (x', h') are adjacent if vertical bar h - h'vertical bar <= 1. Consider there a simple random walk coming from infinity which deposits on a growing cluster as follows: the cluster is a collection of columns, and the height of the column first hit by the walk immediately grows by one unit. Thus, columns do not grow laterally. We prove that there is a critical time scale N = log (N) for the maximal height of the piles, i.e., there exist constants alpha < beta such that the maximal pile height at time alpha/N = log (N) is of order log (N), while at time beta N/log(N) is larger than N-chi for some positive chi. This suggests that a monopolistic regime starts at such a time and only the highest pile goes on growing. If we rather consider a walk whose height-component goes down deterministically, the resulting ballistic deposition has maximal height of order log (N) at time N. These two deposition models, diffusive and ballistic, are also compared with uniform random allocation and Polya's urn.
We study an inverse problem for variable coefficient fractional parabolic operators of the form (∂t − div(A(x)∇x))s + q(x, t) for s ∈ (0, 1) and show the unique recovery of q from exterior measured data. Similar to t...
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