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This study aims to understand how different levels of streamer channels influence luxury brand sales in live streaming commerce. This study also seeks to understand the conditions under which luxury brands may benefit more from different level streamer channels.

Panel data were collected from 17 international luxury brands on the Douyin live streaming platform in an 18 week period from August to December 2020 and analyzed by using a two-way fixed effects model.

The authors compared different mega-, macro- and micro-streamer channels within live streaming commerce and found that the densities of mega- and macro-streamer channels had significant positive impacts on luxury brand sales in live streaming commerce. Moreover, the effects of the density of streamer channel on luxury brand sales were moderated by such variables as product line breadth, product line depth, product type (star/non-star) and product price (high/low). The authors found that product line breadth and depth could reduce the positive impact of the densities of mega- and macro-streamer channels on luxury brand sales. For star products and high-priced products, the relationship between the density of mega-streamer channel and luxury brand sales was more likely to be observed than for non-star products and low-priced products. The relationship between the density of macro-streamer channel and luxury brand sales was more likely to be observed in low-priced products than in high-priced products.

The findings make important contributions to the literature in that the authors expand the influencer-brand fit theory by proposing a new model of effects of the densities of mega-, macro- and micro-streamer channels on sales performance across different luxury products to improve our understanding of the fit among influencers, brands and products. This helps luxury brands make basic decisions of “who sells” and “sells what” when engaging in live streaming commerce.

The purpose of this study is to quantitively characterize pitting or local corrosion of steel bars. Characterization of pitting or local corrosion is important for steel bar corrosion research in concrete, which is still an unsolved problem for the reason that the pitting on corroded steel is distributed irregularly, besides the varied pitting depths. To solve this problem in a certain degree, two parameters were collectively used to find the pitting distribution and pitting depth distribution of corroded steel bar surface.

Corroded reinforcement bars were subjected to two different corrosive conditions to obtain the profile of the surface of corroded steel bar. The arithmetic mean deviation of the profile, Ra, also a roughness parameter, and the fractal dimension, D, were computed using MATLAB software from the data on corroded steel bar profiles scanned by a profile tester. Statistical analysis was performed to determine the parameters distribution of Ra.

Ra and D can assist gravimetric technique in defining the degree of pitting corrosion and make further understanding about the characterization of local or pitting corrosion.

Two parameters were collectively used to find the pitting distribution and pitting depth distribution of corroded steel bar surface, while many studies only study the fractal dimension of pitting corrosion. And, the relationship between these two parameters is studied when using them to describing the non-uniformity of pitting corrosion degree. Using these two parameters can much better describe the non-uniform degree of pitting corrosion.