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Optimal Advertorial Allocation and Contract Design of a Multichannel Networks Company on Video Sharing
               Platforms



               multiple creators, and it is natural to ask what will happen if this is not allowed. In this
               case, the advertorial allocation decision is said to be binary, i.e., either to the type-H
               creator or the type-L one. Technically, the setting x ∈ [0,1] in the basic model is changed
               to x ∈ {0,1}, where x = 1 means allocating the advertorial to the type-H creator.
                    To understand the impact of this binary restriction, note that the derivations in
               Sections 4.1 and 4.2 need no change. However, the fact obtained in Section 4.3 that
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               the optimal proportion x  may be 1, between 0 and 1, but is never 0 if γ ≠ 0, should be
               modified. As x can only be 0 or 1 now, the MCN company will always find it optimal to
               allocate the advertorial to the type-H creator (i.e., x  = 1 for sure). The comparison between
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               the independent-MCN and no-MCN structures in Proposition 3 will also be changed
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                   N
               to x  = 1 = x . In other words, the low-type creator will have no chance to get allocated
               an advertorial, and the benefit of having an independent MCN to protect and help weak
               creators will disappear. Though splitting an advertorial to multiple creators is currently
               not a popular practice (in fact, no news article or report is found to have reported the wide

               application of this practice), our analysis suggests MCN companies (or the community)
               consider this to help create a more diverse ecosystem for video sharing and digital content
               creation.


                                               7. Conclusions



                    In this study, we address the advertorial allocation and contract design problem of
               an MCN company by taking the creators’ different abilities and effort exertion decisions
               into consideration. Besides, we compare the advertorial allocation decisions and the
               effort exertion decisions under different types of industry structures. Through analytical
               modeling and analysis, we characterize the equilibrium effort levels and revenue sharing
               percentages given any predetermined advertorial allocation decision and then make
               comparisons among different industry structures. It is indeed true that the MCN company

               may incentivize a creator to exert more effort by allocating a larger proportion of an
               advertorial to her/him, and the revenue sharing percentages should be adjusted according
               to the allocation proportion. Regarding the allocation proportion, we identify several
               factors that affect the adoption of the focusing strategy or splitting strategy. In particular,
               the splitting strategy is optimal if and only if the creators’ abilities are similar, the
               advertorial fee is moderate, and the cost of making videos is moderate. Our findings may




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