Cross-Level Interactions Only - Random Slopes without Random Intercepts?

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I was wondering if there are discussions, examples of studies, or book chapters which model randomly varying slopes while disregarding intercepts. I am facing a situation where the dv (overall job performance) needs to be standardized within organization due to variations in scaling (e.g,. 3-, 5-, and 7-point rating scales). As a result, all lines pass through the same point on the y-axis thus eliminating between-unit variance in the outcome (i.e., ICC of zero).

I have variables originating at three levels (individual, task, organization) and theoretical predictions on when the relationship between
particular individual differences and overall job performance should vary in strength. In other words, I am only interested in cross-level
interactions. At this point, I am wondering if it would make more sense to use ordinary least squares regression or, perhaps, sift through the date for comparable scaling to model randomly varying intercepts. Thanks!

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关键词：interactions interaction intercepts Intercept interact individual interested comparable particular situation

I encountered a similar situation in which the level-1 intercept I was studying did not significantly vary across level 2 units but I detected a cross-level interaction and had a theoretical reason to do so. Snidjers and Bosker discuss exceptions to the precondition of significant random intercept variance on pg. 106 of their book "Multilevel Analysis" (2nd ed.).

Given your a priori hypothesis regarding the presence of an interaction, there is no need to observe a large ICC to proceed with your cross-level interaction test. For more detailed information on this issue, see the following article available at http://mypage.iu.edu/~haguinis/pubs.html

Aguinis, H., Gottfredson, R. K., & Culpepper, S. A. 2013. Best-practice recommendations for estimating cross-level interaction effects using multilevel modeling. Journal of Management, 39: 1490-1528.