Data envelopment analysis (DEA) is a method for calculating relative efficiency as a ratio of weighted outputs to weighted inputs of decision making units (DMUs). It is well-known that DEA can be done under the assumption of constant returns to scale (CRS) or variable returns to scale (VRS), however. One major disadvantage of the classical approach is that each DMU optimizes its individual weighting scheme–often called self-appraisal. To overcome this flaw cross-efficiency evaluation has been developed as an alternative way of efficiency evaluation and ranking of DMUs, cf. Sexton (1986) or Doyle and Green (1994). Here all individual weighting schemes–called price systems–are applied to the activities of all DMUs. The derived cross-efficiency matrix forms the basis for seeking a consensual price system–a peer–, and hence this price system can be used for a peer-based activity planning, cf. Rödder and Reucher (2012). In this contribution we show that a scale-efficiency gap can occur when peer-based activity planning under VRS is applied, i.e. there is no feasible point in which self-appraisal efficiency under CRS, VRS and peer-appraisal efficiency coincide. As a consequence, we propose a mixed integer linear problem to find a compromise. Moreover, some numerical examples are provided to complement our theoretical results.