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Researchers have addressed the implications of power imbalance for nonprofits engaging in collaborations with businesses. Yet as nonprofit–business collaboration intensifies, nonprofit managers' perceptions of power asymmetry in these relationships remain scantly studied. We argue that investigating these perceptions can sharpen the understanding of determinants and processes of power relations from a nonprofit perspective. To do so, we studied nonprofit–business collaboration in a network of international cooperation nongovernmental organizations (NGOs). Based on our findings, we designed a nonprofit-centric "resource profile" framework of power relations in cross-sector collaborations. This framework provides an empirically grounded tool to inform nonprofit managers' decision making as they engage in collaborations with businesses. Based on this framework, we elaborate a set of theoretical propositions to integrate existing knowledge and guide further nonprofit-centric research on power dynamics in cross-sector collaboration.

The classic wood supply optimisation model maximises even-flow harvest levels, and implicitly assumes infinite fibre demand. In many jurisdictions, this modelling assumption is a poor fit for actual fibre consumption, which is often a species-unbalanced subset of total fibre allocation. Failure to anticipate this bias in volume and species mix of industrial wood fibre consumption has been linked to increased risk of wood supply failure. In particular, we examine the distributed wood supply planning problem, which is a variant of the general wood supply planning problem where the roles of forest owner and fibre consumer are played by independent agents (e.g. wood supply planning on public forest land in Canada, where government stewards control wood supply and forest products industry firms consume the fibre). We use agency theory to describe the source of antagonism between public forest land owners (the principal) and industrial fibre consumers (the agent). We show that the distributed wood supply planning problem can be modelled more accurately using a bilevel formulation, and present an extension of the classic wood supply optimisation model which explicitly anticipates industrial fibre consumption behaviour. The general case of the bilevel wood supply optimisation problem is NP-hard, non-linear, and non-convex-it is difficult to solve to global optimality. By imposing certain restrictions on agent network topology, we show that the general case can be decomposed into convex sub-problems. We present a solution methodology that can solve this special case to global optimality, and compare output and solution times of classic and bilevel model formulations using a computational experiment on a realistic dataset. Experimental results show that solution time for the bilevel problem is comparable to solution time for the classic single-level problem, and that the bilevel formulation can mitigate risk of wood supply failure.