Contractual Complexity and the Cognitive Load of R&D Alliance Contracts

Abstract

We offer a new perspective on measuring the complexity of interfirm contracts. We define complex contracts as those contracts that contain many elements (clauses) with a relatively large number of interdependencies that also impose a significant cognitive load on contract parties. Previous studies on contractual complexity employ objective measures such as the number of pages, the number of kilobytes, or the number of provisions to measure this complexity. Following some suggestions in the literature, we argue that the degree to which a contract imposes a cognitive load on contract parties should be taken as another important dimension of contractual complexity. We develop a conceptual model of the complexity of contracts using a multidimensional perspective where both objective and subjective dimensions are taken into account. Our empirical analysis combines a sample of nearly 400 R&D alliance contracts in the biopharmaceutical industry with a measurement of the cognitive load of these contracts. Our findings show that quantitative, objective measures of complexity, such as length, and objective as well as subjective elements of the cognitive load of contracts, that is, the information‐processing effort that contractual parties have to make, do indeed measure different aspects of contractual complexity.

Determinants of Contractual Completeness in Franchising

“…Recent studies on contractual complexities show that complexity is a heterogeneous concept (e.g. Poppo and Zenger 2002;Arino and Reuer 2005;Reuer and Arino 2007;Hagedoorn and Hesen 2008;Barthelemy and Quelin 2006). Although these studies differ widely in their approach and definition of complexity, the main characteristics of complexity concept can be defined as follows: Complex contracts have detailed specification of promises, obligations, responsibilities to be performed, procedures for monitoring and dispute resolution and determine in detail outcomes or outputs to be delivered.…”

Trust and Collaboration in the Aftermath of Conflict: The Effects of Contract Structure

“…The findings based on this eight-clause analysis strongly converge with the results reported below (results available on request). In the second set of analyses, we added an interpretive (coding) step to the Step 1 categorization, in which a rater evaluated each provision in every contract of the dataset for seeming ambiguity of intent (Hagedoorn & Hesen, 2009). All clauses that seemed ambiguous as to (coordination vs. control) function were then eliminated.To test the reliability of this elimination procedure, a second rater evaluated 10 randomly selected clauses for each of the 8 types of provisions; the level of agreement was 91.25%.…”

Software tools for the visualization of definition networks in legal contracts

“…Length is often used as a simple measure of complexity: the longer a definition, the more complex it is likely to be [13]. We found the correlation between out-degree and definition length to be low to moderate with a value of 0.325 over 223 data points (individual definitions).…”