Two general goals were raised in this thesis: First, to establish a PLS model for patent value and to investigate causality relationships among variables that determine the patent value; second, to investigate the performance of Partial Least Squares (PLS) Path Modelling with Mode C in the context of patent value models. This thesis is organized in 10 chapters. Chapter 1 presents an introduction to the thesis that includes the objectives, research scope and the document's structure. Chapter 2 gives an overview of the different approaches for patent value from the perspective of technological change. Definitions related to patent documents and patent indicators are provided. Chaper 3 reports on patent sample descriptions. We present criteria to retrieve data, the procedure for calculating patent indicators, and a statistical data description. Chapter 4 provides an introduction to structural equation models (SEMs) including origins, basic background and recent developments. In addition, it provides guidelines for model specification and modelling process for SEMs. Special emphasis is placed on determining the reflective or formative nature of measurement models. Chapter 5 puts forward the main PLS algorithms: NIPALS, PLS Regression and PLS Path Modelling. We present two path modelling implementations: Lohmöller and Wold's procedures. Additionally, insights are given on procedure sensitivity to starting weight values and weighting schemes; algorithm properties, such as consistency and consistency at large; and convergence. We briefly review some PLS Path Modelling extensions and relationships with other procedures. The chapter ends by describing validation techniques. Chapter 6 provides evidence about the accuracy and precision of PLS Path Modelling with Mode C to recover true values in SEMs with few indicators per construct. Monte Carlo simulations and computational experiments are carried out to study the performance of the algorithm. Chapter 7 addresses the formulation and estimation of patent value models. This entails the identification and definition of observable and unobservable variables, the determination of blocks of manifest variables and structural relationships, the specification of a first- and a second-order models of patent value, and the models' estimation by PLS Path Modelling. In Chapter 8, the evolution of patent value over time using longitudinal SEMs is investigated. Two set-ups are explored. The first longitudinal model includes time-dependent manifest variables and the second includes time-dependent unobservable variables. The SEMs are estimated using PLS Path Modelling. In Chapter 9, there is a description of a Two-Step PLS Path Modelling with Mode C (TsPLS) procedure to study nonlinear and interaction effects among formative constructs. Monte Carlo simulations are performed to generate data and to determine the accuracy and precision of this approach to recover true values. This chapter includes an application of the TsPLS algorithm to patent value models. Finally, in Chapter 10, we provide a summary of conclusions and future researchs. The main contribution of this thesis is to set-up a PLS model for patent value, and around this issue, we have also contributed in two main areas: Contributions to the field of Technological Change are comprised of: (1) Evidence on the role of the knowledge stock, technological scope and international scope as determinants of patent value and technological usefulness. A stable pattern of path coefficients was found across samples in different time periods. (2) To conceptualize the patent value as a potential and a recognized value for intangible assets. It was also shown that the potential value of patent is small compared to the value that is given later. (3) Evidence for the importance of considering the longitudinal nature of the indicators in the patent value problem, especially for forward citations, which are the most widely used indicator of patent value. (4) To introduce a multidimensional perspective of the patent valuation problem. This novel approach may offer a robust understanding of the different variables that determine patent value. Contributions to the field of PLS Path Modelling are comprised of: (5) Empirical evidence on the performance of PLS Path Modelling with Mode C. If properly implemented, the procedure can adequately capture some of the complex dynamic relationships involved in models. Our research shows that PLS Path Modelling with Mode C performs according to the theoretical framework established for PLS procedures and PLS-models (Wold, 1982; Krämer, 2006; Hanafi, 2007; Dijkstra, 2010). (6) Empirical evidence for the consistency at large of the PLS Path Modelling with Mode A. (7) Empirical evidence for formative outer models with few manifest variables. (8) Empirical evidence on the performance of a Two-Step PLS Path Modelling with Mode C procedure to estimate nonlinear and interaction effects among formative constructs.