Joint pricing and openness decisions in software markets with reinforcing loops

Abstract

In software markets, pricing and openness interact to determine profitability through the direct effect of openness on feasible prices and costs, and their impact on different reinforcing feedback loops such as network effects. We develop a simulation model of the inner workings of a software firm, product life cycle and market aggregation, and analyze their interactions in a competitive market. The reinforcing loops increase the value of early market lead and put pressure on the competing firms to seek such advantage. The competitive equilibrium under strong reinforcing loops calls for highly open software products with early discounts that significantly compromise the profitability of the players. Proprietary platforms and higher prices are favored when those mechanisms are weak. We discuss the implications of this analysis for the dynamics of different competitive markets as well as the contributions to the system dynamics literature in analyzing Nash equilibrium of differential games. Copyright © 2012 System Dynamics Society.

Dynamic supply chains with endogenous dispositions

“…Within the system dynamics literature, the use of discrete choice modeling frameworks is similarly sparse, though much of the underlying mathematical theory overlaps with parameter estimation tools such as the method of simulated moments (Train, 2009; Jalali et al ., 2015; Hosseinichimeh et al ., 2016). Explicit use of this choice framework in system dynamics modeling has followed more closely its marketing applications, determining expected market share of different options given perceived utility in specific consumer contexts (Rahmandad and Sibdari, 2012; Keith et al ., 2017). In a single industrial context found by this author, seemingly more superficially similar to the supply chain context discussed in this article, use of the MNL choice model is still ultimately framed in terms of relative market share of fuel options for running electricity plants (Moxnes, 1990).…”

Reporting guidelines for simulation‐based research in social sciences

“…feature‐space definition and functional approximations used for approximate dynamic programming (Bertsekas and Tsitsiklis, ; Bertsekas, ) the mapping of search parameters into model variables shall be reported. The search algorithm used shall be specified by reference to the original article introducing the algorithm and fully explaining any modifications or new search methods. If iterative methods are used, e.g. for finding game‐theoretic equilibria (Kim and Kim, ; Sterman et al ., ; Rahmandad and Sibdari, ), the number of iterations needed for convergence shall be reported. The actual search that has led to the reported optimization results based on the algorithm used, e.g. the number of restarts of the search in the parameter space, the total number of scenarios simulated, and the number of iterations per scenario (for stochastic models).…”

“…• If iterative methods are used, e.g. for finding game-theoretic equilibria (Kim and Kim, 1997;Sterman et al, 2007;Rahmandad and Sibdari, 2012), the number of iterations needed for convergence shall be reported. • The actual search that has led to the reported optimization results based on the algorithm used, e.g.…”

A System Dynamics Model for a Sustainable Fish Population

“…Simulation as a concept consists of a few basic steps including building a simulation model; running the simulation model; analyzing the performance measures; and evaluating alternative scenarios (Laguna & Markland, 2005). With the advent of software and computer engineering, nowadays, dynamic simulation modeling tools (Richardson, 2013;Martinez-Moyano & Richardson, 2013) are being used to measure sustainability of various ecological (Thakker et al, 2013), economic (Rahmandad & Sibdari, 2012;Pierson & Sterman, 2013;Wyburn & Roach, 2013), social (Abdel-Hamid, 1989Onggo, 2012;Black, 2013;Eberlein & Thompson, 2013;Morrison et al, 2013), technological (Rahman & Akhter, 2010;Jones et al, 2002;Morrison, 2012;Ng et al, 2012;Jammoussi et al, 2013) and natural phenomena (Barker, 2008).…”