How Formal and Informal Institutions of Middle Eastern Countries Influence Managerial Discretion: An Empirical Investigation

Managerial discretion is the focal theme bridging the clash between two schools of thoughts; whether executives have greater influence on their firms’ outcomes or other factors restrain their actions (Hambrick & Finkelstein, 1987). It is argued that constraints come from inertial, normative and environmental forces (e.g. DiMaggio & Powell, 1983). Of these restraints is the institutional environment in which a firm is headquartered. Our paper falls within this research stream and provides an extension for Crossland and Hambrick (2007, 2011) work. We investigate the national level of discretion in new cross-cultural contexts, provide deeper understanding of its concept, and shed the light on undiscovered discretion’s antecedents and consequences. We adopt a quantitative approach in which questionnaires represent our data collection instrument. We anticipate that in high discretion countries firms tend to follow what Miles & Snow (1978) labeled ‘Prospector’ strategy as opposed to low discretion countries in which firms incline to implement a ‘Defender’ strategy.

Genetic programming for the minimum time swing up and balance control acrobot problem

This work describes how genetic programming is applied to evolving controllers for the minimum time swing up and inverted balance tasks of the continuous state and action: limited torque acrobot. The best swing-up controller is able to swing the acrobot up to a position very close to the inverted ‘handstand’ position in a very short time, shorter than that of Coulom (2004), who applied the same constraints on the applied torque values, and to take only slightly longer than the approach by Lai et al. (2009) where far larger torque values were allowed. The best balance controller is able to balance the acrobot in the inverted position when starting from the balance position for the length of time used in the fitness function in all runs; furthermore, 47 out of 50 of the runs evolve controllers able to maintain the balance position for an extended period, an improvement on the balance controllers generated by Dracopoulos and Nichols (2012), which this paper is extended from. The most successful balance controller is also able to balance the acrobot when starting from a small offset from the balance position for this extended period.