Psychological contracts and independent sales contractors: an examination of the predictors of contractor-level outcomes

Over the past decade, the independent sales contractor (ISC) has emerged as both an important distribution channel and a management challenge. This study makes two contributions to this evolving field. First, it explores the interrelations of the psychological contract with sales performance, voluntary turnover and organisational advocacy of ISCs, which have hitherto been largely unexplored. Second, it examines differences between high- and low-performing sales contractors on these linkages, due to findings in the literature that a small number of sales contractors often achieve a majority of sales. Based on survey data as well as 7 years of contractor-level data related to sales performance and voluntary turnover (n = 189), results indicate that psychological contract fulfilment and perceived dependency are important determinants of subsequent sales performance, voluntary turnover and organisational advocacy, with significant differences reported between high- and low-performing ISCs. A notable finding pertinent for sales managers responsible for managing ISCs is that high-performing sales contractors are motivated by psychological contract fulfilment and a low perception of dependency, while low-performing sales contractors are more likely to act as advocates for the firm due to perceived dependency, but may concurrently engage in organisational advocacy as a means to leave the firm.

Compensation and Rewards for Environmental Services (CRES) and efficient design of contracts in developing countries. Behavioral insights from a natural field experiment

The use of economic incentives for biodiversity (mostly Compensation and Reward for Environmental Services including Payment for ES) has been widely supported in the past decades and became the main innovative policy tools for biodiversity conservation worldwide. These policy tools are often based on the insight that rational actors perfectly weigh the costs and benefits of adopting certain behaviors and well-crafted economic incentives and disincentives will lead to socially desirable development scenarios. This rationalist mode of thought has provided interesting insights and results, but it also misestimates the context by which ‘real individuals’ come to decisions, and the multitude of factors influencing development sequences. In this study, our goal is to examine how these policies can take advantage of some unintended behavioral reactions that might in return impact, either positively or negatively, general policy performances. We test the effect of income's origin (‘Low effort’ based money vs. ‘High effort’ based money) on spending decisions (Necessity vs. Superior goods) and subsequent pro social preferences (Future pro-environmental behavior) within Madagascar rural areas, using a natural field experiment. Our results show that money obtained under low effort leads to different consumption patterns than money obtained under high efforts: superior goods are more salient in the case of low effort money. In parallel, money obtained under low effort leads to subsequent higher pro social behavior. Compensation and rewards policies for ecosystem services may mobilize knowledge on behavioral biases to improve their design and foster positive spillovers on their development goals.

Endogenous managerial compensation contracts in experimental quantity-setting duopolies

Given the ongoing debate on managerial compensation schemes, our paper offers empirical insights on the strategic choice of firms' owners over the terms of a managerial compensation contract, as a commitment device aiming at gaining competitive advantage in the product market. In a quantity setting duopoly we experimentally test whether firms' owners compensate their managers through contracts combining own profits either with revenues or with relative performance, and the resulting managerial behaviour in the product market. Prominent among our results is that firms' owners choose relative performance over profit revenue contracts more frequently. Further, firms' owners successfully induce a more aggressive behaviour by their managers in the market, by setting incentives which deviate from strict profit maximization.

Risk taking of executives under different incentive contracts: experimental evidence

Classic financial agency theory recommends compensation through stock options rather than shares to counteract excessive risk aversion in agents. In a setting where any kind of risk taking is suboptimal for shareholders, we show that excessive risk taking may occur for one of two reasons: risk preferences or incentives. Even when compensated through restricted company stock, experimental CEOs take large amounts of excessive risk. This contradicts classical financial theory, but can be explained through risk preferences that are not uniform over the probability and outcome spaces, and in particular, risk seeking for small probability gains and large probability losses. Compensation through options further increases risk taking as expected. We show that this effect is driven mainly by the personal asset position of the experimental CEO, thus having deleterious effects on company performance.

Construction contracts: law and management. 5th edition

The fifth edition of this best-selling textbook has been thoroughly revised to provide the most up-to-date and comprehensive coverage of the legislation, administration and management of construction contracts. It now includes comparison of working with JCT, NEC3 and FIDIC contracts, throughout. In line with new thinking in construction management research, this authoritative guide is essential reading for every construction undergraduate and is an extremely useful source of reference for practitioners.

Zero attracting recursive least squares algorithms

The l1-norm sparsity constraint is a widely used technique for constructing sparse models. In this contribution, two zero-attracting recursive least squares algorithms, referred to as ZA-RLS-I and ZA-RLS-II, are derived by employing the l1-norm of parameter vector constraint to facilitate the model sparsity. In order to achieve a closed-form solution, the l1-norm of the parameter vector is approximated by an adaptively weighted l2-norm, in which the weighting factors are set as the inversion of the associated l1-norm of parameter estimates that are readily available in the adaptive learning environment. ZA-RLS-II is computationally more efficient than ZA-RLS-I by exploiting the known results from linear algebra as well as the sparsity of the system. The proposed algorithms are proven to converge, and adaptive sparse channel estimation is used to demonstrate the effectiveness of the proposed approach.

A constrained recursive least squares algorithm for adaptive combination of multiple models

In this paper, we develop a novel constrained recursive least squares algorithm for adaptively combining a set of given multiple models. With data available in an online fashion, the linear combination coefficients of submodels are adapted via the proposed algorithm.We propose to minimize the mean square error with a forgetting factor, and apply the sum to one constraint to the combination parameters. Moreover an l1-norm constraint to the combination parameters is also applied with the aim to achieve sparsity of multiple models so that only a subset of models may be selected into the final model. Then a weighted l2-norm is applied as an approximation to the l1-norm term. As such at each time step, a closed solution of the model combination parameters is available. The contribution of this paper is to derive the proposed constrained recursive least squares algorithm that is computational efficient by exploiting matrix theory. The effectiveness of the approach has been demonstrated using both simulated and real time series examples.