Management Practices and Employee Performance - Causal Evidence from Field- and Laboratory Experiments

The research presented in this thesis contributes to the incentive literature in accounting, economics, and management. Chapter two reports the results of two field experiments in a retail chain and show that the effectiveness of performance pay crucially hinges on prior job experience. Introducing sales-based performance pay for district- and later for store-managers, we find negligible average treatment effects. Based on surveys and interviews, we develop a formal model demonstrating that the effect of performance pay decreases with experience and may even vanish in the limit. We provide empirical evidence in line with this hypothesis, for instance, finding positive treatment effects (only) in stores with low job experience. Chapter three addresses the core role of managerial accounting - the processing and provision of information to facilitate managers’ decisions and influence their behavior through incentives. We study the impact of these two roles of information on profits implementing a field experiment in a large retail chain. In a 2x2 factorial design we vary: (i) whether store managers obtain access to decision-facilitating accounting information to raise profits and (ii) whether they receive performance pay based on an objective profit metric to influence their decisions. We find that both practices indeed increase profits. In contrast to our hypothesis, we find no evidence of a complementarity. Net of bonus costs, the mere provision of decision-facilitating information even tends to outperform the combined intervention. Chapter four studies how a gift of more leisure time affects employees’ performance in a real-effort laboratory experiment. Results show that a monetary gift of a 75% wage increase does not alter employee’s performance, compared to a baseline of no gift. A comparable gift of more leisure time, however, significantly increases employee performance by 25%. The mechanism for this is a significant reduction in on-the-job leisure (Internet) consumption by 45%. An online survey experiment among human resource managers provides some external validity

Mobility in a Globalised World 2015

The term mobility has different meanings in the following science disciplines. In economics, mobility is the ability of an individual or a group to improve their economic status in relation to income and wealth within their lifetime or between generations. In information systems and computer science, mobility is used for the concept of mobile computing, in which a computer is transported by a person during normal use. Logistics creates by the design of logistics networks the infrastructure for the mobility of people and goods. Electric mobility is one of today’s solutions from engineering perspective to reduce the need of energy resources and environmental impact. Moreover, for urban planning, mobility is the crunch question about how to optimise the different needs for mobility and how to link different transportation systems. In this publication we collected the ideas of practitioners, researchers, and government officials regarding the different modes of mobility in a globalised world, focusing on both domestic and international issues

Time for helping

This study investigates whether individuals engage in prosocial behavior when it requires an investment of their time, but not money. In a laboratory experiment with rigorous anonymity arrangements, senders receive their payoff at the beginning. They may then engage in a tedious task to increase the earnings of exogenously disadvantaged recipients who otherwise receive no earnings. We find that senders are willing to sacrifice time to benefit recipients. Whether or not the recipient is present in the laboratory during the working time does not alter this decision. However, in a treatment variation some senders also display antisocial behavior

Talking About Performance or Paying for It? A Field Experiment on Performance Reviews and Incentives

We investigate the causal effect of performance pay and conversations about performance in 224 stores of a retail chain implementing a field experiment with a 2x2 factorial design. In the performance pay treatments, managers receive a bonus, which is a simple linear function of the profits achieved above a threshold value. In the performance review treatments, managers have to report their activities undertaken to increase profits in regular meetings. We find that whereas performance pay did not yield significant profit increases, performance review conversations increased profits by about 7%. However, when additionally receiving performance pay, the positive effect of performance reviews vanished. We provide evidence from surveys and meeting protocols that performance pay changes the nature of conversations, leading to a stronger self-reliance of store managers, which undermines the value of the performance reviews

Performance Pay and Prior Learning-Evidence from a Retail Chain

We report the results of two field experiments in a retail chain and show that the effectiveness of performance pay crucially hinges on prior job experience. Introducing sales-based performance pay first for district managers and later for store managers, we find negligible average treatment effects. From surveys and interviews, we develop a formal model demonstrating that the effect of performance pay decreases with experience and may even vanish in the limit. We provide empirical evidence in line with this hypothesis-for instance, finding positive treatment effects (only) in stores with low job experience

Characteristics, potentials, and limitations of open-source Simulink projects for empirical research

Simulink is an example of a successful application of the paradigm of model-based development into industrial practice. Numerous companies create and maintain Simulink projects for modeling software-intensive embedded systems, aiming at early validation and automated code generation. However, Simulink projects are not as easily available as code-based ones, which profit from large publicly accessible open-source repositories, thus curbing empirical research. In this paper, we investigate a set of 1734 freely available Simulink models from 194 projects and analyze their suitability for empirical research. We analyze the projects considering (1) their development context, (2) their complexity in terms of size and organization within projects, and (3) their evolution over time. Our results show that there are both limitations and potentials for empirical research. On the one hand, some application domains dominate the development context, and there is a large number of models that can be considered toy examples of limited practical relevance. These often stem from an academic context, consist of only a few Simulink blocks, and are no longer (or have never been) under active development or maintenance. On the other hand, we found that a subset of the analyzed models is of considerable size and complexity. There are models comprising several thousands of blocks, some of them highly modularized by hierarchically organized Simulink subsystems. Likewise, some of the models expose an active maintenance span of several years, which indicates that they are used as primary development artifacts throughout a project's lifecycle. According to a discussion of our results with a domain expert, many models can be considered mature enough for quality analysis purposes, and they expose characteristics that can be considered representative for industry-scale models. Thus, we are confident that a subset of the models is suitable for empirical research. More generally, using a publicly available model corpus or a dedicated subset enables researchers to replicate findings, publish subsequent studies, and use them for validation purposes. We publish our dataset for the sake of replicating our results and fostering future empirical research

Welcome to the First International Workshop on Requirements Engineering for Explainable Systems (RE4ES)

Welcome to the First International Workshop on Requirements Engineering for Explainable Systems (RE4ES), where we aim to advance requirements engineering (RE) for explainable systems, foster interdisciplinary exchange, and build a community. On the one hand, we believe that the methods and techniques of the RE community can add much value to explainability research. On the other hand, we have to ensure that we develop techniques fitted to the needs of other communities.This first workshop explores synergies between the RE community and other communities already researching explainability.To this end, we have based our agenda on a mix of paper presentations from authors of different domains, one keynote from industry and one from research, as well as interactive activities to stimulate lively discussions