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The purpose of this study is to use a developed and pre-tested scenario-based measurement instrument for policy compliance and determine whether policy compliance measurements in the current policy compliance research are biased as has been postulated during a pre-study. The expected biases are because of social desirability and because of biases based on identity theory.

A survey was conducted (n = 54) that used policy compliance scales from literature and the developed self-reporting policy compliance (SRPC) scale, along with the Marlow–Crowne social desirability (MC-SDB) scale. Differences between the policy compliance scales were assessed. Moreover, a transformation of the SRPC measurements into the literature-based scales was examined using pair-wise t-testing. Finally, correlations between the MC-SDB and the policy compliance scales were examined.

There are no significant influences on the desire for social approval of the respondents as was exhibited by the MC-SDB values and policy compliance on either scale. However, the SRPC scale measurements show deviations from the literature-based policy compliance scales. Individuals that exhibit secure behaviour, which is not rooted in a policy but rather in anything but the policy, are also captured as being policy compliant in the current scales. This shows that a response bias exists in current scales. Respondents, who perceive to exhibit secure behaviours, may think that they are in compliance with the policy, even when they are not.

These findings mean that several contributions in the field of policy compliance must be questioned and that a revisit of several factors influencing policy compliance may be required.

To the best of the authors’ knowledge, response biases in policy compliance research have not been considered to date.

Researchers in economics and other disciplines are often interested in the causal effect of a binary treatment on outcomes. Econometric methods used to estimate such effects are divided into one of two strands depending on whether they require unconfoundedness (i.e., independence of potential outcomes and treatment assignment conditional on a set of observable covariates). When this assumption holds, researchers now have a wide array of estimation techniques from which to choose. However, very little is known about their performance – both in absolute and relative terms – when measurement error is present. In this study, the performance of several estimators that require unconfoundedness, as well as some that do not, are evaluated in a Monte Carlo study. In all cases, the data-generating process is such that unconfoundedness holds with the ‘real’ data. However, measurement error is then introduced. Specifically, three types of measurement error are considered: (i) errors in treatment assignment, (ii) errors in the outcome, and (iii) errors in the vector of covariates. Recommendations for researchers are provided.

The purpose of this paper is to estimate aircraft roll angle and rate gyro biases using aircraft kinematics with GPS and low‐quality rate gyros.

The proposed method is motivated by observing the fact that, in typical flight applications with transport, reconnaissance, or surveillance missions, the aircraft flies along relaxed flight paths, and the associated aircraft motion can be considered as the sum of the coordinated flight, low‐frequency motion and non‐coordinated, high‐frequency motion. The proposed scheme utilizes the coordinated flight kinematics to form the relatively simple, low‐order Kalman filter that estimates the aircraft roll attitude and rate gyro biases.

The associated frequency analysis reveals that, for the estimation in the relatively low‐frequency region, the method relies primarily on GPS with the help of coordinated flight kinematics in removing the bias effect from the low‐quality rate gyros. Also, for the estimation in the high‐frequency region the method relies mainly on the numerical integration of the rate gyro for the roll attitude, which enables a high‐bandwidth estimation.

The proposed method is not suitable for flight manoeuvres where a non‐coordinated flight, such as steady heading sideslip, is sustained for a long period of time.

The proposed method has been implemented in a small UAV. The associated flight tests and simulations indicate that the new method has a potential to be used as a backup or a replacement for other complex conventional methods for many flight applications.

This paper has been the first to promote the estimation method that combines aircraft kinematics with GPS and low‐quality rate gyros.

The purpose of this paper is to present a refined framework providing clarity in terms of the components of profitability and productivity change from the perspective of the firm level.

The literature is analysed with a scoping study and a systematic literature review. Productivity measurement approaches are compared using data at the product level.

The definition of total factor productivity (TFP) in the literature negatively affects the accuracy of profitability and productivity measurement. In the usual case of a dynamic output mix, TFP change encompasses biasing output mix effects relating to profitability, but not to productivity change. Therefore, this paper defines changes of a ratio of output quantities to input quantities not as TFP change, but as quantitative profitability (QP) change. A framework is proposed decomposing profitability change into price recovery and QP change, whereas the latter comprises of valid productivity change (encompassing technological, technical efficiency and productivity-related scale effects) and output mix change (encompassing proportion, quality, output switching and profitability-related scale effects).

Future research should include literature from the industrial organisation field of economics. The presented framework should be transferred to the standard production function framework used in economics.

The paper can help preventing faulty decision making or distrust due to the use of biased profitability or productivity indicators. TFP-based productivity indicators are unsuitable for most firms. To measure productivity meaningfully, firms should use adequate approaches (e.g. standard input- or adjusted total factor productivity-based ones).

The paper contributes to a more accurate performance measurement approach, as researchers and practitioners better understand the components of profitability and productivity change.

Many consumer-focused corporate social responsibility (CSR) studies suggest a positive link between the responsibility demonstrated by a company and consumers’ intention to favor the company in their purchases. Yet an analogous causal effect between corporate social and financial performances is not evident. This chapter conceptualizes how social desirability and cynicism contribute to the discrepancy between consumers’ attitudes and their actual purchase behavior, and analyzes why consumer choices indicated in surveys do not consistently convert into actions.

We develop a conceptual framework based on hybrid choice modeling to estimate the impact of two new variables, Corporate Social Desirability and Corporate Social Cynicism, on CSR research. The model presented synthesizes research findings from the fields of CSR and psychology with a discrete choice methodology that allows inclusion of psychological aspects as latent variables.

The goal of the framework is to bridge the gap between choices stated by consumers in CSR surveys and their actual choices by quantifying and extracting the effects of biases that otherwise threaten the validity of such survey results. As the next step, the practical value of the model must be evaluated through empirical research combining a CSR choice study with social desirability and cynicism measurement.

The framework proposes a novel way of controlling CSR surveys for potential biases created by social desirability and cynicism and enables quantification of this impact, with potential application to other fields where psychological aspects may distort research results. Future empirical evidence based on the framework may also offer new insights into the mechanisms by which the two biases distort findings.

The purpose of this paper is to investigate if and how firms approach debiasing and what determines its success. In particular, this study examines if debiasing is effective in reducing cognitive decision biases. This paper also investigates organizational characteristics that determine the effectiveness of debiasing.

This study uses survey data from German firms to answer the research questions. Target respondents are individuals in a senior management accounting function.

In line with the hypotheses, this paper finds that debiasing can reduce cognitive biases. Moreover, this study finds that psychological safety not only directly influences the occurrence of cognitive biases but is also an important factor that determines the effectiveness of debiasing.

This paper provides evidence that debiasing can serve as a powerful management accounting tool and discusses debiasing in the context of recent management accounting literature. This study also adds to the stream of research that investigates the role of psychological safety in organizations by highlighting its importance for successful debiasing.

This paper informs firms that use or intend to use debiasing about crucial determinants to consider when debating its implementation, i.e. psychological safety. This study also identifies risk management as a potential interface for the implementation of systematic debiasing.

While previous research primarily addresses specific cognitive biases and debiasing mechanisms using lab experiments, this is – to the best of the knowledge – the first study investigating cognitive biases and debiasing on a broad conceptual level using survey data.

This paper verifies the adequacy of perceived quality measurement instruments by comparing the SERVPERF and EP methods. After a discussion of the differences between the two methods, a quality perception measurement instrument for the company is developed and applied to a sample of ceramic company clients. The methods are compared by analyzing the multitrait‐multimethod matrix using the structural equation model methodology. Results indicate that SERVPERF has greater reliability, greater convergent and discriminant validity, explains variance more completely, and consequently introduces less bias.

Immersive virtual reality (IVR) has been frequently proposed as a promising tool for learning. However, researchers have commonly implemented a plethora of design elements in these IVR systems, which makes the specific aspects of the system that are necessary to achieve beneficial outcomes unclear. Against this background, this study aims to combine the literature on presence with learning theories to propose that the ability of IVR to present 3D objects to users improves the presence of these objects in the virtual environment compared with 2D objects, leading to increased learning performance.

To test this study’s hypotheses, the authors conducted a 2 (training condition: approach vs avoid) x 2 (object presence: high vs low) between-subjects laboratory experiment that used IVR with 83 female participants.

The results support this study’s hypotheses and show that training with high object presence leads to greater reactions to cues (chocolate cravings) and improved health behaviour (chocolate consumption).

This study shows that increased object presence leads to unique experiences for users, which help reinforce training effects. Moreover, this work sheds further light on how immersive computer technologies can affect user attitudes and behaviour. Specifically, this work contributes to IVR research by showing that learning effects can be enhanced through an increased degree of object presence.

Memory impairments in the elderly have been widely studied in the past. This study focuses on the effects of these memory impairments on the ability of mature consumers to respond to brand attitude scales. An experimental study investigates the impact of age and type of measurement scale on responses to brand attitude scales. Groups of seniors within the elderly market (55‐65, 66‐75, and over 75) are investigated as opposed to contrasting two extreme points on the continuum, namely the elderly versus the young. Three commonly used attitude scales were manipulated to determine how age interacts with the form of scale to generate response bias. Three types of response bias; extremity response, acquiescence, and item non‐response were investigated. Results indicate a significant interaction between age and type of scale. Implications of these results for those involved in marketing to seniors are highlighted.