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The idea that a significant portion of what consumers do, feel, and think is driven by automatic (or “implicit”) cognitive processes has sparked a wave of interest in the development of assessment tools that (attempt to) capture cognitive processes under automaticity conditions (also known as “implicit measures”). However, as more and more implicit measures are developed, it is becoming increasingly difficult for consumer scientists and marketing professionals to select the most appropriate tool for a specific research question. We therefore present a systematic overview of the criteria that can be used to evaluate and compare different implicit measures, including their structural characteristics, the extent to which (and the way in which) they qualify as “implicit,” as well as more practical considerations such as ease of implementation and the user experience of the respondents. As an example, we apply these criteria to four implicit measures that are (or have the potential to become) popular in marketing research (i.e., the implicit association test, the evaluative priming task, the affect misattribution procedure, and the propositional evaluation paradigm).

Snacking typically occurs as an automatic, consciously uncontrolled process which can lead to unintended health consequences. Grounded cognition informs about the multifaceted drivers of such automatic consumption processes. By integrating situation-, stimulus-, and person-specific factors, this study provides a holistic account of snacking.

A combined psychophysiological and behavioral experiment is conducted wherein participants can casually snack chocolate while participating in a survey setting. Implicit cognitions are assessed with the Implicit Association Test. The percentage of consumed chocolate serves as dependent variable in a Tobit regression with predictors at situation, stimulus and person level.

Chocolate snacking is positively influenced by personal craving tendencies, implicit food associations and situational contingency. We condense the results into an overarching framework in line with grounded cognition literature.

The multidimensional framework can guide consumer protection efforts to reduce excessive snacking habits based on situation, stimulus and person.

This study integrates theory from social cognition, consumer research, and behavioral food research and, thereby, extends the existing body of knowledge on grounded cognitions underlying snacking consumption.

There are common problems in the identification of uncertain nonlinear systems, nonparametric approximation, state estimation, and automatic control. Dynamic neural network (DNN) approximation can simplify the development of all the aforementioned problems in either continuous or discrete systems. A DNN is represented by a system of differential or recurrent equations defined in the space of vector activation functions with weights and offsets that are functionally associated with the input data.

This study describes the version of the toolbox, that can be used to identify the dynamics of the black box and restore the laws underlying the system using known inputs and outputs. Depending on the completeness of the information, the toolbox allows users to change the DNN structure to suit specific tasks.

The toolbox consists of three main components: user layer, network manager, and network instance. The user layer provides high-level control and monitoring of system performance. The network manager serves as an intermediary between the user layer and the network instance, and allows the user layer to start and stop learning, providing an interface to indirectly access the internal data of the DNN.

Control capability is limited to adjusting a small number of numerical parameters and selecting functional parameters from a predefined list.

The key feature of the toolbox is the possibility of developing an algorithmic semi-automatic selection of activation function parameters based on optimization problem solutions.

Purpose – Due to an absence of dialogue between sociology and the neurosciences, the scientific study of morality largely ignores cultural and structural influences. This chapter offers a synthetic approach integrating these separate disciplines to aid a more complete understanding of morality.

Design/methodology/approach – This chapter reviews morality's bonding (a sense of groupness and belonging) and bounding (reproducing and reinforcing group boundaries) qualities across disciplines, and proposes three provisional principles to systematize an interdisciplinary model of morality. We then offer a preliminary illustration of how this model might be operationalized with functional MRI data.

Findings – Our proposed principles (as exemplified by our illustrative example) suggest that the sociology-neurology gap in understanding the domain of morality might shrink through an engagement with the underlying neural mechanisms that encompass issues of empathy, racial attitudes, and identity as potential platforms opening up a more “social” neuroscience.

Research limitations/implications – This chapter provides a starting-point for further research incorporating biological mechanisms into sociological theories in the area of morality. The illustrative case study should be replicated in a larger sample and/or in additional studies with different social groups.

Practical implications – This chapter is a useful source of information for sociologists seeking to find out more about the intersection of neuroscience and sociology as well as the neural dynamics of morality.

Originality/value – This chapter presents an introduction to an integrative approach recognizing our biological capacities for a socially constructed morality and the interaction between society and the mind. It includes one of the first sociologically oriented fMRI studies, offering avenues for new ways to bridge research disciplines.

Substantial research has examined the self-concept, but little work has investigated the contents and structure of the self-concept in combination within performance settings, particularly from a within-person perspective. Thus, this research developed and examined a conceptual framework based on Greenwald et al. (2002) to understand how core self-evaluations (CSE) and self-concept clarity (SCC) interact to influence motivational orientation with implications for performance dimensions.

Full-time employees (N = 138) completed daily measures of CSE, SCC, motivational orientation, organizational citizenship behaviors (OCBs) and counterproductive work behaviors (CWBs) over the course of three weeks.

Multilevel modeling indicated CSE influences motivational orientation, SCC can moderate these relationships and motivational orientation relates to OCBs and counterproductive work behaviors.

This work contributes to this research area by developing and examining an integrative conceptual framework involving aspects of self-concept, motivation and performance from a within-person perspective.

The purpose of this paper is to design and develop a new robotic device for the rehabilitation of the upper limbs. The authors are focusing on a new symmetrical robot which can be used to rehabilitate the right upper limb and the left upper limb. The robotic arm can be automatically extended or reduced depending on the measurements of the patient's arm. The main idea is to integrate electrical stimulation into motor rehabilitation by robot. The goal is to provide automatic electrical stimulation based on muscle status during the rehabilitation process.

The developed robotic arm can be automatically extended or reduced depending on the measurements of the patient's arm. The system merges two rehabilitation strategies: motor rehabilitation and electrical stimulation. The goal is to take the advantages of both approaches. Electrical stimulation is often used for building muscle through endurance, resistance and strength exercises. However, in the proposed approach the electrical stimulation is used for recovery, relaxation and pain relief. In addition, the device includes an electromyography (EMG) muscle sensor that records muscle activity in real time. The control architecture provides the ability to automatically activate the appropriate stimulation mode based on the acquired EMG signal. The system software provides two modes for stimulation activation: the manual preset mode and the EMG driven mode. The program ensures traceability and provides the ability to issue a patient status monitoring report.

The developed robotic device is symmetrical and reconfigurable. The presented rehabilitation system includes a muscle stimulator associated with the robot to improve the quality of the rehabilitation process. The integration of neuromuscular electrical stimulation into the physical rehabilitation process offers effective rehabilitation sessions for neuromuscular recovery of the upper limb. A laboratory-made stimulator is developed to generate three modes of stimulation: pain relief, massage and relaxation. Through the control software interface, the physiotherapist can set the exercise movement parameters, define the stimulation mode and record the patient training in real time.

There are certain constraints when applying the proposed method, such as the sensitivity of the acquired EMG signals. This involves the use of professional equipment and mainly the implementation of sophisticated algorithms for signal extraction.

Functional electrical stimulation and robot-based motor rehabilitation are the most important technologies applied in post-stroke rehabilitation. The main objective of integrating robots into the rehabilitation process is to compensate for the functions lost in people with physical disabilities. The stimulation technique can be used for recovery, relaxation and drainage and pain relief. In this context, the idea is to integrate electrical stimulation into motor rehabilitation based on a robot to obtain the advantages of the two approaches to further improve the rehabilitation process. The introduction of this type of robot also makes it possible to develop new exciting assistance devices.

The proposed design is symmetrical, reconfigurable and light, covering all the joints of the upper limbs and their movements. In addition, the developed platform is inexpensive and a portable solution based on open source hardware platforms which opens the way to more extensions and developments. Electrical stimulation is often used to improve motor function and restore loss of function. However, the main objective behind the proposed stimulation in this paper is to recover after effort. The novelty of the proposed solution is to integrate the electrical stimulation powered by EMG in robotic rehabilitation.

This paper aims to focus on brand oldness associations and their measurement. Research on brand age points to a variety of interpretations concerning perceived brand oldness and establishes the existence of multiple positive consequences such as brand credibility, trust or attachment. However, the complexity and measurement of brand oldness associations are not yet well-established. This paper proposes a reliable and valid measurement scale of the concept.

The research follows a rigorous scale-development procedure based on eight empirical studies, with a total of 2,065 respondents. The data were analyzed through covariance-based structural equation modeling.

The scale consists of 18 items and six dimensions, namely, decline, expertise, maintenance, reminiscence, timelessness and tradition. Results demonstrate an effect of brand oldness associations on both brand attachment and brand equity.

The research was conducted in one country (France). Additional studies in other settings or countries should be carried out to establish generalizability of results and strengthen causality inferences.

This is the first research to study the notion of brand oldness associations. This study identifies its dimensions, develops a measurement scale and demonstrates its reliability and validity.

Leadership training has led to a large amount of research due to the belief that such training can lead to (or more precisely cause) positive changes in followers’ behavior and work performance. This chapter describes some of the conditions necessary for research to show a causal relationship between leadership training and outcomes. It then describes different research designs, employed in leadership training research, and considers the types of problems that can affect inferences about causality. The chapter focuses on the role of randomization of leaders (e.g., into training vs. non-training conditions) as a key methodological procedure and alludes to problems of achieving this in field settings.

The purpose of this study is to develop a method to reduce the computation time necessary for the automated optimal design of dual-band wearable antennas. In particular, the authors investigated if this can be achieved by the use of a hierarchical optimization paradigm combined with a simplified human body model. The geometry of the antenna under consideration is described via eight geometrical parameters which are automatically adjusted with the use of an evolutionary algorithm to improve the impedance matching of an antenna located in the proximity of a human body. Specifically, the antennas were designed to operate in the ISM band which covers two frequency ranges: 2.4-2.5 GHz and 5.7-5.9 GHz.

During the studies on the automated design of wearable antennas using evolutionary computing, the authors observed that not all design parameters exhibit equal influence on the objective function. Therefore, it was hypothesized that to reduce the computation effort, the design parameters can be activated sequentially based on their influence. Accordingly, the authors’ computer code has been modified to include this feature.

The authors’ novel hierarchical multi-parameter optimization method was able to converge to a better solution within a shorter time compared to an equivalent method not exploiting automatic activation of an increasing number of design parameters. Considering a significant computational cost involved in the calculation of the objective function, this exhibits a convincing advantage of their hierarchical approach, at least for the considered class of antennas.

The described method has been developed for the design of single- or dual-band wearable antennas. Its application to other classes of antennas and antenna environments may require some adjustments of the objective functions or parameter values of the evolutionary algorithm. It follows from the well-recognized fact that all optimization methods are to some extent application-specific.

Computation load involved in the automated design and optimization can be significantly reduced compared to the non-hierarchical approach with a heterogeneous human body model.

To the best of the authors’ knowledge, the described application of hierarchical paradigm to the optimization of wearable antennas is fully original, as well as is its combination with simplified body models.