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Although supplier-initiated punishment is widely used to manage distributors’ opportunism, its spillover effect on unpunished distributors (i.e. observers) within the same distribution network remains under-researched. Specifically, this paper aims to investigate the curvilinear effect of punishment severity on an observer’s opportunism, and how such an effect is contingent on the observer’s network position.

This paper uses regression analysis with survey data gathered from 218 distributors in China’s automobile industry.

Punishment severity has an inverted U-shaped effect on the observers’ opportunism, and such effect is weakened by both the observers’ network centrality and their degree of dependence on the supplier.

The findings should encourage suppliers to focus more on the spillover effects of punishment on observers. To this end, the supplier must deliberately initiate the appropriate level of punishment severity against its distributors because an inappropriate level of punishment severity (e.g. too lenient) may unexpectedly raise the unpunished observers’ level of opportunism. Moreover, the supplier should be fully aware that observers’ specific network positions may produce varying spillover effects of the punishment.

This study enriches the literature on channel governance by revealing the curvilinear mechanism through which punishment severity influences observers’ opportunism. By applying social learning theory to channel punishment research, this study unveils both the inhibitive learning and the imitative learning forces inherent in a single punishment event, and it delineates their joint effect on an observer’s opportunism. In addition, this study outlines the observer’s vertical and horizontal relationships within the distribution network and explores their contingent roles in determining the spillover effects of punishment.

Although manufacturer-initiated rewards are widely used to secure distributors’ compliance, the spillover effect on unrewarded distributors (i.e. observers) in the same distribution channel is under-researched. Using insights from social learning theory, this paper aims to investigate how manufacturer-initiated rewards affect observers’ expectation of reward and shape observers’ compliance toward the manufacturer. Furthermore, this paper explores how such effects are contingent upon distributor relationship features.

To test the hypotheses, hierarchical multiple regression and bootstrapping analyses were performed using survey data from 280 Chinese distributors.

The magnitude of a manufacturer-initiated reward to a distributor stimulates expectation of reward among observers, which enhances compliance; observers’ expectation of reward mediates the impact of reward magnitude on compliance. Moreover, network centrality (of the rewarded peer) negatively moderates the positive impact of reward magnitude on observers’ expectation of reward, whereas observers’ dependence (on the manufacturer) positively moderates this dynamic.

Manufacturers should pay attention to the spillover effects of rewards. Overall, they should use rewards of appropriate magnitude to show willingness to recognize outstanding distributors. This will inspire unrewarded distributors, which will then be more compliant. Furthermore, manufacturers should know that specific types of distributor relationship features may significantly vary the spillover effects.

This study illuminates the spillover effects of manufacturer-initiated reward by opening the “black box” of the link between reward magnitude and observers’ compliance and by specifying the effects’ boundary conditions.

Modeling is a potentially productive activity in which coaches can engage teachers to support teaching and learning (Gibbons and Cobb, 2017). Yet, there is a lack of empirical research that describes how coaches can productively implement this activity with teachers. The overarching purpose of this study was to explore the challenges and support coaches faced while modeling instruction for teachers.

Twenty-nine semi-structured interviews were conducted with five coaches and six elementary teachers in two different school districts in the United States. The data were qualitatively coded using a combination of literature-driven and emergent codes.

Participants identified 16 distinct challenges they faced during coaching cycles involving modeling, and 11 supports that could ultimately enhance the success of the modeled lesson for all involved parties. These challenges and support spanned the broad categories of contextual factors, management and logistics, pedagogical dilemmas and teacher learning.

Although modeling is a popular coaching activity, researchers have only an emerging understanding of the challenges associated with modeling instruction, as well as the support that can enhance the modeled lesson's success. By having a thorough understanding of such challenges and support, coaches can effectively leverage modeling to support teaching and learning at their schools. Hence, the findings from this study will importantly inform coaching practice, as well as future research directions.

Prior studies have extensively explored individual examples of unethical behavior in sales organizations but focused little on repeated violation (RV) of ethical codes, particularly when managers develop salesforces. Based on social learning theory (SLT), the authors propose a multilevel model of RV antecedents and suggest that organizational influence (social cues and modeling) and individual factors (observer characteristics and behavioral outcomes) affect RV, especially with increasing recruitment of salespeople.

Using data from a leading financial company in Taiwan, the authors analyzed 1,231 records of salespeople’s misbehavior through logistic regression and average marginal effects.

Modeling in the organization (i.e. peer misconduct), observer characteristics (i.e. experience concerning job tenure and prior violations) and behavioral outcomes (i.e. information concealment violations) were all found to affect the likelihood of RV, and the interactional effect of organizational size was confirmed.

This study contributes to ethical decision-making theory by explaining aspects of RV through SLT. Its multilevel model, integrated with organizational strategy theories, adds an SLT-focused paradigm into unethical behavior research by considering vicarious learning and self-learning, alongside the reciprocal determinism of cognition, behavior, and environment.

Managers should consider socially based patterns of violation when initiating a sales business plan. The chances of RV are increased by unethical models in the organization and offenders’ potential for violations, which is reinforced by social environment.

This study clarified the key drivers of RV decision-making using SLT and identified an effective sales development strategy to maintain an ethically responsible salesforce.

Research on entrepreneurial behaviour has been largely descriptive in nature. Critics of the field have called for an interdisciplinary approach to build theory. A social learning theory framework is proposed for explanation and prediction of entrepreneurial development. Research questions are posed and a model developed to guide future enquiry.

The purpose of this paper is to review the literature on observation of teaching in a Higher Education (HE) context with a view to proposing some guidelines for the design and practice of institutional systems to observe teaching.

A literature review and a proposed model for a system of observation of teaching with practical suggestions for managing the process and the information that results from implementation.

Practice in this area across the HE sector remains patchy and frequently cursory, despite the benefits that may follow from implementation of such systems, namely improved teaching and thus student learning.

This article synthesises best practice guidelines and proposes a three‐stage process to be adopted to help ensure that lecturers (and their students) gain the maximum benefit from being observed.

The purpose of this paper is to accomplish robust actuator fault isolation and identification for microsatellite attitude control systems (ACSs) subject to a series of space disturbance torques and gyro drifts.

For the satellite attitude dynamics with Lipschitz constraint, a multi-objective nonlinear unknown input observer (NUIO) is explored to accomplish robust actuator fault isolation based on a synthesis of H_inf techniques and regional pole assignment technique. Subsequently, a novel disturbance-decoupling learning observer (D²LO) is proposed to identify the isolated actuator fault accurately. Additionally, the design of the NUIO and the D²LO are reformulated into convex optimization problems involving linear matrix inequalities (LMIs), which can be readily solved using standard LMI tools.

The simulation studies on a microsatellite example are performed to prove the effectiveness and applicability of the proposed robust actuator fault isolation and identification methodologies.

This research includes implications for the enhancement of reliability and safety of on-orbit microsatellites.

This study proposes novel NUIO-based robust fault isolation and D²LO-based robust fault identification methodologies for spacecraft ACSs subject to a series of space disturbance torques and gyro drifts.

The purpose of this study is to analyze the configurational effect of transformational leadership, team conflict, team cohesion and psychological safety on team learning.

The questionnaire and two different data sources (team members and team leaders) were used as data collection strategy. Based on a sample of 82 teams, qualitative comparative analysis in its fuzzy set variant was used to test the model.

The findings of this study reveal that three important paths explain team learning: the presence of transformational leadership, task cohesion and psychological safety with the absence of relationship conflict; the presence of transformational leadership, social and task cohesion and psychological safety; and the presence of transformational leadership, social and task cohesion with the absence of relationship and task conflict.

Overall, the findings suggest that the presence of transformational leadership, team cohesion and psychological safety and the absence of conflict are important conditions for team learning to occur, as well as that more than one configurations of antecedent factors drive team learning.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Different types of barrier can impede the learning that is critical within workplaces that are complex and challenging. Firms that identify and successfully address these barriers become better placed to create conditions that are more conducive to workplace learning.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

W. Ross Ashby’s elementary non-trivial machine, known in the cybernetic literature as the “Ashby Box,” has been described as the prototypical example of a black box system. As far as it can be ascertained from Ashby’s journal, the intended purpose of this device may have been to exemplify the environment where an “artificial brain” may operate. This paper describes the construction of an elementary observer/controller for the class of systems exemplified by the Ashby Box – variable structure black box systems with parallel input.

Starting from a formalization of the second-order assumptions implicit in the design of the Ashby Box, the observer/controller system is synthesized from the ground up, in a strictly system-theoretic setting, without recourse to disciplinary metaphors or current theories of learning and cognition, based mainly on guidance from Heinz von Foerster’s theory of self-organizing systems and W. Ross Ashby’s own insights into adaptive systems.

Achieving and maintaining control of the Ashby Box requires a non-trivial observer system able to use the results of its interactions with the non-trivial machine to autonomously construct, deconstruct and reconstruct its own function. The algorithm and the dynamical model of the Ashby Box observer developed in this paper define the basic specifications of a general purpose, unsupervised learning architecture able to accomplish this task.

The problem exemplified by the Ashby Box is fundamental and goes to the roots of cybernetic theory; second-order cybernetics offers an adequate foundation for the mathematical modeling of this problem.