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Sustainability is an emotional issue. It is also an issue that is gaining prominence in organizational agendas. In this chapter, we outline a model to explain how employees perceive change agents working to implement sustainability initiatives in organizations. Using this model, we argue that organizational support for sustainability can influence how employees respond to sustainability messages. We further argue that the intensity of emotions that change agents display, and how appropriate those emotions are within the organizational context, will influence how employees perceive those individuals and the success of their efforts to influence green outcomes.

We extend the Dual Threshold Model of emotions (DTM: Geddes & Callister, 2007) to assess the impact of displays of emotional intensity on achieving sustainability goals. Our model links emotional propriety to change agent success. By exploring variations of the DTM in terms of contextual factors and emotional intensity, our model elaborates on the dynamic nature of emotional thresholds.

Using our framework, change agents may be able to improve their influence by matching the emotional intensity of their messages to the relevant display rules for that organization. That is, change agents who are perceived to express emotion within the thresholds of propriety can enhance their success in implementing green outcomes.

This chapter examines sustainability initiatives at the interpersonal behavior level. We combine aspects of organizational behavior, emotion in organizations, and organizations and the natural environment to create a new model for understanding change agent success in corporate sustainability.

This monograph presents a thorough examination of the phenomena of “threshold” levels of advertising activity and the “wearout’ of advertisements and/or campaigns. These are seen as corresponding to the management questions “How little can we spend/How infrequently can we advertise?” and “How much is too much/How infrequently is too little?” In the first section the relevant literature on, or related to, the two issues is reviewed. Section 2 describes a survey aimed at establishing current beliefs in the existence of the phenomena, the practices resulting from these beliefs, and the data which support them. Finally, Section 3 offers an overview on the managerial issues involved in decisions concerning threshold or wearout risks in advertising. It is suggested that wasted expenditure may be occurring in advertising because the believed levels of threshold and wearout are both too high.

The purpose of this paper is to investigate the spillover effects of a bright-line disclosure regulation that required Chinese listed firms to provide earnings forecasts if they anticipated specified, large earnings changes.

The paper examines the discontinuity of the earnings change distribution of firms listed on the Shenzhen Stock Market between 2010 and 2014. The paper finds that firms no longer subject to the bright-line test still exhibited discontinuity in earnings change distribution. The discontinuity lasted for at least three years with magnitude comparable to that of the firms still subject to the bright-line test. In addition, newly listed firms that had never experienced the bright-line test showed similar tendency to avoid the same threshold. There is some evidence that these firms’ avoidance of the −50 per cent changes was partly because of market pressure.

Research on bright-line tests has to date focused on their immediate and direct effects on firms currently subject to such tests. This study finds that a bright-line disclosure regulation’s influence is not limited to the firms directly governed by the regulation. It could lead to widespread and long lasting distortions in financial reporting behaviors of firms not currently subject to such tests.

The paper has implications for regulators who study the economic consequences of bright-line regulations in general and analysts of the Chinese capital market in particular.

This is the first empirical report that bright-line disclosure regulations affected the financial reporting behavior of firms that were not directly subject to the bright-line tests.

The purpose of this paper is to examine a model for conceptualizing the impacts of environmental management strategies on travel and recreation choice making behavior that considers tolerance thresholds in visitor responses to destination change.

A survey involving a sample of 347 regular campers and fishers in the Ningaloo Marine Park, Australia, is analyzed to discern the effect of tolerance thresholds.

Despite widespread dissatisfaction with enlarged sanctuary zones and negative impacts on recreational activities, visitors indicated a high level of satisfaction with their stay. This apparent contradiction is, it is argued, best explained by the threshold of tolerability concept.

It is argued that recreational users, planning authorities and other stakeholders have a threshold of tolerability in terms of decision‐making concerning management changes. These thresholds mean that changes in management policies, modes of activity and destination travel choices are rarely predictable in their effect, but are bounded by minimal and ideal expectations of destination appeal.

The paper introduces an important concept for tourism research that will aid tourism planning and management authorities in the face of growing environmental pressures caused by overpopulation and climate change.

This chapter reviews recent developments in the density discontinuity approach. It is well known that agents having perfect control of the forcing variable will invalidate the popular regression discontinuity designs (RDDs). To detect the manipulation of the forcing variable, McCrary (2008) developed a test based on the discontinuity in the density around the threshold. Recent papers have noted that the sorting patterns around the threshold are often either the researcher’s object of interest or may relate to structural parameters such as tax elasticities through known functions. This, in turn, implies that the behavior of the distribution around the threshold is not only informative of the validity of a standard RDD; it can also be used to recover policy-relevant parameters and perform counterfactual exercises.

Individual decisions fall in the broad categories of instinctive, automatic, intuitive, deliberate, and impulsive. Decisions may be conscious, pre‐conscious, or unconscious. These broad categorizations serve as background for the thrust of this paper. Decisions occur if certain forces exceed a threshold. This paper centers on issues related to action thresholds in the context of marketing. The approach characterizes decision space of an individual in the context of multidimensional utility‐psychic space. Variables of different characteristics influence decision space and thresholds. Asserts that variables of influence in the psychic region of the mind play an especially important role in this decision space and in marketing. Offers a conceptual background on this decision space and thresholds and focuses on implications for marketing.

The purpose of this paper is to adapt concepts from resiliency theory to understand the conditions under which social enterprises may remain true to form and purpose or are likely to change their character. This leads us to consider issues of governance, economic incentives associated with different organizational forms of social enterprise and the effects of the financial environment, the role of organizational slack and the influence of organizational leadership on the dynamics of social enterprises. Three case studies of organizations in the USA are analyzed to illustrate the application of resiliency theory to the stability of social enterprises. The fact that all forms of social enterprise must reconcile the tensions of social purpose and market raises important questions about the dynamics of these enterprises.

Theory and case study analysis.

Governance, financial incentive structure, organizational slack and leadership influence the stability of social enterprises.

First application of resiliency theory to the analysis of social enterprise stability.

Classification techniques have been applied to many applications in various fields of sciences. There are several ways of evaluating classification algorithms. The analysis of such metrics and its significance must be interpreted correctly for evaluating different learning algorithms. Most of these measures are scalar metrics and some of them are graphical methods. This paper introduces a detailed overview of the classification assessment measures with the aim of providing the basics of these measures and to show how it works to serve as a comprehensive source for researchers who are interested in this field. This overview starts by highlighting the definition of the confusion matrix in binary and multi-class classification problems. Many classification measures are also explained in details, and the influence of balanced and imbalanced data on each metric is presented. An illustrative example is introduced to show (1) how to calculate these measures in binary and multi-class classification problems, and (2) the robustness of some measures against balanced and imbalanced data. Moreover, some graphical measures such as Receiver operating characteristics (ROC), Precision-Recall, and Detection error trade-off (DET) curves are presented with details. Additionally, in a step-by-step approach, different numerical examples are demonstrated to explain the preprocessing steps of plotting ROC, PR, and DET curves.

This article considers a reliability model where the failure is due to cumulative damage exceeding a threshold level. The concept that the threshold level of cumulative damage at each arrival of shock can change based on whether the magnitude of each shock exceeds its defined threshold level is considered to compute the system reliability.

The stochastic process approach is used to obtain the cumulative damage based on Poisson arrival of shocks. The general expression for reliability is obtained using the conditional probability over each arrival of shock. The method of maximum likelihood estimation is used to obtain the estimators of the parameters and system reliability. A sensitivity analysis is performed to measure the effect of the parameter representing the rate of arrival of shock.

The maximum likelihood estimates of the reliability approach the actual reliability for increasing sample size. A sensitivity analysis study on the parameter representing the rate of arrival of shock shows that as the values of parameter increase (decrease), the reliability value decreases (increases).

Obtained a new expression for the cumulative damage–shock model and the findings are positively supported by presenting the general trend of estimated values of reliability approaching the actual value of reliability. The sensitivity analysis also genuinely supports our findings.

Regression discontinuity (RD) models are commonly used to nonparametrically identify and estimate a local average treatment effect. Dong and Lewbel (2015) show how a derivative of this effect, called treatment effect derivative (TED) can be estimated. We argue here that TED should be employed in most RD applications, as a way to assess the stability and hence external validity of RD estimates. Closely related to TED, we define the complier probability derivative (CPD). Just as TED measures stability of the treatment effect, the CPD measures stability of the complier population in fuzzy designs. TED and CPD are numerically trivial to estimate. We provide relevant Stata code, and apply it to some real datasets.