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Prior research suggests that there is enough residual uncertainty in conflict situations so that a person's attitude towards risk may influence his or her conflict behavior. This paper explores the level of dyadic conflict arising from negotiation between partners having different combinations of risk propensities. Dyadic conflict was measured as the sum of each dyadic partner's conflict score using the Rahim Organizational Conflict Inventory‐I. Risk propensities of negotiators were induced The results from the experiment provide clear evidence in support of the research hypothesis that in a dyad, the greater the disparity between the negotiating partners in their risk‐taking propensities, the greater will be the levels of dyadic conflict. The result suggests that conflict models of negotiating under uncertainty need to include risk propensities of the players to expand their descriptive power.

PurposeThe purpose of this paper is to first examine whether intellectual capital (IC) information is considered in firm valuation. Next, to examine two issues: financial analysts' investment recommendations when faced with different combinations of performance levels (i.e. above or below industry average) of financial and IC measures, and the role of financial and IC measures with different performance levels and holding periods (i.e. short‐term vs long‐term) for the investment on analysts' recommendations.Design/methodology/approachThe first part of the paper used secondary (both archival and survey) data. The second part was an experiment.FindingsThe findings in the first part show that, after controlling for the effect of financial performances on firm value, measures of IC are still significant explanatory variables (of firm value). The second part shows that the financial and IC measures affect financial analysts' investment recommendations differently depending on the measures' levels of performance and the time horizon for holding the investments.Research limitations/implicationsThe limitations of the paper are as follows: the use of secondary data from a single country limits its generalizability; and the results of the experiment are parameterized by the research design such as the amount of information provided to the financial analysts. Extending the analyses to other settings and using time‐series data represent future research opportunities.Originality/valueThe research makes three contributions to the IC literature. First, it extends the studies on the relevance of IC in capital market research by broadening its scope to include measures of IC other than R&D intensity. Next, it provides evidence of the informativeness of IC measures in market valuation of firms and analysts' recommendations, thus lending credence to the arguments of reports and researchers for more external communication of IC information. Finally, this study is one of the first to examine a broader scope of IC in the capital market context and the use of IC by sophisticated market participants. With policy‐makers and standard‐setting bodies considering proposals to enhance information on IC in financial reports, it is important to broaden the scope of IC metrics and understand their role in enhancing firm value to develop a framework for reporting IC.

ABSTRACTThis paper extends prior research by jointly assessing the roles of risk attitude and tolerance for ambiguity in predicting choice. An experiment examined the effects of these variables on decisions made in four different scenarios. The four scenarios (treatment combinations) were generated by manipulating risk and ambiguity into two levels (high and low). The context was defined in terms of a sample size selection problem. The second issue explored was the effect of attitudes toward risk and ambiguity on decision confidence.The results indicate that (1) both risk attitude and ambiguity intolerance determined choice behavior, (2) the roles of these individual attitudes depend on the levels of the two treatment variables of risk and ambiguity, (3) the presence of ambiguity accentuates the perception of risk in individual subjects, and (4) decision makers who are less risk averse, and have more tolerance for ambiguity, display greater confidence in their choice. The paper discusses some of the managerial implications of the results.

ABSTRACTDecisions in the real world usually involve imprecise information or uncertainty about the precesses by which outcomes may be determined. This research reports the results of a laboratory experiment which examined whether the structure of uncertainty, namely, both the center and the range of the probability distribution describing the uncertainty, is an important determinant of choice. Specifically, it examines how the uncertainty of audit by the Internal Revenue Service of income tax returns affects taxpayers' decisions about intentional noncompliance. The context is relevant as almost nothing is known about how taxpayers assess detection risks using the probability information they have.The study focuses on intentional noncompliance. The factors affecting it are distinct and separate from those affecting unintentional noncompliance. Other factors that affect intentional tax noncompliance, such as risk, tax rates, and penalty rates, were controlled in the experiment. It was hypothesized that the lower the mean and the lesser the range (ambiguity) of the perceived audit probability, the greater the international noncompliance. As hypothesized, the analysis indicates that both the mean and the range of the perceived audit probability rate affect intentional noncompliance, though the effect of ambiguity is greater at a relatively higher level of mean. This result suggests that the strength of the information describing an uncertain event is captured better by both the mean and the range of the uncertainty than either of those components singly.

ABSTRACTAlthough recent research has identified attitudes towards ambiguity and risk to be important determinants of choice behavior [8] [18], no prior work jointly assessed the roles of both attitudes. We conducted a laboratory experiment using a real decision scenario and conducted exploratory analyses of the relationship between attitudes towards risk and ambiguity and the decision taken by the subjects. The results support the prediction that attitudes towards both risk and ambiguity affect choice behavior. Our exploratory analyses indicate interesting avenues for future research, including an examination of the decision process itself.

In this study, we developed and analyzed a mathematical model for explaining the transmission dynamics of COVID‐19 in India. The proposed model is a modified version of the existing model. Our model divides the infected class of model into two classes: (unknown infected class) and (known infected class). In addition, we consider a recovered and reserved class, where susceptible people can hide them due to fear of the COVID‐19 infection. Furthermore, a non‐monotonic incidence function is deemed to incorporate the psychological effect of the novel coronavirus diseases on India's community. The epidemiological threshold parameter, namely the basic reproduction number, has been formulated and presented graphically. With this threshold parameter, the local and global stability analysis of the disease‐free equilibrium and the endemic proportion equilibrium based on disease persistence have been analyzed. Lastly, numerical results of long‐run prediction using MATLAB show that the fate of this situation is very harmful if people are not following the guidelines issued by the authority.