A Model Integrating the Multidimensional Developmental Theory of Privacy and Theory of Planned Behavior to Examine Fabrication of Information Online

We investigate the antecedents behind online consumers' attempt to disguise their identities through fabrication. We first develop a general conceptual model that draws on two extant theoretical frameworks: (1) Laufer and Wolfe's Multidimensional Approach to Privacy, and (2) Ajzen's Theory of Planned Behavior (TPB) with Perceived Moral Obligation. Next we conduct an empirical study using SEM to test the portion of the conceptual model based on the TPB framework. Results demonstrate that Attitudes, Perceived Behavioral Control, and Perceived Moral Obligation are significant drivers of fabrication, while Subjective Norms are not. Anonymity, one of the unique characteristics of the Internet compared to in-store environments, likely contributed to the intention to fabricate information. In the concluding section we discuss the implications of our empirical results, industry self-regulation and public policy considerations, and how future research can draw upon the conceptual Laufer and Wolfe framework, particularly the calculus of behavior construct, to further enrich our understanding of fabrication behavior on the Internet.     

Threshold estimation for continuous three-phase polynomial regression models with constant mean in the middle regime

This paper considers a continuous three-phase polynomial regression model with two threshold points for dependent data with heteroscedasticity. We assume the model is polynomial of order zero in the middle regime, and is polynomial of higher orders elsewhere. We denote this model by ${ℳ}_2$, which includes models with one or no threshold points, denoted by ${ℳ}_1$ and ${ℳ}_0$, respectively, as special cases. We provide an ordered iterative least squares (OiLS) method when estimating ${ℳ}_2$ and establish the consistency of the OiLS estimators under mild conditions. When the underlying model is ${ℳ}_1$ and is $(d_0-1)$th-order differentiable but not $d_0$th-order differentiable at the threshold point, we further show the $O_p(N^{-1/(d_0+2)})$ convergence rate of the OiLS estimators, which can be faster than the $O_p(N^{-1/(2d_0)})$ convergence rate given in Feder when $d_0\ge 3$. We also apply a model-selection procedure for selecting ${ℳ}_{\kappa }$; $\kappa =0,1,2$. When the underlying model exists, we establish the selection consistency under the aforementioned conditions. Finally, we conduct simulation experiments to demonstrate the finite-sample performance of our asymptotic results.