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In a recent paper, Hausman, Newey, Woutersen, Chao, and Swanson (2012) propose a new estimator, HFUL (Heteroscedasticity robust Fuller), for the linear model with endogeneity. This estimator is consistent and asymptotically normally distributed in the many instruments and many weak instruments asymptotics. Moreover, this estimator has moments, just like the estimator by Fuller (1977). The purpose of this note is to discuss at greater length the existence of moments result given in Hausman et al. (2012). In particular, we intend to answer the following questions: Why does LIML not have moments? Why does the Fuller modification lead to estimators with moments? Is normality required for the Fuller estimator to have moments? Why do we need a condition such as Hausman et al. (2012), Assumption 9? Why do we have the adjustment formula?

This chapter shows how a weighted average of a forward and reverse Jackknife IV estimator (JIVE) yields estimators that are robust against heteroscedasticity and many instruments. These estimators, called HFUL (Heteroscedasticity robust Fuller) and HLIM (Heteroskedasticity robust limited information maximum likelihood (LIML)) were introduced by Hausman, Newey, Woutersen, Chao, and Swanson (2012), but without derivation. Combining consistent estimators is a theme that is associated with Jerry Hausman and, therefore, we present this derivation in this volume. Additionally, and in order to further understand and interpret HFUL and HLIM in the context of jackknife type variance ratio estimators, we show that a new variant of HLIM, under specific grouped data settings with dummy instruments, simplifies to the Bekker and van der Ploeg (2005) MM (method of moments) estimator.

The technology acceptance model (TAM) has been one of the most influential theories in the information technology literature, but it has not been used in the marketing literature to understand consumer acceptance of international web sites. Thus, the purpose of this study is to use TAM to study international consumers' acceptance and use of MNEs web sites designed specifically for their country.

This study applies and extends the TAM to study the B2C international web sites of American and Japanese MNEs for Brazilian, German, and Taiwanese consumers. In total, there were 2,243 usable questionnaires and the structural equation modeling method was used to analyze the data.

This study provides strong support for the applicability of TAM in explaining international web site usage in Brazil, Germany, and Taiwan and shows that cultural adaptation is an important explanatory variable that should be included in the TAM when exploring cross‐cultural issues.

The value of this paper is that it not only extends the use of TAM to study user acceptance of international e‐commerce web sites, but also sees how the cultural adaptation of international web sites impacts the attitude and the purchase intention of consumers.

Team cohesion and other team processes are inherently dynamic mechanisms that contribute to team effectiveness. Unfortunately, extant research has typically treated team cohesion and other processes as static, and failed to capture how these processes change over time and the implications of these changes. In this chapter, we discuss the characteristics of team process dynamics and highlight the importance of temporal considerations when measuring team cohesion. We introduce innovative research methods that can be applied to assess and monitor team cohesion and other process dynamics. Finally, we discuss future directions for the research and practical applications of these new methods to enhance our understanding of the dynamics of team cohesion and other processes.

This paper proposes a new class of estimators for the autoregressive coefficient of a dynamic panel data model with random individual effects and nonstationary initial condition. The new estimators we introduce are weighted averages of the well-known first difference (FD) GMM/IV estimator and the pooled ordinary least squares (POLS) estimator. The proposed procedure seeks to exploit the differing strengths of the FD GMM/IV estimator relative to the pooled OLS estimator. In particular, the latter is inconsistent in the stationary case but is consistent and asymptotically normal with a faster rate of convergence than the former when the underlying panel autoregressive process has a unit root. By averaging the two estimators in an appropriate way, we are able to construct a class of estimators which are consistent and asymptotically standard normal, when suitably standardized, in both the stationary and the unit root case. The results of our simulation study also show that our proposed estimator has favorable finite sample properties when compared to a number of existing estimators.

Differs from previous studies of managerial selection methods. Focuses wholly on the activities of external executive recruitment consultancies. Results are presented from two major surveys on the use of selection methods by such consultancies: in general they use low validity techniques, primarily unstructured interviews and references. Low validity selection methods may be used because validity is not the primary “evaluative standard”. Suggests five alternative “evaluative standards”.