We clarify differences among moderation, partial mediation, and full mediation and identify methodological problems related to moderation and mediation from a review of articles in Strategic Management Journal and Organization Science published from 2005 to 2014.
Statistical control is widely used in correlational studies with the intent of providing more accurate estimates of relationships among variables, more conservative tests of hypotheses, or ruling out alternative explanations for empirical findings.
Does the way that individuals pay for a good or service influence the amount of connection they feel after the purchase has occurred? Employing a multi-method approach across four studies, individuals who pay using a relatively more painful form of payment (e.g., cash or check) increase their post-transaction connection to the product they purchased and/or the organization their purchase supports in comparison to those who pay with less painful forms of payment (e.g., debit or credit card).
Exploiting a 2004 reduction in a unique capital gains withholding tax for foreign investors in U.S. publicly traded REITs, this paper explores both the sensitivity of real estate investors to changes in their own taxes and the reaction of real estate managers to changes in their investors' taxes. We find that both foreign investors and REIT managers responded to the tax change.
The authors study the drivers and performance implications of retailers’ branding strategies for their premium and economy private-label tiers. Retailers can opt for store-banner branding and use their store-banner name and/or logo to reveal their ownership, or they can use stand-alone branding and avoid an explicit link between store brand and retail banner.
In this paper we argue that task design affects rule breaking in the workplace. Specifically, we propose that task variety activates deliberative (Type 2) processes as opposed to automatic/intuitive (Type 1) processes, which, in turn, helps prevent individuals from breaking rules in order to serve their own hedonic self-interest.
Across the globe, every workday people commute an average of 38 minutes each way, yet surprisingly little research has examined the implications of this daily routine for work-related outcomes. Integrating theories of boundary work, self-control, and work-family conflict, we propose that the commute to work serves as a liminal role transition between home and work roles, prompting employees to engage in boundary management strategies.
How best to structure the work day is an important operational question for organizations. A key structural consideration is the effective use of breaks from work. Breaks serve the critical purpose of allowing employees to recharge, but in the short term, translate to a loss of time that usually leads to reduced productivity. We evaluate the effects of two types of breaks (expected versus unexpected), and two distinct forms of unexpected breaks, and find that unexpected breaks can, under certain conditions, yield immediate post-break performance increases.
Determining how best to route work is a key element of service system design. Not surprisingly then, many analytical models have identified various optimal routing algorithms for service operations management. However, in many settings, humans make routing decisions dynamically, either because algorithms don't exist, decision support tools have not been implemented, or existing rules are not enforced.
We propose a new theory of systemic risk based on Knightian uncertainty (“ambiguity”). Because of uncertainty aversion, bad news on one asset class worsens investors’ expectations on other asset classes, so that idiosyncratic risk creates contagion, snowballing into systemic risk.
We develop Granger causality tests that apply directly to data sampled at different frequencies. We show that taking advantage of mixed frequency data allows us to better recover causal relationships when compared to the conventional common low frequency approach.
Many time series are sampled at different frequencies. When we study co-movements between such series we usually analyze the joint process sampled at a common low frequency.
We propose a quantile-based measure of conditional skewness, particularly suitable for handling recalcitrant emerging market (EM) returns. The skewness of international stock market returns varies significantly across countries over time, and persists at long horizons.
This article presents a reduced-form model that contains frailty factors to predict mortgage default and develops a novel framework to model systematic risk of mortgages. We match default rates along multiple dimensions by extending the generalized autoregressive score (GAS) models.
We examine the relationship between MIDAS regressions and the estimation of state space models applied to mixed frequency data. While in some cases the binding function is known, in general it is not, and therefore indirect inference is called for. The approach is appealing when we consider state space models which feature stochastic volatility, or other non-Gaussian and nonlinear settings where maximum likelihood methods require computationally demanding approximate filters.
Because security analysts, who serve as brokers between public firms and investors, arrive at their forecasts by incorporating guidance from managers, there is immense pressure on the managers to meet or beat analyst earnings forecasts; moreover, investors reward (penalize) firms for exceeding (missing) analyst forecasts.
Successful initial public offerings (IPOs) provide firms with access to valuable resources, but also put pressure on firms to impress potential investors with evidence of their current well-being and prospects for future growth.
Firms spend billions of dollars on advertising every year but remain uncertain about allocation across various advertising vehicles. Allocation decisions are even more complex as online advertising has proliferated and consumers' media usage patterns have become more fragmented.
Using an integrative approach, the authors incorporate the four mechanisms in their empirical model specification. Specifically, to model the interplay among CSR, CSI, and firm performance and to test the four mechanisms simultaneously, they propose a structural panel vector autoregression specification.
In this paper, we study the effect of a firm’s local channel exits on prices charged by incumbents remaining in the marketplace. Exits could result in higher prices due to tempered competition or lower prices due to reduced co-location or agglomeration benefits. The net effect of these two countervailing forces remains unknown. In addition, little is known about how this effect could change depending on incumbents’ geographic locations.