8 research outputs found

    Examining the generalizability of research findings from archival data

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    This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability-for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples

    Examining the generalizability of research findings from archival data

    Get PDF
    This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability—for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples

    Service Failures in Times of Crisis: An Analysis of eWOM Emotionality

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    The COVID-19 pandemic continues to disrupt consumer experiences as well as service operations. Despite the magnitude of this exogenous shock, little is known about the pandemic’s impact on consumers. Building on engagement theory, this study examines consumers’ emotional responses to service failures on social media. Contributing to the brand equity literature, we test whether electronic word-of-mouth (eWOM) emotionality is contingent on brand strength. To do so, we analyzed 327,205 tweets directed at airline brands over the first 12 months of the pandemic in addition to data from a nonaffected period. The models show that consumers’ overall emotionality in tweets was lower during the pandemic than before it. Over the course of the pandemic, levels of joy were lower while levels of sadness and anger were more prominent in tweets directed at weaker brands. Thus, brand strength still acts as a “buffer” if service failures are caused by exogenous shocks

    Examining the generalizability of research findings from archival data.

    Get PDF
    This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability-for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples

    How valence, volume and variance of online reviews influence brand attitudes

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