A Dynamic Model of the Longitudinal Relationship between Perceived progress and Effort in Complex Goal Realization Process:A Latent Change Score Approach

Journal of Psychological Science ›› 2021, Vol. 44 ›› Issue (3) : 522-529.

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PDF(1172 KB)
Journal of Psychological Science ›› 2021, Vol. 44 ›› Issue (3) : 522-529.

A Dynamic Model of the Longitudinal Relationship between Perceived progress and Effort in Complex Goal Realization Process:A Latent Change Score Approach

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Abstract

Perceived progress and effort represent two of the most important constructs in the existing literature. Despite of the accumulated knowledge, the reciprocal relationship between effort and perceived progress under the pursuit of long-term, multi-goals remains ambiguous. Thus, many scholars call for future research to unravel the complex relationship between perceived progress and effort under the pursuit of complex goals.However, other scholars hold the opposite view and found mixed or even contradictory findings. Some studies, using longitudinal correlations or cross-lagged regression, have provided initial evidence about the influence and possible direction of perceived progress and effort. However, these studies only rely on covariance rather than on mean structures. Thus, the findings of these studies cannot capture the dynamic changes in absolute levels of the constructs (i.e., the actual changes of effort when people perceived higher levels of progress). To clarify the effect of perceived progress on effort, this study uses a dynamic latent difference score model (LDS) with second data from an entrepreneur sample (PESD II) that have collected repeated measures across 5 occasions (years). We measure perceived progress with 7 objective indicators to evaluate the progress in the pursuit of one's venture goal. Analogously, effort is measured by assessing 5 key activities had been done for their new ventures. The final sample consists of 215 entrepreneurs who engaged in entrepreneurial activities across five measurement occasions (2006 to 2010). For our analyses, we conducted the LDS approach in Mplus 8.0. Figure 1 presents a path diagram of a bivariate LDS model with two factors: perceived progress and effort. In a bivariate LDS model (see Figure 1), latent intercepts and slopes (e.g., Intercept 1 and Slope 1 for effort) for two variables, as typically modeled in growth curve analyses, are constructed as the former affecting the same variable at the first occasion (e.g., Effort T1). The latent change variable (e.g., Δ Effort, T1-T2) is specified to be affected by three components: a linear systematic constant change from the slope (e.g., Slope 1), a proportional change from the same construct at a previous occasion (e.g., Effort T1), and effects from the other variable at a previous occasion (e.g., Perceived progress T1), as indicated by γ1. The findings provide support for a reciprocal model of relationships. Entrepreneurs who make more effort generally demonstrate higher perceived progress over time. Perceived progress, however, negatively predicts entrepreneurial effort. Overall, the findings of the present study have three major contributions: First, by constructing a latent difference score model, this study clarifies the intra-individual dynamic nature of effort and perceived progress. Furthermore, we also find the reciprocal relationship between perceived progress and effort. Second, give that our research setting is startups that involve the pursuit of complex goal (e.g., short-term survival or long-term profit), this study can take account for the roles of time and complex goals into the complex relationship between perceived progress and effort. Third, we use a longitudinal design with multi-source and objectively evaluated secondary data to avoid potential statistical bias.

Key words

complex goal / perceived progress / effort / latent difference score model

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A Dynamic Model of the Longitudinal Relationship between Perceived progress and Effort in Complex Goal Realization Process:A Latent Change Score Approach[J]. Journal of Psychological Science. 2021, 44(3): 522-529
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