The objective of this study is to conduct a marketing mix modeling to measure the effectiveness of past marketing activities on the product sales using a time-varying effect model (TVEM) approach. The longitudinal intensive data for this study has come from a large ice cream manufacturer in USA. Traditionally, static regression models have been used to measure the effectiveness of marketing mix variables to predict sales. And, these models used to find the time independent effect of the covariate on the dependent variable. On the other hand, a dynamic model such as time-varying effect model takes time into consideration. Researchers can model the changes in the relationship between dependent and independent variables over time using time-varying effect model. This is the first study, where a time-varying effect model approach has been used to measure the effectiveness of marketing mix elements in the ice cream industry. In addition, we have compared the predictive validity of both static and dynamic models using this data set.

Yes / In the context of global climate change threatening human survival, and in a post-pandemic era that advocates for a global green and low-carbon economic recovery, conducting an in-depth analysis to assess whether green f inance can effectively support low-carbon economic development from a dynamic perspective is crucial. Unlike existing research, which focuses solely on the average effects of green credit (GC) on carbon productivity (CP), we introduce a non-parametric panel data model to investigate GC’s impact on CP across 30 provinces in China from 2003 to 2021, verifying a significant time-varying effect. Specifically, during the first phase (2003–2008), GC negatively impacted CP. In the second phase (2009–2014), this negative influence gradually diminished and transformed into a positive effect. In the third phase (2015–2021), GC continued to positively influence CP, although this effect became insignificant during the pandemic. Further subgroup analysis reveals that in the regions with low environmental regulations, GC did not significantly boost CP throughout the sample period. In contrast, in the regions with high environmental regulations, GC’s positive effect persisted in the mid to late stages of the sample period. Additionally, compared to the regions with low levels of marketization, the impact of GC on CP was more pronounced in highly marketized regions. This indicates that the promoting effect of GC on CP depends on strong support from environmental regulations and well-functioning market mechanisms. By adopting a non-parametric approach, this study reveals variations in the impact of GC on CP across different stages and under the influence of the pandemic shock, offering new insights into the relationship between GC and China’s CP. / The full-text of this article will be released for public view at the end of the publisher embargo on 15 May 2025.

<p>  </p> <p>Dyadic play interactions are a cornerstone of early development and difficulty engaging in sustained synchronous interactions are linked to later difficulties with language and joint attention. For children at elevated risk for autism spectrum disorder (ASD), it is unclear if early difficulties in synchronous exchanges could inform later diagnoses. As part of a prospective monitoring study, infant siblings of children with ASD (high-risk group) or typical development (low-risk group), and their mothers completed a standardized play task. Play interactions for infants were evaluated to: (1) assess if early difficulties with social responsiveness or synchrony proceed ASD diagnoses within the first year; (2) explore whether repertoires of observed synchronous behaviors distinguish ASD-risk; and (3) examine whether the unfolding rates of synchrony and responsiveness over continuous time highlight ASD-risk differences. </p> <p><br></p> <p>By 12 months, distinct mean-level differences in synchrony and responsiveness by risk status were observed. Higher synchrony and responsiveness totals were also positively associated with infants later language and cognitive scores and negatively associated with ASD symptom severity (Chapter 2). Although, dyads utilized mostly comparable repertoires of observed synchronous and responsive behaviors, regardless of group membership (Chapter 3). And lastly, the overall rates of unfolding synchrony and responsiveness were fairly stable throughout the interaction. However, distinct patterns by ASD-risk and developmental outcomes were evident (Chapter 4). Ultimately, the encompassed studies did not consistently find robust ASD-specific differences. However, these studies did demonstrate the applicability of advanced methodologies to provide relevant contextual/dyadic elements (beyond the field’s norm of mean-level totals), particularly for infants with non-autism developmental concerns. Future research should build upon these studies to assess synchrony and responsiveness growth curves that extend beyond 12 months of age, as well as utilize behavioral coding approaches that systematically capture both synchronous and asynchronous exchanges.</p>