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The widespread use of temporal aspects in user modeling indicates their importance, and their consideration showed to be highly effective in various domains related to user modeling, especially in recommender systems. Still, past and ongoing research, spread over several decades, provided multiple ad-hoc solutions, but no common understanding of the issue. There is no standardization and there is often little commonality in considering temporal aspects in different applications. This may ultimately lead to the problem that application developers define ad-hoc solutions for their problems at hand, sometimes missing or neglecting aspects that proved to be effective in similar cases. Therefore, a comprehensive survey of the consideration of temporal aspects in recommender systems is required. In this work, we provide an overview of various time-related aspects, categorize existing research, present a temporal abstraction and point to gaps that require future research. We anticipate this survey will become a reference point for researchers and practitioners alike when considering the potential application of temporal aspects in their personalized applications.

PurposeTo clarify the concept of the amortization period (20-year factor) associated with direct land-use change (dLUC) accounting, discuss its main inconsistencies, and propose improvements. The current practice is to divide (amortize) the estimated emissions associated with dLUC that has occurred over the last 20 years by another 20 years. Both periods are referred ambiguously as “amortization period.” Issues arise when considering them as a single temporal aspect (TA) that cannot fully represent the complexity of diverse research and policy contexts.MethodsFirst, a systematic review was conducted to understand the 20-year amortization history and concepts and discuss its inconsistencies. Based on the review results, we propose the adoption of two distinct TAs, decomposed from the “amortization period.” Then, we performed a sensitivity analysis by estimating carbon emissions due to dLUC in six land uses in Brazil: soybean, maize, sugarcane, pasture, planted forest, and mango.Results and discussionThe literature review shows that several strategies have emerged to reduce or avoid adopting the amortization period. However, most of these proposals are based on complex approaches focusing on alternatives associated with the life cycle impact assessment stage. We found that the commonly adopted amortization period has an ambiguous nature that could be explored at the life cycle inventory analysis stage. Thus, we argue that there are two distinct TAs linked to amortization in dLUC: (i) the inventory period adopted to account for land-use changes; and (ii) the period over which carbon emissions are annualized. These temporal aspects were named here the “LUC-inventory period” (IP) and the “LUC-amortization period” (AP), for clarification purposes. The sensitivity analysis showed that different values of IP and AP drastically change the emissions results due to dLUC in Brazil for different crops and land uses.ConclusionWe advocate that the “amortization period” should be decomposed into two TAs: “LUC-inventory period” and the “LUC-amortization period.” They affect how the carbon debt incurred by expanding agricultural land is accounted for and amortized over a given period-of-time. Therefore, to ensure regulatory compliance, we argued that these proposed TAs should be explicitly defined, based on three possibilities, depending on the goal and context of LCA studies, such as (i) fixed values set in standards and norms; (ii) IPCC’s 20-year defaults; and (iii) customized IP and AP values based on the study’s specificities.

Why do some entrepreneurial ecosystems successfully adjust amid adversity while others languish? By integrating prospect theory into the entrepreneurial ecosystem literature and using a quasi-natural experimental design with a difference-in-difference-in-differences model, our theory and findings reveal that earthquakes reduce entrepreneurship in regions with high household savings, but increase entrepreneurship in regions with low savings, and these between-area differences increase over time. Reconceptualizing the meaning of savings from a resource into a key driver of loss aversion, we thus identify the surprising constraining influence of financial capital in times of adversity, yielding important implications for entrepreneurship research and policymakers. Plain English Summary We find that regions with more household savings generate fewer startups after an earthquake. Thus, regional savings explain post-crisis differences in performance between entrepreneurial ecosystems, which is a surprising constraining influence of financial capital in times of adversity. This has important implications for entrepreneurship research and policymakers who seek to develop supportive policies to encourage entrepreneurship as part of broader economic recovery strategies after crises.

Summary Biotic interactions of plants can have legacy effects mediated by changes in plant traits and soil characteristics. Legacy effects are defined as effects that persist after the causal biotic interaction ceases, because plant traits and soil characteristics are plastic and modifications may be maintained for long time periods. To date, studies on biotic interactions of plants with above‐ and below‐ground organisms and their plant‐mediated interactions have mainly focused on short‐term effects in the continuous presence of interacting organisms. Little is known about how long the changes in plant traits and soil characteristics persist after the biotic interaction ceases and indirectly affect future biotic interactions and community assembly. Further, since some organisms switch between above‐ and below‐ground compartments during ontogeny, impacts on soil‐dwelling larval stages can have direct legacy effects on their above‐ground adult stages and vice versa. Elucidating legacy effects of biotic interactions above and below the ground will provide a deeper insight into a better understanding of the importance of plant trait‐ and soil characteristic‐mediated indirect interactions in shaping community assembly, biodiversity and ecosystem function. Lay Summary

Like many important theories that were originally tested in one domain, construal level theory has broadened the notion of temporal distance to psychological distance and examined the wide ranging implications of this construct on evaluation and behavior. This commentary seeks to take a step back to admire the “forest” that has been created and suggest additional extensions and implications along the different stages of consumer decision making: goal pursuit, evaluation by way of consideration-set formation and receptivity, and finally choice influenced by context, comparability of options, and post-choice happiness and regret.

What is trust? Should trust be used as a variable or as a process? Is trust in people similar in nature to trust in institutions? These are three main questions I address in this article. I argue that trust is a complex and multi-dimensional phenomenon, which consists of a mix of trust in strong ties, weak ties, and institutions. I explain the need for a new approach to trust, using the Soviet Union as an example. I argue that rigid distinctions in social capital theory between high-trust and lowtrust societies fail to account for the complexity of trust. In this article, I view trust as a process. I also suggest a new definition of trust based on the notion of agency, which underscores the idea of temporality and incorporates the roles of the past, present, and future.

Although environmental filtering and spatial structuring are commonly regarded as two key factors shaping community dynamics, their relative contribution remains unknown for numerous aquatic ecosystems, particularly highly dynamic floodplain lakes. This issue is here addressed by examining the seasonal metacommunity dynamics of freshwater fishes in Lake Dongting, a large subtropical lake of the middle Chang-Jiang basin in southern China. Physicochemical variables and fish assemblages were recorded at 20 sampling sites during the wet, normal, and dry seasons. Distance-based redundancy analysis and associated variation partitioning were used to examine the relative role of environmental variables and spatial factors in fish community assembly in each season. Analysis results demonstrated that the relative contribution of environmental filtering and spatial structuring varied depending on environmental features and the extent of hydrological connectivity in different seasons. Intensified physicochemical parameters in the dry season convinced the enhanced environmental filtering, whereas high hydrological connectivity in the wet season favored the stronger spatial process. Specifically, the community assembly processes were temporally dynamic; spatial structuring (or mass effects), resulting from excessively high dispersal rates, was dominant during the flooding season, and environmental filtering was stronger than spatial structuring (or dispersal limitation) during the non-flooding season. These findings highlight the importance of conserving local habitats of Lake Dongting during the dry and normal seasons, and maintaining of the flood pulse of the lake and its natural variability during the wet season. Apparently, the construction of a water-level regulation project at the Chenglingji Channel, the outlet watercourse of Lake Dongting, is not supported because it will change the flood pulse of this lake and thus impact habitat heterogeneity or variability.

In this research we demonstrate an asymmetry between the spatial dimension and the other three dimensions of psychological distance—i.e., the temporal, social, and hypothetical dimensions. The first study shows that a distal prime along the spatial dimension leads to greater perceived distance along the other three dimensions, but not the other way around. We theorize that this is because people understand temporal, social, and hypothetical distance in terms of spatial distance. Hence, symmetric priming effects should occur when similarities between the spatial dimension and other dimensions are highlighted. Indeed, the last three studies, using multiple operationalizations, show that such priming effects could become symmetric when people engage in relational processing.

Knowledge discovery through spatial and temporal aspects of data related to occurrences of events has many applications in digital forensics. Specifically, in electronic surveillance, it is helpful to construct a timeline to analyze information. The existing techniques only analyze the occurrence and co-occurrence of events; however, in general, there are three aspects of events: occurrences (and co-occurrences), nonoccurrences, and uncertainty of occurrences/non-occurrences with respect to spatial and temporal aspects of data. These three aspects of events have to be considered to better analyze periodicity and predict future events. This study focuses on the spatial and temporal aspects given in intuitionistic fuzzy (IF) datasets using the granular computing (GrC) paradigm; formal concept analysis (FCA) was used to understand the granularity of data. The originality of the proposed approach is to discover the periodicity of events data given in IF sets through FCA and the GrC paradigm that helps to predict future events. An experimental evaluation was also performed to understand the applicability of the proposed methodology.

In this work, a novel, dynamic sustainability assessment tool is presented and validated in a case study. This tool combines two methods—system dynamics (SD) and temporal soil carbon modelling. The case study for sustainability analysis of Danish agriculture and green biorefineries supply chains in Denmark is used. The development of the Danish agriculture sector is simulated and assessed in relation to the ecosystem’s carrying capacity until 2050, defined as 1.4 livestock units per hectare. The results show that under the current development, the agriculture sector would exceed this carrying capacity shortly after 2030. The results obtained from the dynamic sustainability assessment tool show a more precise and less optimistic projection of future development than the assessment using constant soil carbon modelling values only. The study, therefore, suggests that the use of the temporal aspects in the sustainability assessment should be included and further developed.