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Phytophagous insects use a wide range of indicators or associated cues to avoid laying eggs in sites where offspring survival is low. For insects that lay eggs in flowers, these unsuitable sites may be created by the host plant's resource allocation to flowers. In the sequentially flowering host plant, Yucca glauca, late‐opening distal flowers are more likely to be aborted in the presence of already‐initiated basal fruits because they are strong resource sinks. If flowers are aborted, all eggs of the phytophagous insect, Tegeticula yuccasella, within the flower die. We used the phytophagous insect T. yuccasella that lays eggs in and pollinates host plant Y. glauca flowers to test the hypothesis that phytophagous insect females are less likely to invest eggs in host plant flowers if basal fruits are present because they are more likely to be aborted. We also investigated potential predictors of arrival of T. yuccasella at inflorescences at the onset of flowering. These factors may influence a phytophagous insect's decisions to select oviposition sites. We carried out a behavioral experiment using wild‐caught T. yuccasella females on manipulated inflorescences with distal flowers with basal fruits and without fruits. As potential predictors of T. yuccasella arriving at inflorescences, we used floral display size and day of onset of flowering. In support of our hypothesis, our experimental results showed that T. yuccasella was significantly less likely to oviposit in distal flowers on inflorescences with basal fruits. We also found that T. yuccasella arrival was higher at inflorescences with larger floral display size and earlier in the flowering season. These findings uncover a novel indicator of unsuitable oviposition sites—the presence of basal fruits, that phytophagous insects use to make oviposition decisions. Further, our study contributes to the growing body of evidence that shows that females prefer sites that increase the probability of survival of their offspring. This study showed for the first time that the presence of fruits in sequentially flowering plants reduces the probability of Tegeticula yuccasella females laying eggs in flowers. Fruits constitute strong resource sinks and as a result flowers above these resource sinks are more likely to be aborted. As all T. yuccasella eggs in aborted flowers die, it is highly adaptive to avoid ovipositing in flower when fruits are present.

A major goal in marine ecology is to understand patterns of larval dispersal and population connectivity. Dispersal plasticity allows for adaptive variation in dispersal phenotypes in response to variation in environmental conditions and may help to explain intraspecific variation in dispersal distances. However, this phenomenon has only been hypothesized for marine fishes. Here, we test the hypothesis that parents produce larvae with different dispersal‐related traits in response to variation in environmental quality using the orange anemonefish, Amphiprion percula. By manipulating food rations in a crossover experimental design, we show that parents produce larger offspring on low‐food rations than on high‐food rations. However, there was no effect of parental diet on larval critical swimming speed. We also show that parents produce larvae with smaller otolith cores while on low‐food rations, which, in combination with parentage analyses, may provide a way to test the dispersal plasticity hypothesis in the field. This study shows that parents can produce different larval phenotypes in response to variation in environmental conditions, demonstrating plasticity in a dispersal‐related larval trait that may help to explain observed variation in A. percula larval dispersal distances. Incorporating dispersal plasticity into our understanding of marine dispersal patterns may enhance our understanding of marine metapopulation ecology, fisheries management, and conservation. In this study, we investigate whether dispersal‐related larval traits are plastic in response to parental habitat quality in a marine fish: the clown anemonefish, Amphiprion percula. Results from this study show that parents can produce different larval dispersal‐related phenotypes in response to variation in food rations, which may explain some of the observed variation in A. percula larval dispersal distances.

Resource selection is widely appreciated to be context‐dependent and shaped by both biological and abiotic factors. However, few studies have empirically assessed the extent to which selective foraging behaviour is dynamic and varies in response to environmental conditions for free‐ranging animal populations. Here, we assessed the extent that forage selection fluctuated in response to different environmental conditions for a free‐ranging herbivore, moose (Alces alces), in Isle Royale National Park, over a 10‐year period. More precisely, we assessed how moose selection for coniferous versus deciduous forage in winter varied between geographic regions and in relation to (a) the relative frequency of forage types in the environment (e.g. frequency‐dependent foraging behaviour), (b) moose abundance, (c) predation rate (by grey wolves) and (d) snow depth. These factors are potentially important for their influence on the energetics of foraging. We also built a series of food‐chain models to assess the influence of dynamic foraging strategies on the stability of food webs. Our analysis indicates that moose exhibited negative frequency dependence, by selectively exploiting rare resources. Frequency‐dependent foraging was further mediated by density‐dependent processes, which are likely to be predation, moose abundance or some combination of both. In particular, frequency dependence was weaker in years when predation risk was high (i.e. when the ratio of moose to wolves was relatively low). Selection for conifers was also slightly weaker during deep snow years. The food‐chain analysis indicates that the type of frequency‐dependent foraging strategy exhibited by herbivores had important consequences for the stability of ecological communities. In particular, the dynamic foraging strategy that we observed in the empirical analysis (i.e. negative frequency dependence being mediated by density‐dependent processes) was associated with more stable food web dynamics compared to fixed foraging strategies. The results of this study indicated that forage selection is a complex ecological process, varying in response to both biological (predation and moose density) and abiotic factors (snow depth) and over relatively small spatial scales (between regions). This study also provides a useful framework for assessing the influence of other aspects of foraging behaviour on the stability of food web dynamics. The study presents evidence suggesting that the type of frequency‐dependent foraging strategy exhibited by herbivores had important consequences for the stability of ecological communities.

Context-aware recommender systems have been widely investigated in both academia and industry because they can make recommendations based on a user’s current context (e.g., location, time). However, most existing context-aware techniques only use contextual information at the item level when modeling users’ preferences, i.e., contextual information that correlates with users’ overall evaluations of items such as ratings. Few studies have attempted to detect more fine-grained contextual preferences at the level of item aspects (e.g., a hotel’s “location”, “food quality”, and “service”). In this study, we use contextual weighting strategies to derive users’ aspect-level context-dependent preferences from user-generated textual reviews. The inferred context-dependent preferences are then combined with users’ context-independent preferences that are also inferred from reviews to reflect their stable requirements over time. To automatically incorporate both types of user preferences into the recommendation process, we propose a linear-regression-based algorithm that uses a stochastic gradient descent learning procedure. We tested the proposed recommendation algorithm with two real-life service datasets (one with hotel review data and the other with restaurant review data) and compared its contribution with three previously suggested approaches: one that does not consider contextual information; one that uses contextual information to pre-filter rating data before applying the recommendation algorithm; and one that generates recommendations according to users’ aspect-level contextual preferences. The experiment results demonstrate that our approach outperforms the others in terms of recommendation accuracy.

PurposeThis study intends to analyze the relationship between the digital maturity of SMEs and intellectual capital, investigating the determining factors. Starting from the endowment in terms of intellectual capital and evaluating Management Style, Decision-Making Competences, and Business Network, a model is proposed aiming to provide a comprehensive measure of SMEs’ digital maturity and thus to improve understanding and, consequently, effectiveness. The empirical analysis allows assessing the validity and applicability of the suggested model, providing valuable insights for the improvement of digital strategy and competitiveness of SMEs in the Amalfi Coast Tourist District (Italy), with evident implications also for policymakers and the community.Design/methodology/approachA mixed-methods research strategy was utilized to confirm research hypotheses that were derived from literature review. The field study was organized into two separate phases: the first phase, which is qualitative, employed focus groups comprising key stakeholders (managers and entrepreneurs) from various companies within the Amalfi Coast Tourist District. This phase adhered to the principles of homogeneity (to facilitate deeper discussions) and heterogeneity (to allow for a broader range of viewpoints among participants). The insights gathered from these preliminary focus groups informed the subsequent quantitative phase. In this second phase, structured interviews were conducted using a questionnaire to probe the participants’ views on digital maturity. This analysis involved 94 companies, all part of the Amalfi Coast Tourist District, assessing their digitalization levels and highlighting key management attributes. Logistic regression was applied to quantitatively analyze the data, effectively assessing the impact of various independent variables (such as Management Style, Decision-Making Competencies and Business Network) on the dependent variable, digital maturity. Employing both qualitative and quantitative methods provides a thorough and nuanced understanding of the digital maturity landscape within the specified context.FindingsThe main results suggest the existence of a correlation between the analyzed variables and digital maturity. Innovation, indeed, increases by applying a data-driven leadership style. Intellectual capital (measured in its three components of human capital: decision-making competences; structural capital: management style; and relational capital: business network) influences digital maturity, although some of the variables used are not equally weighted.Originality/valueThe main contribution of this article is to provide an in-depth understanding of the company components that favor digital maturity, to support strategic choices oriented towards a conscious digital transition. The results enrich the existing literature on intellectual capital in terms of its contribution to the digitalization of organizations, which can be a critical success factor in the context of SMEs.

In the prior literature on performance measurement of firms with fixed-sum outputs, an equilibrium-efficient frontier is constructed. This paper shows that a single equilibrium-efficient frontier needs a significant trade-off between efficient and inefficient firms, and this may be impossible in practical applications. We develop a data envelopment analysis (DEA) model to construct multiple equilibrium-efficient frontiers in the presence of fixed-sum outputs. The approach uses context-dependent DEA that refers to a DEA approach where a set of firms are assessed against a particular assessment context. Numerical examples are used to illustrate the applicability of the approach.

Background IMPROVE aims to conduct a hybrid type 3 evaluation design to test the effectiveness of bundled implementation strategies on intervention fidelity of the Healthy School Start (HSS) program, while simultaneously monitoring effects on health outcomes of children and parents. The HSS is a 4-component family support program for children starting school (5–7 years of age) promoting healthy dietary habits and physical activity in the home environment to prevent childhood obesity and parents’ risk of developing type 2 diabetes. Methods IMPROVE is a cluster-randomized controlled trial with two arms to evaluate and compare the effects of two different bundles of implementation strategies on intervention fidelity expressed as adherence and responsiveness at 12 and 24 months (primary outcomes). Thirty schools in two municipalities will participate in the study reaching about 1400 families per school year. In stakeholder workshops, key implementation determinants were identified according to the domains of the Consolidated Framework for Implementation Research. Through a consensus process with stakeholders, two bundles of implementation strategies were tailored to address context-specific determinants. Schools randomly assigned to group 1 will receive bundle 1 (Basic) and group 2 will receive bundle 1 + 2 (Enhanced). Bundle 2 consists of external facilitation, fidelity monitoring and feedback strategies. Secondary outcomes will include change in acceptability, appropriateness, feasibility, and organisational readiness as perceived by school staff. In addition, child weight status and diet, and parents’ feeding practices and risk of type 2 diabetes will be monitored. Linear and ordinal regression analysis will be used to test the effect on the primary and secondary outcomes, taking clustering and covariates into consideration where needed. Process evaluation will be conducted through key stakeholder interviews to investigate experiences of the program and perceptions on sustainability. Discussion This systematic approach to investigating the effectiveness of two different bundles of implementation strategies tailored to context-specific determinants on the fidelity of the HSS intervention will provide new insight into feasible implementation strategies and external support needed for the HSS to be effective and sustainable. Results will help inform how to bridge the gap between the research on school-based health programs and routine practice in schools. Trial registration Registered prospectively at ClinicalTrials.gov ID: NCT04984421 , registered July 30, 2021

Evidence shows that marketers can direct consumers’ limited attention to specific product attributes by making them “prominent.” This research asks: How should firms decide which attribute to make prominent in competitive environments? A key feature of this setting is that consumers’ preferences are context-dependent and that a firm’s choice of an attribute affects the evaluation of all products in the category. We develop a model in which firms selectively promote one of two attributes (e.g., image or performance) before competing in price. We find when consumers evaluate both attributes, perceived differentiation within an attribute can become diluted; we call this the dilution effect . This implies that making the same attribute prominent can arise in equilibrium. Only if there is a sufficient quality advantage in an attribute do we find equilibria with firms making different attributes prominent. We also show how the dilution effect can be a disincentive for investments in quality improvements. Data and the online appendix are available at https://doi.org/10.1287/mksc.2017.1037 .

Disruptive innovations introduce a new performance dimension into a product category, but often suffer from inferior performance on key performance dimensions of their existing substitutes. Hence, the followers of these innovations face an important decision to make: they must choose to improve the new technology either on the key performance dimension shared with the old technology or on the new performance dimension. This paper investigates which path firms should choose when they face such a dilemma in the absence of any cost or capability issues. In doing so, we integrate customer response into the theory of technological evolution and allow preferences on the product choices to be context dependent. We show that context-dependent preferences may encourage the follower to improve the new technology on the new performance dimension. Later, we extend our game to a dynamic one and show that the context-dependent preferences may cause the pioneer to innovate less. This paper was accepted by J. Miguel Villas-Boas, marketing.

The concepts and implementation of flipped education have been prevailing globally. However, most studies focus on learning performance with few analyses on moderator variables. The study conducted a meta-analysis to analyze 39 studies published over the 2012–2018 period. Among the 39 studies involving 4662 participants, 33 of the studies analyzed the dependent variable of learning performance, and 6 of the studies analyzed the other dependent variable of higher-order thinking. To further examine the effects, four moderators—education level, scaffolding, subject area, and country, were analyzed to investigate the various effects on learning performance. Overall, flipped education demonstrated a low effect size of 0.31 for learning performance, and a moderate effect size of 0.53 for higher-order thinking. The in-depth results and syntheses of the four moderators and two dependent variables and their implications are discussed.