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The purpose of this paper is to examine the extent to which cultural differences and slogan meaning type affect the role of comprehension in attitude toward the ad (A_ad) and attitude toward the brand (A_brand) formation.

In an online experiment, a total of 256 adult participants from the USA (ranged in age from 19 to 26 years old) and 184 participants from France (ranged in age from 18 to 28) were randomly assigned to one of the two conditions (slogan: single meaning vs polysemous) in a between-subjects experimental design. After getting exposed to the ad, participants responded to questions related to their A_ad, A_brand, comprehension, uncertainty avoidance and demographics.

Results from this research demonstrate the moderating effect of uncertainty avoidance and slogan type (single meaning vs polysemous) on the relationship between comprehension and A_ad. The authors show that for polysemous (and not single meaning) slogans, comprehension results in more favorable A_ad for low uncertainty avoidance individuals than for high uncertainty avoidance individuals. In addition, the authors demonstrate the mediating effect of A_ad in the relationship between comprehension and A_brand.

The authors used nationality as a proxy for culture. Future research should include other cultural dimensions in the development of conceptual models and analysis of data. Another limitation is that the authors used a college student sample for this research. A more representative sample should be used in future research to examine cultural differences in interpreting adverting messages. One other limitation concerns the measurement tool the authors used to measure objective versus subjective comprehension in this research. While the theoretical foundations of the two modes of comprehension are clear and robust, improved measurement tools can enhance the validity and reliability of future research. Finally, the authors suggest that future research examine the effect of such variables as figure-ground contrast, figure attractiveness, stimulus repetition, prototypicality, symmetry and semantic or visual priming that may impact the processing of brand slogans.

This study argues that the processing of brand slogans in advertising is impacted by culture. Individuals from different cultures perceive and comprehend brand slogans differently. This study contributes to the research stream that examines the influence of cultural dimensions on the effectiveness of advertising by focusing more precisely on the impact of uncertainty avoidance (one of Hofstede’s cultural dimensions). In the case of single meaning slogans, advertisers might diminish the use of objective comprehension advertising strategies to influence both individuals with high and low uncertainty avoidance. In the case of polysemous slogans, advertisers should consider that consumers with high uncertainty avoidance (vs low uncertainty avoidance) are impacted more by subjective comprehension (vs objective comprehension) when forming A_ad and A_brand.

This research contributes meaningfully to the marketing literature by examining previous work on ad slogan processing through subjective vs objective comprehension and extending the analysis by incorporating culture as an important factor.

The purpose of this paper is to examine the interesting but largely unexamined impact of self-uncertainty on the persuasiveness of self-deprecating advertisement.

In the present research, the experimental design and survey methods are used to collect data. Furthermore, the ANOVA and bootstrap analysis methods are adopted to verify whether a self-deprecating advertisement is more persuasive for consumers experiencing self-uncertainty and explore the mediating role of self-verification.

Study 1 indicates that people experiencing self-uncertainty are more likely to engage in actual self-verification. Study 2 demonstrates that consumers experiencing self-uncertainty are more likely to purchase products in a self-deprecating advertisement (vs. self-enhancing advertisement), and actual self-verification motive underlies this effect. In Study 3, a novel boundary condition for the main effect–product type (hedonic vs. utilitarian) is found, and it further reveals that the impact of self-uncertainty on the persuasiveness of self-deprecating advertisement will attenuate when the advertised product is utilitarian.

This research reveals that self-deprecating advertising is more desirable for consumers who experience self-uncertainty. Based on the conclusions in this paper, the self-deprecating advertising is more attractive and desirable for consumers who are reminded about their personal uncertainties. Thus, marketers could employ self-deprecating (vs. self-enhancing) advertisement to promote products. For example, in order to promote the waterproof function of iPhone 12, Apple China released a self-deprecating advertisement of “Splash proof and water resistant. Don't worry, iPhone.”

First, this research not only sheds new light on the relationship between self-uncertainty and the persuasiveness of self-deprecating advertisement but also verifies the mediating role of self-verification motive in this relationship. Moreover, this research reveals that self-uncertainty is a significant factor in how people react to the self-deprecating advertisement. It is noteworthy that the self-uncertainty effect is more likely to be found when the advertised product is related to hedonic or experiential consumption as opposed to utilitarian consumption.

This paper investigates a problem in a reverse logistics (RLs) network to decide whether to dispose of unsold goods in primary stores or re-commercialize them in outlet centers. By deducting the costs associated with each policy from its revenue, this study aims to maximize the profit from managing unsold goods.

A new mixed-integer linear programming model has been developed to address the problem, which considers the selling prices of products in primary and secondary stores and the costs of transportation, cross-docking and returning unwanted items. As a result of uncertain nature of the cost and time parameters, gray numbers are used to deal with it. In addition, an innovative uncertain solution approach for gray programming problems is presented that considers objective function satisfaction level as an indicator of optimism.

According to the results, higher costs, including transportation, cross-docking and return costs, make sending goods to outlet centers unprofitable and more goods are disposed of in primary stores. Prices in primary and secondary stores heavily influence the number of discarded goods. Higher prices in primary stores result in more disposed of goods, while higher prices in secondary stores result in fewer. As a result of the proposed method, the objective function satisfaction level can be viewed as a measure of optimism.

An integral contribution of this study is developing a new mixed-integer linear programming model for selecting the appropriate goods for re-commercialization and choosing the best outlet center based on the products' price and total profit. Another novelty of the proposed model is considering the matching percentage of boxes with secondary stores’ desired product lists and the probability of returning goods due to non-compliance with delivery dates. Moreover, a new uncertain solution approach is developed to solve mathematical programming problems with gray parameters.

This study demonstrates how individual paradigms implicate the questions asked, methods used and results drawn in association with a common object of study in human information behavior (HIB) research – the relationship between uncertainty and decision-making.

The author uses textual case studies to examine uncertainty and decision-making through the framework of four paradigms used in HIB research: positivism, cognitivism, collectivism and constructionism and suggests deconstructionism as a paradigm which raises new questions around this topic.

Positivistic approaches to uncertainty are often systems oriented; cognitive approaches are often user-oriented; collectivist approaches are intersubjective; and constructionist approaches blend a subjective and intersubjective research orientation. Deconstructionism raises new questions around ethics and responsibility in relation to decision-making, and the author therefore situates it as a new paradigmatic approach for this topic in HIB research.

Despite the presence of research aimed at recognizing and defining paradigms in HIB research, a comparative micro-examination of how individual paradigms implicate a specific research topic has yet to be conducted. Each paradigm uniquely shapes the ways in which uncertainty and decision-making are characterized, but the four central ones examined here have thus far left out questions of ethics and responsibility as being core elements of decision-making as tied to uncertainty. Therefore, this paper introduces deconstructionism as a paradigm new to HIB uncertainty research, arguing that it provides an important and novel complication of existent research questions and approaches.

We aim to clarify the effect of economic uncertainty on Chinese stock market fluctuations. We extend the understanding of the asymmetric connectedness between economic uncertainty and stock market risk and provide different characteristics of spillovers from economic uncertainty to both upside and downside risk. Furthermore, we aim to provide the different impact patterns of stock market volatility following several exogenous shocks.

We construct a Chinese economic uncertainty index using a Factor-Augmented Variable Auto-Regressive Stochastic Volatility (FAVAR-SV) model for high-dimensional data. We then examine the asymmetric impact of realized volatility and economic uncertainty on the long-term volatility components of the stock market through the asymmetric Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling (GARCH-MIDAS) model.

Negative news, including negative return-related volatility and higher economic uncertainty, has a greater impact on the long-term volatility components than positive news. During the financial crisis of 2008, economic uncertainty and realized volatility had a significant impact on long-term volatility components but did not constitute long-term volatility components during the 2015 A-share stock market crash and the 2020 COVID-19 pandemic. The two-factor asymmetric GARCH-MIDAS model outperformed the other two models in terms of explanatory power, fitting ability and out-of-sample forecasting ability for the long-term volatility component.

Many GARCH series models can also combine the GARCH series model with the MIDAS method, including but not limited to Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH). These diverse models may exhibit distinct reactions to economic uncertainty. Consequently, further research should be undertaken to juxtapose alternative models for assessing the stock market response.

Our conclusions have important implications for stakeholders, including policymakers, market regulators and investors, to promote market stability. Understanding the asymmetric shock arising from economic uncertainty on volatility enables market participants to assess the potential repercussions of negative news, engage in timely and effective volatility prediction, implement risk management strategies and offer a reference for financial regulators to preemptively address and mitigate systemic financial risks.

First, in the face of domestic and international uncertainties and challenges, policymakers must increase communication with the market and improve policy transparency to effectively guide market expectations. Second, stock market authorities should improve the basic regulatory system of the capital market and optimize investor structure. Third, investors should gradually shift to long-term value investment concepts and jointly promote market stability.

This study offers a novel perspective on incorporating a Chinese economic uncertainty index constructed by a high-dimensional FAVAR-SV model into the asymmetric GARCH-MIDAS model.

This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

To address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.

Various numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.

Due to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.

This study examined subjective numeracy and its relationship with accounting judgements on probability issues.

A subjective numeracy scale (SNS) questionnaire was distributed to 231 accounting students to measure self-evaluated numeracy. Modified Bayesian reasoning tasks were applied in an accounting-related probability estimation, manipulating presentation formats.

The study revealed a positive relationship between self-evaluated numeracy and performance in accounting probability estimation. The findings suggest that switching the format of probability expressions from percentages to frequencies can improve the performance of participants with low self-evaluated numeracy.

Adding objective numeracy measurements could enhance results. Future numeracy research could add objective numeracy items and assess whether this influences participants' self-perceived numeracy. Based on this sample population of accounting students, the findings may not apply to large populations of accounting-information users.

Investors' ability to exercise sound judgement depends on the accuracy of their probability estimations. Manipulating the format of probability expressions can improve probability estimation performance in investors with low self-evaluated numeracy.

This study identified a significant performance gap among participants in performing accounting probability estimations: those with high self-evaluated numeracy performed better than those with low self-evaluated numeracy. The authors also explored a method other than additional training to improve participants' performance on probability estimation tasks and discovered that frequency formats enhanced the performance of participants with low self-evaluated numeracy.

Advertisements often use fear appeals to encourage prevention focused behaviors. This approach has been somewhat successful in changing attitudes and behaviors, often encouraging consumers to secede from behaviors such as smoking or to adopt preventative behaviors such as engaging in health screenings. However, health-care marketers have been less successful in efforts to reduce obesity. The obesity crisis has led to an abundance of marketing communications designed to influence weight loss. Many of these focus on fear of physical health risks associated with being overweight which have a certain degree of uncertainty surrounding them. This study aims to examine financial threats that have lower perceptions of uncertainty, and the differential impact this type of threat has on elements of the Extended Parallel Process Model (EPPM).

A 2 × 2 experimental design is used to examine the differential impact of messages communicating threat of financial and physical risk on evoked fear, perceived uncertainty, perceived susceptibility, efficacy and intention to lose weight.

Overall results indicate that response to weight loss advertising varies given the type of threat presented. Results indicate that there is a greater level of uncertainty associated with physical health threats than that with financial threats. Moreover, even though individuals were more fearful of and felt more susceptible to physical threats, when they believed that the recommended behavior was feasible, financial threat was more influential.

To encourage weight loss and intentions to lose weight advertising in practice and advertising research primarily focus on the physical health risks associated with being overweight as a motivating factor. Current research explores the impact of financial threats on attitudes and behavioral intention and finds that financial threats are perceived as more certain than physical threats, and the communication of financial threats is more salient in its effect on weight loss intentions. An opportunity for future research is to further explore the impact of uncertainty in relation to components of EPPM and how threats varying in degrees of uncertainty may impact weight loss intentions.

This study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy variations, supported by a case application in the aeronautical sector.

Based on experts' opinions in risk analysis within the aeronautical sector, rules governing the relationship between severity, occurrence, detection and risk factor were defined. This served as input for developing a fuzzyfied FMEA tool using the Matlab Fuzzy Logic Toolbox. The tool was applied to the sealing process in a company within the aeronautical sector, using triangular and trapezoidal membership functions, and the results were compared with the traditional FMEA approach.

The results of the comparative application of traditional FMEA and fuzzyfied FMEA using triangular and trapezoidal functions have yielded valuable insights into risk analysis. The findings indicated that fuzzyfied FMEA maintained coherence with the traditional analysis in identifying higher-risk effects, aligning with the prioritization of critical failure modes. Additionally, fuzzyfied FMEA allowed for a more refined prioritization by accounting for variations in each variable through fuzzy rules, thereby improving the accuracy of risk analysis and providing a more realistic representation of potential hazards. The application of the developed fuzzyfied FMEA approach showed promise in enhancing risk assessment in the aeronautical sector by considering uncertainties and offering a more detailed and context-specific analysis compared to conventional FMEA.

This study emphasizes the potential of fuzzyfied FMEA in enhancing risk assessment by accurately identifying critical failure modes and providing a more realistic representation of potential hazards. The application case reveals that the proposed tool can be integrated with expert knowledge to improve decision-making processes and risk mitigation strategies within the aeronautical industry. Due to its straightforward approach, this facilitating methodology could also prove beneficial in other industrial sectors.

This paper presents the development and application of a facilitating methodology for implementing Fuzzy FMEA, comparing it with the traditional approach and incorporating variations using triangular and trapezoidal functions. This proposed methodology uses the Toolbox Fuzzy Logic of Matlab to create a fuzzyfied FMEA tool, enabling a more nuanced and context-specific risk analysis by considering uncertainties.

The paper aims to propose an innovative two-stage decision model to address the sustainable-resilient supplier selection and order allocation (SSOA) problem in the single-valued neutrosophic (SVN) environment.

First, the sustainable and resilient performances of suppliers are evaluated by the proposed integrated SVN-base-criterion method (BCM)-an acronym in Portuguese of interactive and multi-criteria decision-making (TODIM) method, with consideration of the uncertainty in the decision-making process. Then, a novel multi-objective optimization model is formulated, and the best sustainable-resilient order allocation solution is found using the U-NSGA-III algorithm and TOPSIS method. Finally, based on a real-life case in the automotive manufacturing industry, experiments are conducted to demonstrate the application of the proposed two-stage decision model.

The paper provides an effective decision tool for the SSOA process in an uncertain environment. The proposed SVN-BCM-TODIM approach can effectively handle the uncertainties from the decision-maker’s confidence degree and incomplete decision information and evaluate suppliers’ performance in different dimensions while avoiding the compensatory effect between criteria. Moreover, the proposed order allocation model proposes an original way to improve sustainable-resilient procurement values.

The paper provides a supplier selection process that can effectively integrate sustainability and resilience evaluation in an uncertain environment and develops a sustainable-resilient procurement optimization model.