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The rising number of food recalls has raised concerns about complexity, globalization and weak governance in the food supply chain. This paper aims to investigate the recall of plant-based products with data from the US Food and Drug Administration.

Introducing the structural topic modeling method allowed us to test theories on recall in the context of sustainable food consumption, enhancing the understanding of food recall processes. This approach helps identify latent topics of product recalls and their interwoven relationships with various stakeholders.

The results answer a standing research call for empirical investigation in a nascent food industry to identify stakeholders’ engagements for food safety crisis management for corporate social responsibility practices. This finding provides novel insights on managing threats to food safety at an industry level to extend existing antecedents and consequences of product recall at a micro level.

For practitioners, this empirical finding may provide insights into stakeholder management and develop evidence-based strategies to prevent threats to food safety. For public policymakers, this analysis may help identify patterns of recalls and assist guidelines and alarm systems (e.g. EU’s Rapid Alert System for Food and Feed) on threats in the food supply chain.

Two detected clusters, such as opportunisms of market actors in the plant-based food system and food culture, from the analysis help understand corporate social responsibility and food safety in the plant-based food industry.

This study investigates whether a firm that has experienced an environmental accident (EA) is less likely to conduct a product recall. If true, it would indicate that EAs tempt firms to hide operational problems that need to be revealed. The logic is that both events are operational failures that damage a firm's reputation and share price. Following an EA, a firm may avoid a discretionary product recall to avoid providing additional evidence of operational incapability and social irresponsibility and thereby triggering amplified reputational and market penalties.

The dataset is compiled from several public and private sources and includes 4,355 product recalls, 153 EAs and 120 firms from the industries that often recall products, including automotive, pharma, medical device, food and consumer products. The study timeframe is 2002–2013. Empirical models are evaluated using hazard modeling.

Results show that EAs reduce the probability of a product recall by 32%, on average. Effect sizes are larger when accidents are more frequent or more severe and when recalls are less severe. Through post hoc analyses, the study finds support for the proposed mechanism that firms avoid recalls due to reputational concerns, provides evidence that EAs can have a lengthy impact on recall behavior, and shows that firms are more likely to avoid recalls managed by the CPSC and NHTSA than recalls managed by the FDA.

Prior studies in operations management (OM) have not examined the impact of one negative event on another. This study finds that EAs tempt firms to hide operational problems that need to be revealed. While recalling fewer defective products is of concern to consumers and regulators, should EAs influence a broader set of discretionary operational decisions, such as closing/relocating a production facility, outsourcing production or conducting a layoff, study implications increase significantly.

This study examines the effect of stable institutional investors on firms' product quality failures. Furthermore, the authors investigate the channels through which institutional ownership stability enhances product quality management.

This study uses probit, ordered probit and negative binomial regression frameworks to investigate the research questions. In addition, the authors utilize the three-stage least-squares to address the endogeneity issues.

Using a sample of product recall incidents from 2012 to 2021, the authors find that firms with more stable institutional ownership have a lower probability, frequency and severity of recall incidents and adopt a proactive product recall strategy. Institutional investors with significant and persistent holdings improve quality management by reducing overinvestment and the use of option-linked and relative performance executive compensations. Furthermore, the influence of stable institutional owners on product quality failures is more pronounced in firms with low managerial ability and specialist CEOs. Lastly, the empirical evidence demonstrates that stable holdings by active investors have a more substantial impact on reducing product recalls than passive and other stable institutional holdings.

This study is the first to examine the impact of institutional ownership stability on firms' product recalls. The authors contribute to the literature on the benefits of stable institutional ownership on firm outcomes and the determinants of product quality failures.

The purpose of this study was to explore potential witnesses' memories for a day that was experienced an unremarkable. There may be instances in an investigation in which all leads have been exhausted, and investigators use a broad appeal for witnesses who may have witnessed something important. Investigators can benefit from knowing the types of information that may be recalled in such circumstances, as well as identifying specific methods that are effective in eliciting useful information.

The present study explored how the delay to recall and recall method influenced the recollection of a seemingly unremarkable day that later became important. Participants were asked to recall an experienced event that occurred either recently (a few weeks prior) or in the distant past (a year prior). Participants recalled via either a written method, in-person individual-spoken or collaborative-spoken interviews.

Results suggest an independent benefit for individual-spoken in-person recall (compared to written or collaborative-spoken recall) and recall undertaken closely after an event (compared to delayed recall). Both individual-spoken interviews as well as more recent recollection resulted in a greater number of overall details recalled. The authors further examined the types of details recalled that might be important to progressing an investigation (e.g. other witnesses and records).

The present work provides important implications for interviewing witnesses about a seemingly unremarkable event that later became important.

The impact of various factors on how TV sports audiences perceive sport event sponsors’ billboards around sports facilities has been the subject of extensive research. Despite numerous factors that impact the effectiveness of sponsor signage at sporting events, there has been a lack of research regarding the language used for such signage around sports facilities’ billboards. Therefore, this study aims to investigate the effects of billboard advertisement language on TV sports audiences’ recognition, recall and search intention to sponsor signage.

This study employed an online experimental design. Participants (n = 925) were recruited from two linguistically different regions: Chinese and English. Participants were randomly assigned to one of two conditions: watching tennis video matches with billboard advertisements presented in either the Roman alphabet exclusively or in a combination of the Roman alphabet and Chinese characters.

This study revealed that although language cannot significantly impact audiences’ unaided recall of a brand, it does have a discernible effect on brand recognition and search intention among audiences. Additionally, people are more likely to search for brands in their native language. Participants from various regions tend to have different recognition rates and search intentions for sport sponsors.

This is the first manuscript examining the use of different languages in relation to audiences’ recognition and recall of sports sponsorship. It provides empirical evidence of the importance of carefully considering the language used in sponsor signage around stadium billboards to optimize the efficacy of sponsorships at sports events.

The purpose of this paper is to investigate how gamification in advertising affects the effectiveness of advertising on social media.

Drawing from the gamification literature, immersion, achievement and social interaction features were identified as features, and advertising effectiveness factors were brand attention, brand liking and recall. A questionnaire was used for collecting data, and a structural equation modeling approach was applied to examine the model.

The results indicated that immersion, achievement and social interaction features affect advertising effectiveness. Furthermore, advertising effectiveness factors had a significant effect on purchase intentions.

The study contributes to the combination of gamification in advertising by offering characteristics for gamification that can enhance advertising effectiveness through brand attention, liking and recall. Finally, it provides managerial guidance on how they can use gamification in their advertising process.

This paper aims to explore the opinions of business owners in an industrial area of Abu Dhabi that could be potentially turned into an art tourism destination.

By mobilizing the concept of “gentrification aesthetics,” the authors use a recall technique to explore support toward art from business owners, regression analyses to understand how the type and content of art predicts gentrification support and chi-square to research the differences between respondents who support the area to become a creative place and those who do not.

A model that explains the connection between gentrification aesthetics and art tourism is presented.

The authors’ proposed model results from testing the possibilities for expanding art tourism specifically and may not apply to other types of tourism. Future research is needed to understand whether and how the model can be applied to other forms of tourist consumption.

The current research presents a case study on how tourism can be strategically expanded into more rural places in a city.

The authors found significant differences between respondents who would like to see Mussafah becoming a creative place in five years and those who believe Mussafah needs to be(come) something else.

While work on tourism gentrification has been conducted, the nexus between gentrification aesthetics and art tourism cannot be found. Their relation can help to expend (art) tourism from busy cultural attractions to industrial areas. The present research fills this gap.

The purpose of this research is to provide a framework in which new data quality dimensions are defined. The new dimensions provide new metrics for the assessment of lecture video indexing. As lecture video indexing involves various steps, the proposed framework containing new dimensions, introduces new integrated approach for evaluating an indexing method or algorithm from the beginning to the end.

The emphasis in this study is on the fifth step of design science research methodology (DSRM), known as evaluation. That is, the methods that are developed in the field of lecture video indexing as an artifact, should be evaluated from different aspects. In this research, nine dimensions of data quality including accuracy, value-added, relevancy, completeness, appropriate amount of data, concise, consistency, interpretability and accessibility have been redefined based on previous studies and nominal group technique (NGT).

The proposed dimensions are implemented as new metrics to evaluate a newly developed lecture video indexing algorithm, LVTIA and numerical values have been obtained based on the proposed definitions for each dimension. In addition, the new dimensions are compared with each other in terms of various aspects. The comparison shows that each dimension that is used for assessing lecture video indexing, is able to reflect a different weakness or strength of an indexing method or algorithm.

Despite development of different methods for indexing lecture videos, the issue of data quality and its various dimensions have not been studied. Since data with low quality can affect the process of scientific lecture video indexing, the issue of data quality in this process requires special attention.

This study aims to highlight the inconsistency between conventional knowledge push judgements and the price of knowledge push. Also, a three-way decision-based relevant knowledge push algorithm was proposed.

Using a ratio of 80–20%, the experiment randomly splits the data into a training set and a test set. Each video is used as a knowledge unit (structure) in the research, and the category is used as a knowledge attribute. The limit is then determined using the user’s overall rating. To calculate the pertinent information obtained through experiments, the fusion coefficient is needed. The impact of the push model is then examined in comparison to the conventional push model. In the experiment, relevant knowledge is compared using three push models, two push models based on conventional International classification functioning (ICF), and three push models based on traditional ICF. The average push cost accuracy rate, recall rate and coverage rate are metrics used to assess the push effect.

The three-way knowledge push models perform better on average than the other push models in this research in terms of push cost, accuracy rate and recall rate. However, the three-way knowledge push models suggested in this study have a lower coverage rate than the two-way push model. So three-way knowledge push models condense the knowledge push and forfeit a particular coverage rate. As a result, improving knowledge results in higher accuracy rates and lower push costs.

This research has practical ramifications for the quick expansion of knowledge and its hegemonic status in value creation as the main methodology for knowledge services.

To the best of the authors’ knowledge, this is the first theory developed on the three-way decision-making process of knowledge push services to increase organizational effectiveness and efficiency.

This study aims to propose a novel deep learning (DL)-based framework, iRelevancy, for identifying the disaster relevancy of a social media (SM) message.

It is worth mentioning that a fusion-based DL model is introduced to objectively identify the relevancy of a SM message to the disaster. The proposed system is evaluated with cyclone Fani data and compared with state-of-the-art DL models and the recent relevant studies. The performance of the experiments is assessed by the accuracy, precision, recall, f1-score, area under receiver operating curve and precision–recall curve score.

The iRelevancy leads to a better performance in accuracy, precision, recall, F-score, the area under receiver operating characteristic and area under precision-recall curve, compared to other state-of-the-art methods in the literature.

The predictive performance of the proposed model is illustrated with experimental results on cyclone Fani data, along with misclassifications. Further, to analyze the performance of the iRelevancy, the results on other cyclonic disasters, i.e. cyclone Titli, cyclone Amphan and cyclone Nisarga are presented. In addition, the framework is implemented on catastrophic events of different natures, i.e. COVID-19. The research study can assist disaster managers in effectively maneuvering disasters during distress.