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Scholarly communications, particularly, questions and answers (Q&A) present on digital scholarly platforms provide a new avenue to gain knowledge. However, several studies have raised a concern about the content anomalies in these Q&A and suggested a proper validation before utilizing them in scholarly applications such as influence analysis and content-based recommendation systems. The content anomalies are referred as disinformation in this research. The purpose of this research is firstly, to assess scholarly communications in order to identify disinformation and secondly, to help scholarly platforms determine the scholars who probably disseminate such disinformation. These scholars are referred as the probable sources of disinformation.

To identify disinformation, the proposed model deduces (1) content redundancy and contextual redundancy in questions (2) contextual nonrelevance in answers with respect to the questions and (3) quality of answers with respect to the expertise of the answering scholars. Then, the model determines the probable sources of disinformation using the statistical analysis.

The model is evaluated on ResearchGate (RG) data. Results suggest that the model efficiently identifies disinformation from scholarly communications and accurately detects the probable sources of disinformation.

Different platforms with communication portals can use this model as a regulatory mechanism to restrict the prorogation of disinformation. Scholarly platforms can use this model to generate an accurate influence assessment mechanism and also relevant recommendations for their scholars.

The existing studies majorly deal with validating the answers using statistical measures. The proposed model focuses on questions as well as answers and performs a contextual analysis using an advanced word embedding technique.

This paper aims to explore the relationship between prudence in risk attitudes and patience of time preference of Chinese apple growers regarding off-farm cold storage of production and marketing in non-harvest seasons. The authors also consider the effect of farmer participation in cooperative-like organizations known as Farm Bases (FBs).

The authors use multiple list methods and elicitation strategies to measure Chinese apple farmers' risk attitudes and time preferences. Because these farmers can either sell their apples immediately to supermarkets or intermediaries or place them in storage, the authors assess correlations between their storage decisions and their preferences regarding risk and time. The authors also differentiate risks involving gains and losses and empirically examine individual risk attitudes in different scenarios.

Marketing decisions are moderately associated with risk attitudes but not time preference. Farmers with memberships in local farmer cooperatives are likely to speculate more in cold storage. Thus, risk aversion behavioral and psychological motives affect farmers' decision-making of cold storage and intertemporal marketing activities. However, membership in cooperatives does not always result in improved income and welfare for farmers.

The research confirms that behavioral factors may strongly drive vulnerable smallholder farmers to speculate into storage even under seasonal and uncertain marketing volatility. There is the need to think deeper about the rationale of promoting cooperatives and other agricultural forms, because imposing these without careful consideration can have negative impacts.

Do risk and time preferences affect the decision of farmers to utilize storage facilities? This question is important because it is not clear if and how risk preferences affect the tradeoff between consuming today and saving for tomorrow, especially for farmers in developing countries.

The purpose of this study is to extend Bippus and Young’s (2005) study and examine the effectiveness of the “I-you,” “I,” “You,” “We,” “But” and Question-based “Why” statements from Winer’s (2021) verbal coding program of conflict management using Bandura’s (1977) social learning theory (SLT).

Mixed methods were used using 175 university students from Texas and New York. A cross-sectional convenience sampling approach was conducted. Survey data was collected using Qualtrics.

Descriptive results demonstrated that the “We” statement was the most passive, the “I-you” statement was the most assertive and the “But,” “I,” “You” and Question statements were perceived to be aggressive. In addition, assertive “I-You” statements were perceived to be more effective in resolving the conflict and maintaining a relationship, whereas aggressive statements were less likely to resolve the conflict and maintain the relationship. Qualitative themes also support the “I-You” statement as the most assertive, while the “But,” “You” and “I” statements were found to be the most aggressive statements.

Implications and applications are discussed to stimulate future research among researchers and practitioners when addressing conflict. Being aware of the verbal statements that de-escalate conflict may be helpful in solving conflict in interpersonal, family and professional relationships. Future trainings can adopt effective verbal statements to resolve conflict when experiencing anger issues. Future research can continue to investigate verbal communication statements using SLT to help practitioners and managers address conflict in interpersonal relationships.

This study examines verbal statements in relation to communication styles and conflict management.

Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel machine-learning method for the rapid estimation of permeability of porous media at different deformation stages constrained by hydro-mechanical coupling analysis.

A convolutional neural network (CNN) is proposed in this paper, which is guided by the results of finite element coupling analysis of equilibrium equation for mechanical deformation and Boltzmann equation for fluid dynamics during the hydro-mechanical coupling process [denoted as Finite element lattice Boltzmann model (FELBM) in this paper]. The FELBM ensures the Lattice Boltzmann analysis of coupled fluid flow with an unstructured mesh, which varies with the corresponding nodal displacement resulting from mechanical deformation. It provides reliable label data for permeability estimation at different stages using CNN.

The proposed CNN can rapidly and accurately estimate the permeability of deformable porous media, significantly reducing processing time. The application studies demonstrate high accuracy in predicting the permeability of deformable porous media for both the test and validation sets. The corresponding correlation coefficients (R²) is 0.93 for the validation set, and the R² for the test set A and test set B are 0.93 and 0.94, respectively.

This study proposes an innovative approach with the CNN to rapidly estimate permeability in porous media under dynamic deformations, guided by FELBM coupling analysis. The fast and accurate performance of CNN underscores its promising potential for future applications.

The competition in the academe has always been tough, but today, the academe seems to be more like an industry than an academic community as academics are evaluated through quantified and economic means.

This article leans on Heidegger’s thoughts on the essence of technology and his ontological view on being to show the dangers that lie in this quantification of researchers and research.

Despite the benefits that information systems (ISs) offer to people and research, it seems that technology has made it possible to objectify researchers and research. This has a negative impact on the academe and should thus be looked into especially by the IS field, which should note the problems that exist in its core. This phenomenon of quantified academics is clearly visible at academic quantification sites, where academics are evaluated using metrics that count their output. It seems that the essence of technology has disturbed the way research is valued by emphasising its quantifiable aspects. The study claims that it is important to look for other ways to evaluate researchers rather than trying to maximise research production, which has led to the flooding of articles that few have the time or interest to read.

This paper offers new insights into the current phenomenon of quantification of academics and underlines the need for critical changes if in order to achieve the academic culture that is desirable for future academics.

The objectives of this study are threefold: to delineate the phenomenon of “You Share, We Donate” (YSWD) campaigns and what distinguishes them from sales-based cause-related marketing; to contrast the effectiveness of YSWD and sales-based cause-related marketing campaigns and provide an explanation for the differences in the effectiveness; to explore boundary conditions of the proposed differences.

Three experiments were conducted to empirically test the differential effect of campaign formats (i.e. YSWD vs sales-based cause-related marketing), the underlying mechanism and structural as well as contextual features moderating the differential effect.

The findings suggest that YSWD messages elicit consumers’ message-sharing intentions more than traditional cause-related marketing messages. The effect is explained by consumers’ sense of empowerment and can be enhanced through donation cap non-specification. The findings further indicate that YSWD campaigns are especially fruitful in low power distance cultures.

This study contributes toward corporate donation campaign literature by focusing on the usage of social media.

From a managerial perspective, this research provides marketers with guidelines on how to choose between the two cause-related marketing campaign formats and how to enhance the effectiveness of YSWD campaigns.

This paper extends cause-related marketing literature by not only introducing the phenomenon of YSWD campaigns to the literature but also exploring strategies to enhance the effectiveness of such campaigns and shedding light on an outcome beyond the sales impact of cause-related marketing campaigns, i.e. an increase of visibility in social media. From a managerial perspective, this research provides marketers with guidelines on how to choose between the two cause-related marketing campaign formats and how to enhance the effectiveness of YSWD campaigns.

This study aims to investigate the viewpoints of heterodox economic thoughts and Islamic economic thought concerning the concept of waste. Additionally, it explores the shared criticisms that both perspectives hold against mainstream economic thought in relation to waste.

First of all, the concept of waste is examined and the global effects of waste are investigated. Criticisms directed in the context of waste in mainstream economics in the context of heterodox school thoughts are examined. Likewise, criticisms directed in the context of waste in mainstream economics in the context of Islamic economic thoughts are examined. Finally, the common and different aspects of heterodox and Islamic economic thoughts were discussed, and the common criticisms of mainstream economic thought’s point of view toward waste were examined. This study is a theoretical, qualitative study.

Although both ideas have different aspects, heterodox and Islamic economic thoughts believe that the mainstream economy, which is based on capitalism and materialism, creates waste by ignoring the long-term social and environmental consequences of economic activity. They argue that the pursuit of profits and growth, without considering the impact on society and the environment, leads to an inefficient and unsustainable use of resources.

The best author’s knowledge, by emphasizing the common and different aspects of Islamic economics and heterodox thoughts, this study is the first to examine the concept of waste in the context of the common aspects of these ideas.

This study aims to assess the effectiveness of a scale measuring artificial intelligence capabilities by using the resource-based theory. It seeks to examine the impact of these capabilities on the organizational-level resources of dynamic capabilities and organizational creativity, ultimately influencing the overall performance of government organizations.

The calibration of artificial intelligence capabilities scale was conducted using a combination of qualitative and quantitative analysis tools. A set of 26 initial items was formed in the qualitative study. In the quantitative study, self-reported data obtained from 344 public managers was used for the purposes of refining and validating the scale. Hypothesis testing is carried out to examine the relationship between theoretical constructs for the purpose of nomological testing.

Results provide empirical evidence that the presence of artificial intelligence capabilities positively and significantly impacts dynamic capabilities, organizational creativity and performance. Dynamic capabilities also found to partially mediate artificial intelligence capabilities relationship with organizational creativity and performance, and organizational creativity partially mediates dynamic capabilities – organizational creativity link.

The application of artificial intelligence holds promise for improving decision-making and problem-solving processes, thereby increasing the perceived value of public service. This can be achieved through the implementation of regulatory frameworks that serve as a blueprint for enhancing value and performance.

There are a limited number of studies on artificial intelligence capabilities conducted in the government sector, and these studies often present conflicting and inconclusive findings. Moreover, these studies indicate literature has not adequately explored the significance of organizational-level complementarity resources in facilitating the development of unique capabilities within government organizations. This paper presents a framework that can be used by government organizations to assess their artificial intelligence capabilities-organizational performance relation, drawing on the resource-based theory.

This paper aims to present the novel stacked machine learning approach (SMLA) to estimate low-cycle fatigue (LCF) life of SAC305 solder across structural parts. Using the finite element simulation (FEM) and continuous damage mechanics (CDM) model, a fatigue life database is built. The stacked machine learning (ML) model's iterative optimization during training enables precise fatigue predictions (2.41% root mean square error [RMSE], R² = 0.975) for diverse structural components. Outliers are found in regression analysis, indicating potential overestimation for thickness transition specimens with extended lifetimes and underestimation for open-hole specimens. Correlations between fatigue life, stress factors, nominal stress and temperature are unveiled, enriching comprehension of LCF, thus enhancing solder behavior predictions.

This paper introduces stacked ML as a novel approach for estimating LCF life of SAC305 solder in various structural parts. It builds a fatigue life database using FEM and CDM model. The stacked ML model iteratively optimizes its structure, yielding accurate fatigue predictions (2.41% RMSE, R² = 0.975). Outliers are observed: overestimation for thickness transition specimens and underestimation for open-hole ones. Correlations between fatigue life, stress factors, nominal stress and temperature enhance predictions, deepening understanding of solder behavior.

The findings of this paper highlight the successful application of the SMLA in accurately estimating the LCF life of SAC305 solder across diverse structural components. The stacked ML model, trained iteratively, demonstrates its effectiveness by producing precise fatigue lifetime predictions with a RMSE of 2.41% and an “R²” value of 0.975. The study also identifies distinct outlier behaviors associated with different structural parts: overestimations for thickness transition specimens with extended fatigue lifetimes and underestimations for open-hole specimens. The research further establishes correlations between fatigue life, stress concentration factors, nominal stress and temperature, enriching the understanding of solder behavior prediction.

The authors confirm the originality of this paper.

Organizational resilience, defined by a firm’s speed in reaching a dynamic equilibrium after a shock and after the shocks are absorbed, and crisis management are critical in a global crisis. The concept of resilience is increasingly used in the economic press; nevertheless, few studies demonstrate empirically how firms became resilient and the lessons to be learned from it. Traditionally, the concept of resilience is approached as resistance in the face of a crisis. The authors go further by showing three-loop learning, which is part of a logic of innovation and regeneration. This study aims to examine how a business can regenerate itself by effectively managing the external threats and disruptions caused by a crisis. Also, this study deepens knowledge on learning process. The double-loop learning process is known in the literature as enabling firms to learn from unexpected events and react accordingly. The findings point out a third loop implying the co-invention of a new business model and a collective mindfulness of changes made.

Using longitudinal data, the authors investigate how the global crisis affects merger negotiations between two companies. This study analyzes the period of dialogue (negotiation) between the two entities with a view to carrying out a merger and then their withdrawal from the project during the pandemic, reshuffling the cards for each company. The negotiation period is not normally disclosed because of its highly confidential and strategic nature and it is therefore difficult for researchers to access merger operations at the negotiation stage. From this viewpoint, this case study was chosen because of the availability of generally inaccessible documentation.

This in-depth case study provides new insights on organizational resilience and the recovery capacity of a firm. The results underline four main triggers that a firm should develop in facing a major crisis: skills; credits; previous and historical relationships; and corporate culture. Recovery capacity depends on reactivity, flexibility, learning and regeneration. Finally, this study points out a three-loop learning experience that can be understood as a learning process in two steps to generate lasting and adaptive changes.

The limitations are those concerning a single case study.

This study highlights the ability to deal with unexpected events. First, this work identifies concrete items that can be perceived by managers as elements enabling a firm to develop resilience. Second, the results show main elements enabling this capacity as reactivity – both companies react quickly and effectively to disturbances to limit the impact on their performance; or flexibility – firms adapt their business model to deal with disruptions. Third, this work underlines a learning capacity process in three steps to recover capacity. This process stimulates creativity and innovation by the teams and stakeholders by placing them at the heart of the change.

This case provides a vivid illustration of firms’ adaptation to a rapidly evolving context because of a global crisis. Theoretical concepts and empirical findings from the literature are combined to present a single consistent picture.