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Consumers nowadays are no longer bystanders in the process of production but are proactive collaborators with the power to co-create value with brands. This study aims to explore the impact of social commerce on the co-creation process of brand value in a social commerce setting.

A questionnaire survey was conducted online to gather 300 eligible responses. The data were empirically validated using the partial least squares structural equation modelling (PLS-SEM) method.

The results indicated that brand engagement (BEN) is vital to brand co-creation (BCC) in social commerce, which could be driven by social-hedonic value (SHV) and social information sharing (SIS).

This study stresses the influence of consumer autonomy in the process of BCC by probing the role of SIS. Moreover, by considering the prevailing trend in social media, this study offers a nuanced perspective on the values of social commerce from the viewpoint of SHV.

This study may serve as a useful guide for practitioners to improve their digital outreach strategy on social commerce to forge stronger relationships, encourage further engagements and promote value co-creation within their brand community.

This examines the effect of relationship quality (RQU) and BEN on BCC through a relational viewpoint.

Gastronomic festivals are important events to bring people together around food-themed activities. This study aimed at determining the relationships between festival quality, memorable food experience, loyalty, behavioral intention, hedonic well-being, and eudaimonic well-being. In this study, festival quality is the independent variable that affects the memorable food experience, the memorable food experience is the independent variable that affects loyalty, and loyalty is the independent variable that affects behavioral intent. Hedonic well-being and eudaimonic well-being are moderating variables. Behavioral intention is the dependent variable, while memorable food experience and loyalty are both dependent and independent variables.

The population consisted of local tourists visiting Orange Blossom Carnival held in Adana, Turkey. The survey technique and the convenience sampling method were preferred and 545 data were obtained.

The analysis results showed that all dimensions of the memorable food experience are strongly affected by festival quality. Plus, superior service approach and high value perception dimensions of the memorable food experience have significant effects on loyalty. Furthermore, destination loyalty was found to have a strong effect on behavioral intentions. Moreover, higher levels of Hedonic well-being (HWB) and Eudomenic well-being (EWB) were found to increase the effect of loyalty on behavioral intention; accordingly, the moderator roles of HWB and EWB were determined.

This article provides information that the memorable dining experiences of festival visitors who attend the Orange Blossom Carnival in Adana affect the quality of the festival and their intentions to loyalty. In addition, in the study, it was found that the well-being of carnival visitors had a moderating role in the effect of their loyalty on their behavioral intentions. Therefore, this article provides information on how the food experiences and well-being of the visitors at the gastronomy festival will affect which factors.

According to the findings, gastronomy-based events may affect tourists’ experiences, and tourists’ psychological well-being affects loyalty and behavioral intentions. Destination management organizations can learn about gastronomy-based festivals. The results of the study include a number of theoretical and practical findings for destination management organizations, festival managers, policy makers and academics working in the literature.

The main aim of this study is to examine the behavior of reinforced concrete short columns strengthened using longitudinal near surface mounted (NSM)-carbon fiber reinforced polymer (CFRP) strips.

A full 3D-finite element (FE) model was developed using ABAQUS in order to conduct the analysis. The model is first validated based on experimental data available in the literature, and then the effect of concrete compressive strength, number of CFRP strips that are used and the spacing between them were taken in consideration for both concentric and eccentric loading cases. The parametric study specimens were divided into three groups. The first group consisted of unstrengthened columns and served as control specimens. The second group consisted of columns strengthened by longitudinal CFRP strips at two opposite column faces.

The results of this study are used to develop interaction diagrams for CFRP-strengthened short columns and to develop best-fit equations to estimate the nominal axial load and moment capacities for these strengthened columns. The results showed that the specimens that were strengthened using more longitudinal CFRP strips showed a significant increase in axial load capacity and a significant improvement in the interaction diagram, especially at large load eccentricity values. This result can be justified by the fact that longitudinal strips effectively resist the bending moment that is generated due to eccentric loading. Generally, the process of strengthening using longitudinal strips only has a reasonable effect and it can be typically considered an excellent choice considering the economic aspect when the budget of strengthening is limited.

This research aims at studying the performance of strengthened rectangular reinforced concrete short columns with CFRP strips using FE method, developing interaction diagrams of strengthened columns in order to investigate the effect of different parameters such as compressive strength (20, 30 and 40 MPa), number of CFRP strips (1, 2, 3 and 4) and the spacing between CFRP strips in terms of the ratio of CFRP center point distance to column outside dimension ratio (0.60, 0.70 and 0.80) on the behavior of strengthened RC columns and improving empirical formulas to predict the nominal axial load and moment capacities of strengthened RC columns. These parameters that directly affect short column load carrying capacity are presented in ACI-318 (2014).

Drawing on conservation of resources theory, this study aims to examine the relationship between temporal leadership (TL) and employees’ thriving at work (TW) by focusing on the positive mediating role of perception of work-goal progress (PWP), the negative mediating roles of job-based psychological ownership (JPO) and the moderating role of synchrony preference (SP).

We employed a dedicated data collection platform called Credamo for two waves of online questionnaires in China between March 2022 and April 2022. A total of 326 questionnaires were collected and analyzed to test the hypotheses.

(1) TL directly and positively affects TW. (2) TL indirectly and positively affects TW via PWP. (3) TL indirectly and negatively affects TW via JPO. (4) SP positively moderates the positive mediating effect of PWP on the relationship between TL and TW. (5) SP negatively moderates the negative mediating effect of JPO on the relationship between TL and TW.

Supervisors in organizations ought to discreetly practice TL and try to maximize the positive role of PWP and minimize the negative role of JPO.

The findings simultaneously discuss the effects of TL on TW from dark and bright perspectives. The influence of interaction between contextual and individual features on TW is also specified.

The extant literature documents the significance of nostalgia-evoking stimuli in promoting consumer behavior. Despite the prevalent use of nostalgia-evoking stimuli in restaurant service, research on nostalgia-evoking restaurants is significantly lacking. As a result, little is known about customers’ cognitive responses toward nostalgia-themed restaurant stimuli and their influences on customer loyalty behavior. Thus, grounded in an extended stimulus-organism-response model, this study aims to examine the role of nostalgia-evoking restaurant stimuli in explaining an integrated model focusing on nostalgia, in relation to local food consumption value, familiarity with nostalgia-triggering restaurants and loyalty and continued patronage.

The authors collected data from 544 Taiwanese customers at nostalgia-themed restaurants. Using PROCESS (Model 6), the direct and indirect effect of nostalgia-evoking restaurant stimuli on loyalty and continued patronage were examined.

The confirmatory factor analysis results showed that five domains of restaurant attributes (i.e., service staff, exterior and interior design, furniture and tableware, local food and atmosphere) are nostalgia-evoking stimuli. The authors also found that these nostalgia-evoking stimuli significantly affected customer loyalty indirectly, through customers’ consumption value and familiarity.

The results of this study help identify the importance of nostalgia-generating cues in nostalgia-themed restaurants and their roles in postpurchase behaviors. The outcomes contribute to an improved understanding of how to exploit nostalgic sentiments in nurturing diners’ consumption value, maintaining customer loyalty and generating greater profits.

To the best of the authors’ knowledge, this is one of the few studies examining restaurant attributes evoking nostalgia and explaining the mechanism by which nostalgia-evoking stimuli affect consumer behavior.

The COVID-19 pandemic has caused significant mortality and morbidity worldwide. However, the role of dietary patterns as a potential risk factor for COVID-19 has not been well established, especially in studies with large samples. Therefore, this study aims to identify and evaluate the association between major dietary patterns and COVID-19 among adults from Iran.

In this cross-sectional study, the authors included 9,189 participants aged 20–70 who participated in the Yazd Health Study (YaHS) and Taghzieh Mardom-e-Yazd study (TAMIZ). They used factor analysis to extract dietary patterns based on a food frequency questionnaire (FFQ). Then, they assessed the relationship between these dietary patterns and the odds of COVID-19.

This study identified two major dietary patterns: “high protein and high fiber” and “transitional”. Participants in the highest tertile of the “high protein and high fiber” dietary pattern, which included vegetables, fruits, dairy and various kinds of meats such as red meat, fish and poultry, had a lower odds of COVID-19 compared with those in the lowest tertile. However, the “transitional” dietary pattern did not affect the risk of COVID-19.

In conclusion, a “high protein, high fiber” diet may lower the odds of COVID-19. This study suggests that dietary patterns may influence the severity and spread of future similar pandemics.

The purpose of this paper is to present an automatic approach for mesh sizing field generation of complicated  computer-aided design (CAD) models.

In this paper, the authors present an automatic approach for mesh sizing field generation. First, a source point extraction algorithm is applied to capture curvature and proximity features of CAD models. Second, according to the distribution of feature source points, an octree background mesh is constructed for storing element size value. Third, mesh size value on each node of background mesh is calculated by interpolating the local feature size of the nearby source points, and then, an initial mesh sizing field is obtained. Finally, a theoretically guaranteed smoothing algorithm is developed to restrict the gradient of the mesh sizing field.

To achieve high performance, the proposed approach has been implemented in multithreaded parallel using OpenMP. Numerical results demonstrate that the proposed approach is remarkably efficient to construct reasonable mesh sizing field for complicated CAD models and applicable for generating geometrically adaptive triangle/tetrahedral meshes. Moreover, since the mesh sizing field is defined on an octree background mesh, high-efficiency query of local size value could be achieved in the following mesh generation procedure.

How to determine a reasonable mesh size for complicated CAD models is often a bottleneck of mesh generation. For the complicated models with thousands or even ten thousands of geometric entities, it is time-consuming to construct an appropriate mesh sizing field for generating high-quality mesh. A parallel algorithm of mesh sizing field generation with low computational complexity is presented in this paper, and its usability and efficiency have been verified.

Social commerce (SC) is a new genre in electronic commerce (e-commerce) that has great potential. This study proposes a new research framework to address deficiencies in existing social commerce research frameworks (e.g. the information model).

In the era of Industrial Revolution 4.0 technologies and new social commerce (s-commerce) models, the authors believe that there is an immediate need for a new research framework. The authors analysed the progress of the s-commerce paradigm between 2003 and 2023 by applying longitudinal science mapping. The authors then developed a research framework based on the themes in the strategic diagrams and evolution map.

From 2003 to 2010, studies on s-commerce mainly focused on social networking sites, virtual communities, social shopping and analytic approaches. From 2011 to 2015, it shifted to s-commerce, consumer behaviour, Web 2.0, artificial intelligence, social technologies, online shopping, user studies, data gathering methods, applications, service-based social commerce constructs, e-commerce and cognitive factors. Social commerce remained the primary research paradigm from 2017 to 2023.

The SC framework may be analogous to popular research frameworks such as technology-organisation-environment (T-O-E) and stimulus-organism-response (S-O-R). Based on this SC framework, researchers may gain a better understanding by determining the factors of the social, commercial, technological and behavioural dimensions.

The authors redefined s-commerce and developed an SC framework. Practical guidelines for the SC framework and an exemplary research model are presented. Overall, this study offers a new research agenda for the extant understanding of s-commerce, with the SC framework as the next frontier of the theoretical advancements and applications of s-commerce.

Surface roughness has a serious impact on the fatigue strength, wear resistance and life of mechanical products. Realizing the evolution of surface quality through theoretical modeling takes a lot of effort. To predict the surface roughness of milling processing, this paper aims to construct a neural network based on deep learning and data augmentation.

This study proposes a method consisting of three steps. Firstly, the machine tool multisource data acquisition platform is established, which combines sensor monitoring with machine tool communication to collect processing signals. Secondly, the feature parameters are extracted to reduce the interference and improve the model generalization ability. Thirdly, for different expectations, the parameters of the deep belief network (DBN) model are optimized by the tent-SSA algorithm to achieve more accurate roughness classification and regression prediction.

The adaptive synthetic sampling (ADASYN) algorithm can improve the classification prediction accuracy of DBN from 80.67% to 94.23%. After the DBN parameters were optimized by Tent-SSA, the roughness prediction accuracy was significantly improved. For the classification model, the prediction accuracy is improved by 5.77% based on ADASYN optimization. For regression models, different objective functions can be set according to production requirements, such as root-mean-square error (RMSE) or MaxAE, and the error is reduced by more than 40% compared to the original model.

A roughness prediction model based on multiple monitoring signals is proposed, which reduces the dependence on the acquisition of environmental variables and enhances the model's applicability. Furthermore, with the ADASYN algorithm, the Tent-SSA intelligent optimization algorithm is introduced to optimize the hyperparameters of the DBN model and improve the optimization performance.

Lean Six Sigma (LSS) implementation follows a structured approach called define-measure-analyze-improve-control (DMAIC). Earlier research about its application in emergency healthcare services shows that it requires organizational transformation, which many healthcare setups find difficult. The Kotter change management model facilitates organizational transformation but has not been attempted in LSS settings till now. This study aims to integrate the LSS framework with the Kotter change management model to come up with an integrated framework that will facilitate LSS deployment in emergency health services.

Two-stage Delphi method was conducted by using a literature review. First, the success factors and barriers of LSS are investigated, especially from an emergency healthcare point of view. The features and benefits of Kotter's change management models are then reviewed. Subsequently, they are integrated to form a framework specific to LSS deployment in an emergency healthcare set-up. The elements of this framework are analyzed using expert opinion ratings. A new framework for LSS deployment in emergency healthcare has been developed, which can prevent failures due to challenges faced by organizations in overcoming resistance to changes.

The eight steps of the Kotter model such as establishing a sense of urgency, forming a powerful guiding coalition, creating a vision, communicating the vision, empowering others to act on the vision, planning for and creating short-term wins, consolidating improvements and producing still more change, institutionalizing new approaches are derived from the eight common errors that managers make while implementing change in the institution. The study integrated LSS principles and Kotter’s change management model to apply in emergency care units in order to reduce waste and raise the level of service quality provided by healthcare companies.

The present study could contribute knowledge to the literature by providing a framework to integrate lean management and Kotter's change management model for the emergency care unit of the healthcare organization. This framework guides decision-makers and organizations as proper strategies are required for applying lean management practices in any system.

The proposed framework is unique and no other study has prescribed any integrated framework for LSS implementation in emergency healthcare that overcomes resistance to change.