Search results

This paper aims to explore whether brand corporate social responsibility (CSR) initiatives increase consumers’ happiness via a mediating mechanism of emotional brand attachment and to examine how brand CSR’s effect may be moderated by CSR fit (e.g. CSR-brand fit vs misfit) and sense of relatedness (e.g. low vs high).

A series of six studies (including the one that is available online), combining field and experimental data, were conducted to test the hypothesized relationships.

Results support the hypothesis that brand CSR initiatives make consumers happy by increasing their attachment to the brand (Studies 1 and 2). This effect is strengthened both directly and indirectly through emotional attachment when brands engage in CSR fit activities (Study 3), but it is weakened when brands engage in CSR misfit activities (Study 4). Furthermore, the effect is more pronounced when brands choose CSR activities that have a high sense of relatedness, and it is eliminated when brands use CSR activities with a low sense of relatedness (Study 5). Finally, the results indicate that when brand CSR programs make consumers happy, they become more likely to purchase, spread positive word of mouth and pay a premium (Study 6).

This research has several major implications for business-to-consumer companies that are unsure about the value of brand CSR initiatives, want to make consumers happy but are unsure which CSR strategies to focus on and/or have decided to launch CSR initiatives but lack guidance on the specific strategies relevant to their desired performance outcomes.

The purpose of this study is to prolong the service life of the Al–Si alloy cylinder and achieve the objective of energy saving and emission reduction by the composite treatments.

Chemical etching + laser texturing + filled MoS₂ composite treatment was applied to the friction surface of aluminum–silicon (Al–Si) alloy cylinder. The friction coefficient and wear loss were measured to characterize the tribology property of cylinders.

The composite-treated Al–Si alloy cylinder had the lowest friction coefficient and weight loss. The friction coefficient and weight loss of the composite treatment were approximately 27.08% and 54.17% lower than those of the untreated sample, respectively. The laser micro-textures control the release of solid lubricant to the interface of friction pairs slowly, which prolongs the service life of cylinders.

The synergistic effect of the chemical etching + laser texturing + filled MoS2 modified the tribology properties of Al–Si alloy cylinder. The chemical etching raised the silicon particles to bear the load, and laser micro-textures control the release of solid lubricant to improve the lubrication property.

This study aims to clarify the influence mechanism of polishing solution type on the glazing evolution of fixed abrasive pad under different interfacial pressure conditions.

The tribological experiments were carried out on the friction and wear machinery with W3-5 diamond fixed abrasive pad and quartz glass workpiece under three polishing solution types of five pressure conditions. The changes of surface morphology, porosity and hardness of fixed abrasive pad were detected by white light interferometer, optical microscope and shore hardness tester.

The results showed that the glazed phenomenon of fixed abrasive pad is occurred after a certain time, which is more obvious with the increasing of interfacial pressures. The polishing solution type has a significant effect on the glazing time, although the glazed phenomenon is inevitable. The mechanism of it is that the micro-convex peaks on the surface of the fixed abrasive pad are easily wear, and the pores are blocked by the accumulation of waste debris generated during the experiment process. Thus, a smooth and high-density hard layer is formed on the surface of the fixed abrasive pad which induces the decreasing of the friction coefficient and surface roughness value. For selected polishing solution types, the wear rate of micro-convex peaks is different due to the corrosion action difference with polishing pad surface.

The main contribution of this work is to provide a new investigating method for further understanding the glazing evolution mechanism of fixed abrasive pad.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2023-0257/

This paper aims to present a novel approach for computing particle temperatures in simulations coupling computational fluid dynamics (CFD) and discrete element method (DEM) to predict flow and heat transfer in fluidized beds of thermally thick spherical particles.

An improved lumped formulation based on Hermite-type approximations for integrals to relate surface temperature to average temperature and surface heat flux is used to overcome the limitations of classical lumped models. The model is validated through comparisons with analytical solutions for a convectively cooled sphere and experimental data for a fixed particle bed. The coupled CFD-DEM model is then applied to simulate a Geldart D bubbling fluidized bed, comparing the results to those obtained using the classical lumped model.

The validation cases demonstrate that ignoring internal thermal resistance can significantly impact the temperature in cases where the Biot number is greater than 0.1. The results for the fixed bed case clearly demonstrate that the proposed method yields significantly improved outcomes compared to the classical model. The fluidized bed results show that surface temperature can deviate considerably from the average temperature, underscoring the importance of accurately accounting for surface temperature in convective heat transfer predictions and surface processes.

The proposed approach offers a physically more consistent simulation without imposing a significant increase in computational cost. The improved lumped formulation can be easily and inexpensively integrated into a typical DEM solver workflow to predict heat transfer for spherical particles, with important implications for various industrial applications.

A zero-day vulnerability is a complimentary ticket to the attackers for gaining entry into the network. Thus, there is necessity to device appropriate threat detection systems and establish an innovative and safe solution that prevents unauthorised intrusions for defending various components of cybersecurity. We present a survey of recent Intrusion Detection Systems (IDS) in detecting zero-day vulnerabilities based on the following dimensions: types of cyber-attacks, datasets used and kinds of network detection systems.

Purpose: The study focuses on presenting an exhaustive review on the effectiveness of the recent IDS with respect to zero-day vulnerabilities.

Methodology: Systematic exploration was done at the IEEE, Elsevier, Springer, RAID, ESCORICS, Google Scholar, and other relevant platforms of studies published in English between 2015 and 2021 using keywords and combinations of relevant terms.

Findings: It is possible to train IDS for zero-day attacks. The existing IDS have strengths that make them capable of effective detection against zero-day attacks. However, they display certain limitations that reduce their credibility. Novel strategies like deep learning, machine learning, fuzzing technique, runtime verification technique, and Hidden Markov Models can be used to design IDS to detect malicious traffic.

Implication: This paper explored and highlighted the advantages and limitations of existing IDS enabling the selection of best possible IDS to protect the system. Moreover, the comparison between signature-based and anomaly-based IDS exemplifies that one viable approach to accurately detect the zero-day vulnerabilities would be the integration of hybrid mechanism.

This study aims to determine whether or not fashion retail brands can maintain their essence by providing personalized care through conventional face-to-face interactions or the use of e-services.

An exploratory investigation is being conducted to attain this goal. According to the findings of this research, Chatbots have an impact on consumer loyalty. The quality of a Chatbot’s system, service and information are all critical to providing a positive consumer experience.

The study concluded that Chatbot e-services might potentially enable dynamic and fascinating interactions between firms and their consumers. To personalize a Chatbot, firms might change the tone of the language used. Customers are more likely to use a Chatbot if it resembles a real person, which increases their pleasure and confidence in the product.

More precisely, the emphasis of the inquiry was on Chatbot, a relatively new digital tool that offers user-friendly, personalized and one-of-a-kind support to customers. Using information supplied by consumers, the authors examine a five-dimensional model that gauges how customers feel about Chatbots in terms of their ability to communicate with users, offer amusement, be trendy, personalize interactions and solve problems.

This study aims to empirically test how sponsored video customization (i.e. the degree to which a sponsored video is customized for a sponsoring brand) affects video shares differently depending on influencer characteristics (i.e. mega influencer and expert influencer) and brand characteristics (i.e. brand establishment and product involvement).

This study uses a unique real-world data set that combines coded variables (e.g. customization) and objective video performance (e.g. sharing) of 365 sponsored videos to test the hypotheses. A negative binomial model is used to analyze the data set.

This study finds that the effect of video customization on video shares varies across contexts. Video customization positively affects shares if they are made for well-established brands and high-involvement products but negatively influences shares if they are produced by mega and expert influencers.

This study extends the influencer marketing literature by focusing on a new media modality – sponsored video. Drawing on the multiple inference model and the persuasion knowledge theory, this study teases out different conditions under which video customization is more or less likely to foster audience engagement, which both influencers and brands care about. The chosen research setting may limit the generalizability of the findings of this study.

The findings suggest that mega and expert influencers need to consider if their endorsement would backfire on a highly customized video. Brands that aim to engage customers with highly-customized videos should gauge their decision by taking into consideration their years of establishment and product involvement. For video-sharing platforms, especially those that are planning to expand their businesses to include “matching-making services” for brands and influencers, the findings provide theory-based guidance on optimizing such matches.

This paper fulfills an urgent research need to study how brands and influencers should produce sponsored videos to achieve optimal outcomes.

Based on the principles of the social capital theory (SCT), this study aimed to generate hypotheses and evaluate a mediated moderated model that examined the impact of social capital on online brand community happiness (OBCH).

Using 215 online questionnaires from users of private online brand communities (OBCs) , researchers examined the hypothesized connections between variables. The SPSS 21.0 and AMOS 26.0 were applied to fulfill the purpose.

For the goodness of model fit, the authors have applied cut off criteria for fit indexes given by Hu and Bentler (1999) and model-fit measures indicators, i.e. CMIN/DF 1.397, CFI 0.958, SRMR 0.045, RMSEA 0.043 and PCLOSE 0.866, which meet the minimum acceptable criteria. Based on the results, social capital significantly affects psychological well-being (PWB), which, consequently, leads toward increased happiness among OBCs. Furthermore, membership duration moderates the relationship between PWB and OBCs.

The authors have utilized a cross-sectional research design, and it limits the researcher’s ability to generalize the findings. These findings imply how social capital leverages PWB and OBCH. Moreover, the presence of membership duration helps to understand that members who spend more time in the community are happier in the OBCs.

In this age of social media, it provides valuable guidance to the administrators of private Facebook groups dedicated to specific brands, enhancing the definition and development of OBC operations and community interactions.

This research takes a broader look at social capital’s impact on happiness among private OBCs. The current research contributes to the existing body of work by emphasizing the role of PWB in generating happiness. The study is novel in examining the mediating moderating model of PWB and membership duration to explore deep insights for social media platforms.

This study aims to enhance the lubrication performance of thrust bearings. The influence of columnar convex–concave compound microtexture on bearing performance is investigated

Based on the compound microtexture model of thrust bearings, considering surface roughness and turbulent effect, the variation of lubrication characteristics with the change in the compound microtexture parameters is studied.

The results indicate that, compared with circular microtexture, the maximum pressure of compound microtexture of thrust bearings increases by 7.42%. Optimal bearing performance is achieved when the internal microtexture depth is 0.02 mm. Turbulent flow states and surface roughness lead to a reduction in the optimal depth. The maximum pressure and load-carrying capacity of the bearing decrease as the initial angle increases, whereas the friction coefficient increases with the increase in the initial angle. The lubrication performance is best for bearings with a circumferential parallel arrangement of microtexture.

The novel composite microtexture with columnar convex-concave is proposed, and the computational model of thrust bearings is set. The influence of surface roughness and turbulent flow on the bearing performance should be considered for better conforming with engineering practice. The effect of microtexture depth, arrangement method and distribution position on the lubrication performance of the compound microtexture thrust bearing is investigated, which is of great significance for improving tribology, thrust bearings and surface microtexture theory.

Original equipment manufacturers and other manufacturing companies rely on the delivery performance of their upstream suppliers to maintain a steady production process. However, supplier capacity uncertainty and delayed delivery often poses a major concern to manufacturers to carry out their production plan as per the desired schedules. The purpose of this paper is to develop a decision model that can improve the delivery performance of suppliers to minimise fluctuations in the supply quantity and the delivery time and thus maximising the performance of the supply chain.

The authors studied a single manufacturer – single supplier supply chain considering supplier uncertain capacity allocation and uncertain time of delivery. Mathematical models are developed to capture expected profit of manufacturer and supplier under this uncertain allocation and delivery behaviour of supplier. A reward–penalty mechanism is proposed to minimise delivery quantity and time of delivery fluctuations from the supplier. Further, an order-fulfilment heuristic based on delivery probability is developed to modify the order quantity which can maximise the probability of a successful deliveries from the supplier.

Analytical results reveal that the proposed reward–penalty mechanism improves the supplier delivery consistency. This consistent delivery performance helps the manufacturer to maintain a steady production schedule and high market share. Modified ordering schedule developed using proposed probability-based heuristic improves the success probability of delivery from the supplier.

Practitioners can benefit from the findings of this study to comprehend how contracts and ordering policy can improve the supplier delivery performance in a manufacturing supply chain.

This paper improves the supplier delivery performance considering both the uncertain capacity allocation and uncertain time of delivery.