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Mass customization is a production process that allows consumers to customize products from an array of options to suit their preferences and needs and benefit from large-scale production efficiencies. In recent years, several apparel retailers have integrated customization into their online presence. While the benefits of online apparel mass customization (OAMC) are apparent, factors that determine the usage of the process are many. Therefore, it is important to explore these factors and understand the relationships between them and the impact on the intention to use OAMC.

A review of studies published in the last decade was conducted through the Scopus, Web of Science and JSTOR databases in September 2023. Peer-reviewed research articles published in the English language were included. These studies were carried out in the United States of America, Canada, Korea and China and addressed motivations and antecedents of OAMC technology.

The data were extracted, and the findings were synthesized. The review process enabled us to examine several theories and determinants of OAMC. The latter were categorized into the following themes: “consumer personality and psychology”, “consumer perceptions”, “consumer behaviour determinants” and “process, experience and product”. The influence of consumer personality traits, psychogenic needs, characteristics and other facilitating conditions emerged through the review.

The purpose of this paper is to study the various determinants of OAMC and thereby provide valuable information to businesses in OAMC domains to improve customized processes, understand consumers' motivations and develop marketing strategies that improve overall satisfaction with OAMC.

To investigate the mechanical properties of geopolymer concrete at elevated temperatures.

The investigation involved studying the influence of partially replacing fly ash with ground granulated blast furnace slag (GGBS) at different proportions (5%, 10%, 15%, 20% and 25%) on the composition of the geopolymer. This approach aimed to examine how the addition of GGBS impacts the properties of the geopolymer material. The chemical NaOH was purchased from the local supplier of Jamshedpur. The alkali solution was prepared with a concentration of 12 M NaOH to produce the concrete. After several trials, the alkaline-to-binder ratio was determined to be 0.43.

The compressive strength values at 28 days for specimens FG1, FG2, FG3, FG4 and FG5 are 35.42 MPa, 41.26 MPa, 44.79 MPa, 50.51 MPa and 46.33 MPa, respectively. The flexural strength values at 28 days for specimens FG1, FG2, FG3, FG4 and FG5 are 5.31 MPa, 5.64 MPa, 6.12 MPa, 7.15 MPa and 6.48 MPa, respectively. The split tensile strength values at 28 days for specimens FG1, FG2, FG3, FG4 and FG5 are 2.82 MPa, 2.95 MPa, 3.14 MPa, 3.52 MPa and 3.31 MPa, respectively.

This approach allows for the examination of how the addition of GGBS affects the properties of the geopolymer material. Four different temperature levels were chosen for analysis: 100 °C, 300 °C, 500 °C and 700 °C. By subjecting the geopolymer samples to these elevated temperatures, the study aimed to observe any changes in their mechanical.

The present work focuses on evaluating the physical and mechanical characteristics of geopolymer concrete (GPC) by replacing the sodium silicate waste (SSW) in place of traditional river sand. The aim is to create eco-friendly concrete that mitigates the depletion of conventional river sand and conserves natural resources. Additionally, the study seeks to explore how the moisture content of filler materials affects the performance of GPC.

SSW obtained from the sodium silicate industry was used as filler material in the production of GPC, which was cured at ambient temperature. Instead of the typical conventional river sand, SSW was substituted at 25 and 50% of its weight. Three distinct moisture conditions were applied to both river sand and SSW. These conditions were classified as oven dry (OD), air dry (AD) and saturated surface dry (SSD).

As the proportion of SSW increased, there was a decrease in the slump of the GPC. The setting time was significantly affected by the higher percentage of SSW. The presence of angular-shaped SSW particles notably improved the compressive strength of GPC when replacing a portion of the river sand with SSW. When exposed to elevated temperatures, the performance of the GPC with SSW exhibited similar behavior to that of the mix containing conventional river sand, but it demonstrated a lower residual strength following exposure to elevated temperatures.

Exploring the possible utilization of SSW as a substitute for river sand in GPC, and its effects on the performance of the proposed mix. Analyzing, how varying moisture conditions affect the performance of GPC containing SSW. Evaluating the response of the GPC with SSW exposed to elevated temperatures in contrast to conventional river sand.

Concrete gravity dams are important structures for flood control and hydraulic power generation, but they can be vulnerable to seismic activity due to ground movements that trigger crack propagation.

To better understand the factors that affect the stability of concrete gravity dams against concrete fracture during earthquakes, a concrete plastic damage model has been utilized with two new expressions to simulate compressive and tensile damage variables.

The findings showed that the crack patterns were strongly influenced by the concrete’s strength. The simulation results led to the proposal of appropriate concrete properties aimed at minimizing damage. These findings, together with the proposed model, offer significant insights that can enhance the safety and stability of concrete gravity dam structures.

This study offers a comprehensive analysis of concrete behavior under varying grades and introduces simple and robust expressions for evaluating concrete parameters in plastic damage models. The versatility of these expressions enables accurate simulation of stress-strain curves for different grades, resulting in excellent agreement between model results and experimental findings. The simulation of the Koyna Dam case study demonstrates a similarity in crack patterns with previous simulations and field observations.

This paper aims to examine the Dufour and Soret combined effects on the study of two-dimensional squeezed flow of copper water nanofluid between parallel plates along with applied (external) magnetic field. Impact of higher order chemical reaction is also considered.

The nonlinear partial differential equations (PDEs) are changed into system of ordinary differential equations (ODEs) by employing suitable similarity transformations. These transformed ODEs are then solved by means of a semianalytical method called differential transform method (DTM). Effects of several changing physical parameters on fluid flow, temperature and concentration have been deliberated through graphs.

It is observed that Dufour and Soret numbers are directly related to temperature profile and a reverse trend was observed in the concentration profile. Temperature enhancement is perceived for the enhanced Dufour number. Enhancement in Dufour number shows a direct association with Sh and Nu for all values of squeezing parameter.

The combined Dufour and Soret effects are used in separation of isotopes in mixture of gases, oil reservoirs and binary alloys solidification. The squeeze nanoliquid flow can be used in the field of composite material joining, rheological testing and welding engineering.

This study is mainly useful for geosciences and chemical engineering.

The uniqueness in this research is the study of the impact of cross diffusion on chemically reacting squeezed nanoliquid flow with the chemical reaction order more than one in the presence of applied magnetic force using a semianalytical procedure, named DTM.

The purpose of this study is to investigate whether the lockdown and the increased spread of food delivery applications (FD Apps) during COVID-19 pandemic have augmented the consumption of fast foods.

A cross-sectional study was conducted on 673 adults from different regions of Saudi Arabia using an online questionnaire.

Data showed that 61% (N = 410) of participants used FD Apps during the pandemic. Among those users, 54.9% (225) were females and 70.5% were in the 18–44 years old group. Most FD Apps’ users were university graduates (74.4%). The increased use of FD Apps during the pandemic significantly affected the eating behavior and the nutritional pattern. It has further significantly augmented the consumption of fast foods (p-value < 0.05).

This study reports on the use of FD Apps during COVID-19 pandemic in Saudi Arabia and its impact on consumer eating pattern. This study shows the need for prudent use of these applications to limit ordering fast foods and consider healthier choices. It further calls for education programs, awareness campaigns, legislative measures and formal policies to rationalize the use of such applications for better nutrition, health and well-being.

The e-services market is expected to reach nearly $500bn globally by 2028. As this marketplace grows, customer-to-customer interactions (CCIs) occurring through virtual channels will likely increase. Consequently, the purpose of this research is to examine how the context in which CCI’s occur (i.e. virtual vs in-person) and the frequency of their occurrence affects customer identification, leading to increased customer engagement and more favorable purchase behaviors.

Two studies were conducted to test the proposed models and hypotheses. The sample for Study 1 is comprised of college students taking in-person or online classes (n = 290). In Study 2, members of an online brand community (n = 125) were surveyed. Hypotheses were tested using structural equation modeling (SEM).

Overall, results support a mediation effect such that CCI context (virtual vs in-person) affects customer engagement and purchase behaviors via customer identification. Specifically, Study 1 finds that customer engagement behaviors (CEBs) are greater for in-person CCIs due to the frequency of interactions and heightened identification between customers. Study 2 further examines the CCI frequency-identification link and finds that customer-firm identification is the only form of identification that affects CEBs and purchase behaviors.

Limited customer engagement research has examined the effects of CCIs on CEBs, and research has rarely compared in-person to virtual CCI contexts. This paper addresses these shortcomings by testing the effects of in-person and virtual CCIs on CCI frequency, identification and CEBs. This research fills another important gap in the literature by considering the unique effects of specific dimensions of customer identification on CEBs and purchase behaviors.

This research paper aims to examine consumers' perceptions and behaviours towards “pre-loved luxury fashion products” and focusses on analysing the moderating influence of consumers' attitude strength. Additionally, it investigates the impact of desirability in sustainable luxury experiences (LEs) on consumers' purchase intentions (PIs). The study draws inspiration from the Norm Activation Model theory and operationalises attitude strength using the Elaboration Likelihood Model theory.

Purposive sampling technique was employed to collect 317 useable samples from respondents who had previously purchased or intended to purchase pre-loved luxury fashion goods. SPSS and AMOS version 25 was used for data analysis.

The findings reveal that consumers' environmental concern influences their intention to purchase pre-loved luxury fashion products. Furthermore, sustainable LE acts as a significant mediator in this relationship. The study also demonstrates that the intention to purchase pre-loved luxury fashion products is strengthened when consumers possess a strong attitude towards them.

Luxury marketers can strategise accordingly to motivate consumers to purchase pre-loved luxury fashion products by resonating with their cultural correlates through persuasive advertising to favourably affirm their attitude towards pre-loved luxury fashion products.

This study contributes to the literature by addressing the unresolved area of PIs for pre-loved luxury fashion products, considering the moderating role of attitude strength in emerging markets. It highlights the significance of advocating and promoting pre-loved luxury fashion products and provides valuable insights for luxury marketers.

Social media has broadened the scope of luxury brand marketing and has emerged as a salient tool for Internet marketing campaigns in the post-pandemic world. Under the theoretical lens of the SOR model, this study aims to explore the nexus between brand social media marketing (BSMM) activities and online consumer brand engagement (CBE) via mediating consumers' emotions in the modest luxury fashion branding post-pandemic context.

This study conducted a post-pandemic survey in five major metropolitan cities in Pakistan with a total of 584 eligible young consumers who follow the fan pages of fashion brands. Structural equation modeling was used to test hypotheses.

The findings reveal that BSMM activities have a significant influence on three emotion states (pleasure, arousal and dominance); however, only pleasure and arousal significantly drive CBE (i.e. affective engagement and activation). Moreover, the results show that pleasure and arousal partially mediate the relationships between BSMM activities and affective and activation dimensions of CBE, while dominance fully mediates the relationship between BSMM activities and cognitive engagement. Interestingly, only affective engagement was shown to be the most potent component of CBE in fostering positive emotions toward luxury fashion brands.

This study contributes to the literature on social media marketing and consumer brand engagement by revealing valuable insights into post-pandemic luxury fashion branding that could assist academicians and marketing practitioners of non-Western markets.

To improve the thermal performance of base fluid, nanoparticles of three types are dispersed in the base fluid. A novel theory of non-Fourier heat transfer is used for design and development of models. The thermal performance of sample fluids is compared to determine which types of combination of nanoparticles are the best for an optimized enhancement in thermal performance of fluids. This article aims to: (i) investigate the impact of nanoparticles on thermal performance; and (ii) implement the Galerkin finite element method (GFEM) to thermal problems.

The mathematical models are developed using novel non-Fourier heat flux theory, conservation laws of computational fluid dynamics (CFD) and no-slip thermal boundary conditions. The models are approximated using thermal boundary layer approximations, and transformed models are solved numerically using GFEM. A grid-sensitivity test is performed. The accuracy, correction and stability of solutions is ensured. The numerical method adopted for the calculations is validated with published data. Quantities of engineering interest, i.e. wall shear stress, wall mass flow rate and wall heat flux, are calculated and examined versus emerging rheological parameters and thermal relaxation time.

The thermal relaxation time measures the ability of a fluid to restore its original thermal state, called thermal equilibrium and therefore, simulations have shown that the thermal relaxation time associated with a mono nanofluid has the most substantial effect on the temperature of fluid, whereas a ternary nanofluid has the smallest thermal relaxation time. A ternary nanofluid has a wider thermal boundary thickness in comparison with base and di- and mono nanofluids. The wall heat flux (in the case of the ternary nanofluids) has the most significant value compared with the wall shear stresses for the mono and hybrid nanofluids. The wall heat and mass fluxes have the highest values for the case of non-Fourier heat and mass diffusion compared to the case of Fourier heat and mass transfer.

An extensive literature review reveals that no study has considered thermal and concentration memory effects on transport mechanisms in fluids of cross-rheological liquid using novel theory of heat and mass [presented by Cattaneo (Cattaneo, 1958) and Christov (Christov, 2009)] so far. Moreover, the finite element method for coupled and nonlinear CFD problems has not been implemented so far. To the best of the authors’ knowledge for the first time, the dynamics of wall heat flow rate and mass flow rate under simultaneous effects of thermal and solute relaxation times, Ohmic dissipation and first-order chemical reactions are studied.