Search results

The purpose is to understand the fundamental mechanism of the consumer decision-making process and how perceived financial risk of search and experience goods influences electronic word-of-mouth adoption (e-WOMA) on social networking sites (SNSs), which will lead to purchase intention.

Drawing on information processing theory, the study conceptualizes a moderated mediation model to investigate the underlying influence of perceived financial risk and online social ties on e-WOMA and the subsequent effect on online purchase intention. Survey data from 275 individuals were analyzed through statistical tools using Statistical Package for the Social Sciences (SPSS).

The results revealed that e-WOMA mediates the effect of perceived financial risk of search and experience goods on online purchase intention. Strength of online social ties on SNSs positively moderates the electric word of mouth adoption for both the experience and search goods.

The limitation of this study was about the researcher's restrictions related to the length of the survey. Moreover, causal explanations can't be deduced as this is a cross-sectional study.

This research offers insight into the consumers that allow marketers to dive into the target market. Marketers should focus on social ties importance while selling products/services of markets online.

The study is novel in the context of an emerging economy to educate marketers on the product categorization of search goods and experience goods based on financial risk.

The purpose of this paper is to empirically analyse the cross‐countries determinants of nonperforming loans (NPLs), the potential impact of supervisory devices, and institutional environment on credit risk exposure.

The paper employs aggregate banking, financial, economic, and legal environment data for a panel of 59 countries over the period 2002‐2006. It develops a comprehensive model to explain differences in the level of NPLs between countries. To assess the role of regulatory supervision on credit risk, the paper uses several interactions between institutional features and regulatory devices.

The empirical results indicate that higher capital adequacy ratio (CAR) and prudent provisioning policy seems to reduce the level of problem loans. The paper also reports a desirable impact of private ownership, foreign participation, and bank concentration. However, the findings do not support the view that market discipline leads to better economic outcomes. All regulatory devices do not significantly reduce problem loans for countries with weak institutions, corrupt environment, and little democracy. Finally, the paper shows that the effective way to reduce bad loans is through strengthening the legal system and increasing transparency and democracy, rather than focusing on regulatory and supervisory issues.

First, higher CARs results in less credit exposures. Second, international regulators should continue their efforts to enhance financial development. The results suggest that foreign participation plays an important role in reducing credit exposure of financial institutions. However, in developed countries, foreign entry led to more problem loans. Finally, to reduce credit risk exposure in countries with weak institutions, the effective way to do it is through enhancing the legal system, strengthening institutions, and increasing transparency and democracy.

The paper contributes to the literature on banking regulation and supervision. It examines aggregated data which best reflect the level of NPL of the banks in a country as opposed to individual data included in databases that suffer from the problem of representativeness. It considers the impact of regulatory variables after controlling for bank industry factors that alter primarily problem loans. Finally, the paper examines the effectiveness of regulation through the inclusion of institutional factors.

The coating process is broadly employed in the manufacturing of wallpapers, adhesive tapes, wrapping, protection of fabrics and metals, X-ray and photographic films, beautification, books and magazines, film foils, magnetic records, coated paper, etc.

In this study, an incompressible flow of non-Newtonian fluid is modeled to inspect the rheological behavior of finite coating thickness in the reverse roll coating process. With the assistance of lubrication approximation theory (LAT), the dimensionless form of governing expressions is simplified. Exact solutions for distributions for velocity, flow rate, temperature and pressure gradient attained utilizing perturbation technique and their variation is presented as well as discussed in graphs. Meanwhile, some important factors from an engineering perspective including coating thickness and transition point were calculated mathematically and are displayed in a tabular manner. Also, streamlines are drawn to observe the flow pattern.

Prandtl fluid parameters provide a controlling factor to regulate the flow rate, velocity, coating thickness, and pressure gradient leading to an efficient coating process. Moreover, the Brinkman number and Prandtl fluid parameters significantly improve the temperature distribution.

In the literature, this study fills a gap in the theoretical prediction of coating thickness rheologically influenced by Prandtl fluid in reverse roll coating process.

This study aims to investigate consumer brand loyalty toward halal cosmetics using the theory of planned behavior through repurchase intention, which is primarily relying on the consumer’s attitude toward halal cosmetics. Important predictors such as trust on halal cosmetics, quality of halal cosmetics and religious beliefs of millennial Muslim female consumers shape consumer attitude.

The present study used the quantitative research design and deductive approach to collect the data from 275 halal cosmetics users in Pakistan by using a judgmental sampling approach.

Findings of the study provide useful insights for both theory and practice. The results support product quality, religious belief and trust on halal cosmetics as predictors of consumer’s attitude toward halal cosmetics that further develop consumers’ repurchase intention, which in turn enhances their overall brand loyalty. Besides, the findings also show that consumer repurchase intention has a mediating effect between consumer attitude toward halal cosmetics and consumer brand loyalty.

The current study helps in advancing practitioners’ understanding of female consumers’ brand loyalty in the halal cosmetics context. This study is considered to be greatly helpful for managers to gain knowledge about how repurchase intention and brand loyalty of millennial Muslim female consumers can be developed in the halal cosmetics segment, especially in the case of Pakistan.

Brand loyalty has been investigated by previous studies through different predictors and antecedents. This study contributes to the literature of brand loyalty by empirically examining and validating the different antecedents of consumer attitude that are accountable for creating consumer brand loyalty in the domain of halal cosmetics within the Pakistani cultural context. The current study also enhances the previous scholarly understanding on halal cosmetics by investigating the mediating role of consumer repurchase intention of halal cosmetics that further extends the discussion for both theory and practice.

Inventory models are quantitative ways of calculating low-cost operating systems. These models can be either deterministic or stochastic. A deterministic model hypothesizes variable quantities like demand and lead time, as certain. However, various types of research have revealed that the value of demand and lead time is still ambiguous and vary unanimously. The main purpose of this research piece is to reduce the uncertainties in such a dynamic environment of Industry 4.0.

The current study tackles the multiperiod single-item inventory lot-size problem with varying demands. The three lot sizing policies – Lot for Lot, Silver–Meal heuristic and Wagner–Whitin algorithm – are reviewed and analyzed. The suggested machine learning (ML)–based technique implies the criteria, when and which of these inventory models (with varying demands and safety stock) are best fit (or suitable) for economical production.

When demand surpasses a predicted value, variance in demand comes into the picture. So the current work considers these things and formulates the proper lot size, which can fix this dynamic situation. To deduce sufficient lot size, all three considered stochastic models are explored exclusively, as per respective protocols, and have been analyzed collectively through suitable regression analysis. Further, the ML-based Classification And Regression Tree (CART) algorithm is used strategically to predict which model would be economical (or have the least inventory cost) with continuously varying demand and other inventory attributes.

The ML-based CART algorithm has rarely been seen to provide logical assistance to inventory practitioners in making wise-decision, while selecting inventory control models in dynamic batch-type production systems.

This paper aims to identify barriers toward the adoption of blockchain (BC) technology in Indian health-care industry and also examines the significant issues of BC applications in health-care industry.

The barriers of the study are identified by two phases including the review of literature and semistructured interviews with hospital staff and administration operating in India. The experts (N = 15) are being taken from top-level management, IT experts and patients from the hospitals. The study implemented integrated total interpretative structural modeling-FUZZY-Cross-impact matrix multiplication applied to classification (TISM-FUZZY-MICMAC) methods for identifying the interrelationship among the barriers.

A total of 15 barriers have been determined in the Indian health-care industry through discussion with the selected experts. TISM is applied to develop multilevel structure for BC barriers. Further, FUZZY-MICMAC has been used to compute driving and dependent barriers. The findings suggest that low awareness related to legal issues and low support from high level of management have maximum driving power.

The present study applies multicriterion approach to identify the limited barriers in BC adoption in health care. Future studies may develop the relationship and mark down the steps for implementation of BC in health-care setting of a developing economy. Empirical study can be conducted to verify the results along with selected case studies.

The present study identifies the BC adoption barriers in health-care industry. The study examines the pertinent issues in context to major support required, bottlenecks in adoption, key benefits of adoption planning and activities. The technology adoption practices are expected to provide applications such as distributed, secured medical and clinical data and patient centric systems that will enhance the efficiency of the health-care industry.

The study is among few primary studies that identify and analyze the BC adoption in health-care industry.

In the developing field of nano-materials synthesis, copper oxide nanoparticles (NPs) are deemed to be one of the most significant transition metal oxides because of their intriguing characteristics. Its synthesis employing green chemistry principles has become a key source for next-generation antibiotics attributed to its features such as environmental friendliness, ease of use and affordability. Because they are more environmentally benign, plants have been employed to create metallic NPs. These plant extracts serve as capping, stabilising or hydrolytic agents and enable a regulated synthesis as well.

Organic chemical solvents are harmful and entail intense conditions during nanoparticle synthesis. The copper oxide NPs (CuO-NPs) synthesised by employing the green chemistry principle showed potential antitumor properties. Green synthesised CuO-NPs are regarded to be a strong contender for applications in the pharmacological, biomedical and environmental fields.

The aim of this study is to evaluate the anticancer potential of CuO-NPs plant extracts to isolate and characterise the active anticancer principles as well as to yield more effective, affordable, and safer cancer therapies.

This review article highlights the copper oxide nanoparticle's biomedical applications such as anticancer, antimicrobial, dental and drug delivery properties, future research perspectives and direction are also discussed.