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This research focuses on the Metaverse's evolving trend and the potential application of blockchain technology in the accounting of virtual assets in this digital domain. The Metaverse introduces a new economy in which users may earn real-world revenue through virtual activities, necessitating the need for efficient and dependable virtual asset accounting. Blockchain technology, with its decentralized and immutable record, appears to be a viable answer to these problems. This chapter discusses the present status of blockchain technology for accounting for virtual assets in the Metaverse as well as its potential role for businesses and the economy. It also determines the technology's issues and limits and makes recommendations for further development. The findings indicate that blockchain technology has the potential to transform virtual asset accounting in the Metaverse by improving security, transparency, and consistency. However, scalability and legal/regulatory issues must be overcome before it can completely achieve its promise. Accounting experts, developers, and stakeholders interested in the convergence of blockchain technology and the Metaverse economy will find this chapter useful.

Grounded on brand equity theory and theory of patronage behavior, this study aims to investigate the moderating effect of consumer involvement and shopping situations in the relationship between consumer-based retailer equity (CBRE) and retail patronage behavior.

The data is collected through a self-administered survey of 338 shoppers in the three biggest shopping centers in Pakistan. Moreover, the data is analyzed through multi-nominal (multiple) regression and interactions analysis.

Results revealed a significant effect of CBRE on patronage behavior and confirmed shopping purpose as a boundary condition in the CBRE-retail patronage behavior relationship. However, the study surprisingly reported that this relationship is not moderated by consumers’ involvement.

Considering our focus on CBRE-based retail patronage behavior, the authors contribute to extant marketing/retailing literature that also yields ample openings for further research. The study offers valuable implications for retailers, especially for evaluating consumers’ behaviors.

This study assists retail-brand managers in best comprehending the CBRE-based patronage behavior paves the way for managers to increase retail patronage behavior.

Regardless of the growing comprehension of consumer-based brand equity and patronage behavior in marketing, more needs to be acknowledged about the relationship between CBRE/retail patronage behavior and related variables, as thus examined in this research.

Basado en la teoría del valor de marca y la teoría del comportamiento de patrocinio, este estudio investiga el efecto moderador de la implicación del consumidor y las situaciones de compra en la relación entre el valor del minorista basado en el consumidor (CBRE) y el comportamiento de patrocinio minorista.

Los datos se recogen mediante una encuesta autoadministrada a 338 compradores en los tres mayores centros comerciales de Pakistán. Además, los datos se analizan mediante regresión multinominal (múltiple) y análisis de interacciones.

Los resultados revelaron un efecto significativo del CBRE en el comportamiento de patrocinio y confirmaron el propósito de compra como una condición límite en la relación CBRE-comportamiento de patrocinio minorista. Sin embargo, el estudio informó sorprendentemente de que esta relación no está moderada por la implicación de los consumidores.

Teniendo en cuenta que nos centramos en el comportamiento de patrocinio minorista basado en el CBRE, contribuimos a la literatura existente sobre marketing/minoristas que también ofrece amplias posibilidades para futuras investigaciones. El estudio ofrece valiosas implicaciones para los minoristas, especialmente para evaluar los comportamientos de los consumidores.

El presente estudio ayuda a los gestores de marcas minoristas a comprender mejor el comportamiento de patrocinio basado en la CBRE y allana el camino para que los gestores aumenten el comportamiento de patrocinio minorista.

A pesar de la creciente comprensión de la equidad de marca basada en el consumidor y el comportamiento de patrocinio en marketing, es necesario reconocer más sobre la relación entre el comportamiento de patrocinio basado en la CBRE y las variables relacionadas, como se examinó en esta investigación.

本研究以品牌资产理论和顾客行为理论为基础, 探讨了消费者参与和购物情境在基于消费者的零售商资产（CBRE）与零售顾客行为之间关系中的调节作用。

数据是通过对巴基斯坦三大购物中心的 338 名购物者进行自填式调查收集的。此外, 还通过多项式（多元）回归和交互分析对数据进行了分析。

结果表明, CBRE 对顾客光顾行为有显著影响, 并证实购物目的是 CBRE 与零售顾客光顾行为关系的边界条件。然而, 令人惊讶的是, 研究报告称这种关系并没有受到消费者参与度的调节。

考虑到我们对基于 CBRE 的零售顾客行为的关注, 我们为现有的市场营销/零售文献做出了贡献, 同时也为进一步研究提供了广阔的空间。本研究为零售商提供了宝贵的启示, 尤其是在评估消费者行为方面。

本研究有助于零售品牌管理者更好地理解基于 CBRE 的顾客行为, 为管理者提高零售顾客行为铺平了道路。

尽管市场营销中对基于消费者的品牌资产和顾客行为的理解不断加深, 但仍需进一步认识 CBRE/零售顾客行为与相关变量之间的关系, 正如本研究中所探讨的那样。

In recent times, reverse logistics (RL) is gaining significant traction in various automobile industries to recapture returned vehicles’ value. A good RL program can lower manufacturing costs, establish a green supply chain, enhance customer satisfaction and provide a competitive advantage. However, reducing disruptions and increasing operational efficiency in the automobile RL requires implementing innovative technology to improve information flow and security. Thus, this manuscript aims to examine the hurdles in automobile RL activities and how they can be effectively tackled by blockchain technology (BCT). Merging BCT and RL provides the entire automobile industry a chance to generate value for its consumers through effective vehicle return policies, manufacturing cost reduction, maintenance records tracking, administration of vehicle information and a clear payment record of insurance contracts.

This research is presented in three stages to accomplish the task. First, previous literature and experts' opinions are examined to highlight certain factors that are an aggravation to BCT implementation. Next, this study proposed an interval-valued intuitionistic fuzzy set (IVIFS) – decision-making trial and evaluation laboratory (DEMATEL) with Choquet integral framework for computing and analyzing the comparative results of factor interrelationships. Finally, the causal outline diagrams are plotted to determine the influence of factors on one another for BCT implementation in automobile RL.

This study has categorized the barriers to BCT implementation into five major factors – operational and strategical, technical, knowledge and behavioral, financial and infrastructural, and government rules and regulations. The results revealed that disreputable technology, low-bearing capacity of IT systems and operational inefficiency are the most significant factors to be dealt with by automobile industry professionals for finer and enhanced RL processes utilizing BCT. The most noticeable advantage of BCT is its enormous amount of data, permitting automobile RL to develop client experience through real-time data insights.

This study reveals several factors that are hindering the implementation of BCT in RL activities of the automobile industry. The results can assist experts and policymakers improve their existing decision-making systems while making an effort to implement BCT into the automobile industry's RL activities.

Although there are several studies on the benefits of BCT in RL and the adoption of BCT in the automobile industry, individually, none have explicated the use of BCT in automobile RL. This is also the first kind of study that has used IVIFS-DEMATEL with the Choquet integral framework for computing and analyzing the comparative results of factor interrelationships hindering BCT implementation in automobile RL activities.

This study examines the influence of consumer skepticism on cause-related marketing (CRM) campaign participation intentions of Generation Z consumers from emerging market perspective. This study was undertaken due to the paucity of relevant literature in the public domain to directly investigate whether and how consumers' skepticism affects CRM participation intentions, specifically in the luxury retailing context.

A survey was conducted among 552 Generation Z consumers and path analysis was used to examine the direct and indirect effects of skepticism. The mediation and moderation analysis was used to explore and test the authors' hypotheses via partial least squares structural equation modeling (PLS SEM).

The authors' findings provide empirical evidence that corporate social responsibility, religiosity and cause involvement positively affects consumer participation intentions, and this link is also established indirectly through skepticism toward the CRM campaign. These findings provide novel theoretical contributions by establishing skepticism's complex role in determining the CRM participation intention in the Generation Z consumers' context. This study further demonstrates the moderating effect of gender and luxury store format on consumer skepticism and CRM participation intentions.

The Generation z group will represent a quarter of the Asia–Pacific region's population by 2025. However, little is known about Generation z consumers' CRM participation intentions. This research would help practitioners, including luxury retailers, CRM managers and advertising professionals, to effectively design CRM campaigns. The paper contributes by highlighting the theoretical implications and managerial implications based on the current findings in the emerging market context.

This study aims to explore the role customer satisfaction play in mediating the nexus between commitment, trust, relative dependence and customer loyalty from an emerging market context under a business-to-business (B2B) setting.

The study was a descriptive survey, and using convenience sampling technique, questionnaires were used to gather data from 356 businesses that were distributors of Guinness Ghana Company Limited. Partial least squares structural equation modeling was used to test the proposed hypotheses for this study, and macro-PROCESS was performed to test the mediating effect of customer satisfaction.

The findings show that relative dependence had the most considerable significant and positive impact on B2B partners satisfaction, followed by commitment and trust, respectively. A positive and significant relationship was also found between B2B firms’ satisfaction and loyalty. The result also indicates that customer satisfaction mediates the relationship between commitment, trust, relative dependence and B2B loyalty.

Practitioners can manipulate specific relative dependence, commitment and trust features to increase customer satisfaction with their firm’s services, thus ensuring longer-term customer loyalty.

Drawing on the social exchange theory, this study provides a more profound perspective focusing on an emerging market context, by examining from a B2B setting the significance of commitment, trust, relative dependence and B2B partners satisfaction on loyalty.

The purpose of this study is to consolidate the existing literature on small retail and develop a conceptual framework using thematic analysis.

The relevant set of 224 articles has been obtained from the Scopus database by applying the PRISMA framework. Bibliometric analysis has been performed using Biblioshiny in Bibliometrix and VOSviewer.

Four major themes have been identified within the conceptual structure of the small retail domain, and a conceptual framework has been developed using the interlinkages within the themes. The intellectual structure of the domain has been explored using citation analysis, co-citation analysis and bibliographic coupling. Future research directions are also identified and documented based on the thematic analysis and overall consolidation of the literature.

This is perhaps one of the first attempts to consolidate the published literature on small retail using bibliometric analysis.

The purpose of this study is to implement lean six sigma (LSS) methodology to improve the admission process in a higher education institute (HEI).

In this study, case study research methodology is adopted and implemented through an LSS define-measure-analyze-improve-control (DMAIC) framework.

The preliminary investigation showed that the completion of the whole admission process of a new student takes an average of 88 min, which is equivalent to a sigma level of about 0.71 based on the targeted admission cycle time of 60 min. The implementation of the proposed LSS approach increased the sigma level from 0.71 to 2.57, which indicates a reduction in the mean admission cycle time by around 55%. This substantial improvement is expected not only to provide an efficient admission process but also to enhance the satisfaction of students and employees and increase the reputation of the HEI to a significant level.

In this study, the sample size used in the analysis is considered small. In addition, the effectiveness of the proposed approach is investigated using a discrete event simulation with a single-case study, which may limit generalization of the results. However, this study can provide useful guidance for further research for the generalization of the results to wider scopes in terms of different sectors of HEIs and geographical locations.

This study uses several statistical process control tools and techniques through a LSS DMAIC framework to identify and element the root causes of the long admission cycle time at a HEI. The approach followed, and the lessons learned, as documented in the study, can be of a great benefit in improving different sectors of HEIs.

This study is one of the few attempts to implement LSS in HEIs to improve the administrative process so that better-quality services can be provided to customers, such as students and guardians. The project is implemented by a group of undergraduate students as a part of their senior design project, which paves the way for involving students in future LSS projects in HEIs. This study is expected to help to improve understanding of how LSS methodology can be implemented in solving quality-related problems in HEIs and to offer valuable insights for both academics and practitioners.

The application of synthetic dyestuffs in the dyeing and printing industries has been criticized because of the introduction of contaminants into the environment. With time, the increasing international awareness of environment and ecology preservation has led to the industry’s attention towards natural dyes and their efficient usage compared to synthetic counterparts. Because the need for “Green” goods and services are rising public awareness, this paper aims to use a banana bio-resource waste to dye cotton fabric.

Factorial design with three variables, including parts of a banana plant, combination of alkalis and application temperature at three different levels, was studied to identify a significant correlation between the effect of these variables on the colour strength and fastnesses of the dyed cotton fabrics.

Dyeing samples achieved with various parts of banana are found to offer significant colour strength and a good wash and rub fastness. Experimental design analysis helped to formulate a standard workable dyeing recipe with the minimum use of resources exhibiting reasonably good wash and rub fastness.

This dyeing technique is novel and can be found useful for partially replacing synthetic dyes with natural colourants possessing good washing and rubbing fastness.

Bank creditworthiness refers to the evaluation of a bank’s ability to meet its financial obligations. It is an assessment of the bank’s financial health, stability and capacity to manage risks. This paper aims to investigate the credit rating patterns that are crucial for assessing creditworthiness of the Islamic banks, thereby evaluating the stability of their industry.

Three distinct machine learning algorithms are exploited and evaluated for the desired objective. This research initially uses the decision tree machine learning algorithm as a base learner conducting an in-depth comparison with the ensemble decision tree and Random Forest. Subsequently, the Apriori algorithm is deployed to uncover the most significant attributes impacting a bank’s credit rating. To appraise the previously elucidated models, a ten-fold cross-validation method is applied. This method involves segmenting the data sets into ten folds, with nine used for training and one for testing alternatively ten times changeable. This approach aims to mitigate any potential biases that could arise during the learning and training phases. Following this process, the accuracy is assessed and depicted in a confusion matrix as outlined in the methodology section.

The findings of this investigation reveal that the Random Forest machine learning algorithm superperforms others, achieving an impressive 90.5% accuracy in predicting credit ratings. Notably, our research sheds light on the significance of the loan-to-deposit ratio as a primary attribute affecting credit rating predictions. Moreover, this study uncovers additional pivotal banking features that intensely impact the measurements under study. This paper’s findings provide evidence that the loan-to-deposit ratio looks to be the purest bank attribute that affects credit rating prediction. In addition, deposit-to-assets ratio and profit sharing investment account ratio criteria are found to be effective in credit rating prediction and the ownership structure criterion came to be viewed as one of the essential bank attributes in credit rating prediction.

These findings contribute significant evidence to the understanding of attributes that strongly influence credit rating predictions within the banking sector. This study uniquely contributes by uncovering patterns that have not been previously documented in the literature, broadening our understanding in this field.

Everyone is extremely concerned about environmental protection and health safety due to the rise in living standards. Plant-derived natural dyes have garnered much industrial attention in food, pharmaceutical, textile, cosmetics, etc. owing to their health and environmental benefits. The present study aims to focus on the elimination of the use of synthetic dyes and provides brief information about natural dyes, their sources, extraction procedures with characterization and various advantages and disadvantages.

In producing natural colors, extraction and purification are essential steps. Various conventional methods used till date have a low yield, as these consume a lot of solvent volume, time, labor and energy or may destroy the coloring behavior of the actual molecules. The establishment of proper characterization and certification protocols for natural dyes would improve the yielding of natural dyes and benefit both producers and users.

However, scientists have found modern extraction methods to obtain maximum color yield. They are also modifying the fabric surface to appraise its uptake behavior of color. Various extraction techniques such as solvent, aqueous, enzymatic and fermentation and extraction with microwave or ultrasonic energy, supercritical fluid extraction and alkaline or acid extraction are currently available for these natural dyes and are summarized in the present review article.

If natural dye availability can be increased by the different extraction measures and the cost of purified dyes can be brought down with a proper certification mechanism, there is a wide scope for the adoption of these dyes by small-scale dyeing units.