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Over energy consumption is one of the causes of global warming and climate change. To deal with this issue, using energy-efficient appliances is strongly encouraged and cultivating consumer loyalty toward energy-efficient appliances is crucial for long-term sustainability. This study investigates the effects of multiple dimensions of perceived value on consumer satisfaction and three outcomes of consumer loyalty (i.e. willingness to pay a premium, repurchase intention and word-of-mouth intention), considering the moderating role of the product category.

Quota sampling based on age and gender and snowball sampling methods were applied to recruit 423 participants for this study. A combination of partial least squares structural equation modeling (PLS-SEM), importance-performance map analysis (IPMA) and necessary condition analysis (NCA) was employed to examine the proposed model.

Functional, price, emotional and environmental values positively impact consumer satisfaction, enhancing the three dimensions of consumer loyalty. The product category moderates the effects of perceived value dimensions on consumer satisfaction. Moreover, the IPMA results highlight that functional value and environmental value are the most essential but underperforming value attributes. The NCA results indicate that social value is a necessary condition for consumer satisfaction.

This study is one of the pioneers in integrating PLS-SEM, IPMA and NCA approaches to comprehensively unpack the relationships between perceived value dimensions, consumer satisfaction and consumer loyalty in the context of energy-efficient appliances. The findings offer theoretical and practical importance for academics, retailers, producers and policymakers to encourage consumer loyalty toward energy-efficient appliances.

A Robo Advisor (RA) is a fully automated investment advisory service. Its development in recent years has been very relevant within the financial industry. Although most RAs comply with most investment principles (diversification, cost efficiency, personalization and contextualization of investment opportunities to the current environment), their need for standardization reduces their ability to find portfolios that fit the investors’ constraints or needs. The main objective of this paper is to analyze the possibility of eliminating this shortcoming of the RA by including new types of financial instruments or generating different investment portfolios.

This study performs a bottleneck analysis of all activities related to the management of financial instruments to detect the most affected activities when incorporating new types of instruments. This study also presents a case study on including fixed-income bonds to increase RA personalization and proposes two types of investment portfolios to promote personalization.

The bottleneck analysis has allowed us to identify that “instrument data validation” and “order management” are the most affected activities if new types of instruments are incorporated. In addition, the liquidity level of financial instruments is a critical variable that must be integrated into an RA.

The results indicate the possibility of designing a new RA with a higher level of personalization. This study helps to understand the difficulties and opportunities when customizing an RA.

This study aims to provide empirical evidence to verify the dimensional structure of artificial intelligence (AI) Chatbot quality and examine the impact of these dimensions on consumer satisfaction and brand advocacy among Gen Z in the fast food industry in Egypt.

The empirical data was obtained with an electronic self-administered survey instrument from 397 young consumers who had prior experience using AI Chatbots across multiple fast food brands in Egypt. Structural equation modeling was used to analyze the formulated hypotheses.

The results showed that AI Chatbot quality dimensions, specifically information authenticity and system compliance, significantly enhance young consumers’ satisfaction. In addition, information authenticity of AI Chatbot quality was observed to wield a significant influence on young consumers’ advocacy. In contrast, an insignificant relationship was noticed between satisfaction and advocacy. Moreover, the mediating role of consumer satisfaction was not established.

Given that Gen Z is more technology savvy and computer literate, marketers and practitioners of fast food brands should invest in AI tools to respond to young consumers’ expectations and improve their perception of their services.

This study uses stimulus-organism-response theory to understand the mediating effect of young consumers’ satisfaction in the relationship between AI Chatbot quality and consumer brand advocacy within the fast food industry. Also, it introduced two novel main constructs of AI Chatbot quality, namely, information authenticity and system compliance.

The purpose of this study is to provide a holistic understanding of the factors that either promote or hinder the adoption of artificial intelligence (AI) in supply chain management (SCM) and operations management (OM). By segmenting the AI lifecycle and examining the interactions between critical success factors and critical failure factors, this study aims to offer predictive insights that can help in proactively managing these factors, ultimately reducing the risk of failure, and facilitating a smoother transition into AI-enabled SCM and OM.

This study develops a knowledge graph model of the AI lifecycle, divided into pre-development, deployment and post-development stages. The methodology combines a comprehensive literature review for ontology extraction and expert surveys to establish relationships among ontologies. Using exploratory factor analysis, composite reliability and average variance extracted ensures the validity of constructed dimensions. Pearson correlation analysis is applied to quantify the strength and significance of relationships between entities, providing metrics for labeling the edges in the resource description framework.

This study identifies 11 dimensions critical for AI integration in SCM and OM: (1) setting clear goals and standards; (2) ensuring accountable AI with leadership-driven strategies; (3) activating leadership to bridge expertise gaps; (4) gaining a competitive edge through expert partnerships and advanced IT infrastructure; (5) improving data quality through customer demand; (6) overcoming AI resistance via awareness of benefits; (7) linking domain knowledge to infrastructure robustness; (8) enhancing stakeholder engagement through effective communication; (9) strengthening AI robustness and change management via training and governance; (10) using key performance indicators-driven reviews for AI performance management; (11) ensuring AI accountability and copyright integrity through governance.

This study enhances decision-making by developing a knowledge graph model that segments the AI lifecycle into pre-development, deployment and post-development stages, introducing a novel approach in SCM and OM research. By incorporating a predictive element that uses knowledge graphs to anticipate outcomes from interactions between ontologies. These insights assist practitioners in making informed decisions about AI use, improving the overall quality of decisions in managing AI integration and ensuring a smoother transition into AI-enabled SCM and OM.

The paper explores the notion of worker voice in terms of its implications for supply chain justice. The paper proposes the value of the recognition perspective on social justice for framing workers’ experiences in global supply chains and identifies opportunities for the advancement of the worker voice agenda with recognition justice in mind.

The paper adopts a conceptual approach to explore the notion of worker voice in supply chains in terms of the recognition perspective on social justice.

Sustainable supply chain management (SSCM) scholarship has considered worker voice in terms of two key paradigms, which we term communication and representation. To address recognition justice for workers in global supply chains, the worker voice agenda must consider designing worker voice mechanisms to close recognition gaps for workers with marginalised identities; the shared responsibilities of supply chain actors to listen alongside the expectation of workers to use their voice; and the expansion of the concept of worker voice to cut across home-work boundaries.

The paper offers conceptual clarity on the emerging notion of worker voice in SSCM and is the first to interrogate the implications of recognition justice for the emergent worker voice agenda. It articulates key opportunities for future research to further operationalise worker voice upon a recognition foundation.

Considering the impact of significant economic and political events, this study investigates the return spillovers and connectedness among eight West African currencies from March 31, 2010, to March 28, 2024. It aims to enhance understanding of the interdependencies within the West African foreign exchange market, providing insights into the region’s risk management and diversification opportunities.

Using the time-varying parameter vector autoregression (TVP-VAR) method, this study analyzes daily exchange rate returns to capture the dynamic spillover effects and connectedness among the selected currencies. This approach identifies key transmitters and receivers of return shocks, reflecting the evolving interactions among the currencies over time.

The results show that the Sierra Leonean Leone, Cape Verdean Escudo, and West African CFA Franc are significant net transmitters of return shocks. At the same time, the Ghana Cedi, Nigerian Naira, Gambian Dalasi, Guinean Franc, and Liberian Dollar are net receivers, with the Gambian Dalasi being the most affected. These findings suggest relatively low regional spillover connectedness, offering favorable diversification opportunities.

This study provides a comprehensive analysis of the interconnectedness of West African currencies, contributing to the limited literature on this region. The findings have practical implications for investors and policymakers in managing foreign exchange risks and designing interventions to stabilize the market.

The main purpose of this study is to test whether ethical financial behavior as a mediator promotes microfinance inclusion and survival of the poor young women microenterprises in rural Uganda.

The methods recommended by Kenny et al. (1998); Shrout and Bolger (2002); MacKinnon et al. (2004); and Preacher and Hayes (2004) were used to establish the existence of non-zero monotonic association between microfinance inclusion and survival through testing the mediating effect of ethical financial behavior in SmartPLS.

The results from the structural equation modeling revealed a significant full mediating effect of ethical financial behavior in the relationship between microfinance inclusion and survival of the poor young women microenterprises. Microfinance inclusion and ethical financial behavior explain 62 % of the variation in survival of the poor young women microenterprises in rural Uganda.

Whereas significant results were obtained from this study, the data were collected only from rural-based poor young women microenterprises located in northern Uganda. Extending the sample to cover the whole country may provide a more representative picture. Besides, it would be useful to compare results across developing countries as this may provide information about the generality of our findings.

The findings from this study can be useful to managers of microfinance institutions in developing countries to adopt practice that can promote financial discipline among rural poor young women microentrepreneurs. Routine financial education and business mentorship can be organized through workshops, trainings and seminars to teach rural poor young women microentrepreneurs how to manage money, especially business loans borrowed from the microfinance institutions to put it into right use. This can help them to meet timely loan repayment to increase access to future microfinance loans.

This study provides the first evidence on the use of the theory of planned behavior (TPB) and theory of reasoned action (TRA) to explain microfinance inclusion of the poor young women microentrepreneurs in rural Uganda. The study uses a blend of TPB and TRA derived from psychology and sociology to explain repayment intention and ethical behaviors of the poor young women borrowers, which determines the microfinance lending cycle to make microcredit available for them to engage in entrepreneurship to come out of poverty to attain wellbeing.

This paper aims to provide a full introduction, new classification, comparison and investigation of the challenges as well as applications of layerless 3D printing, which is one of the industry 4.0 pioneers.

Given the significance and novelty of uniform 3D printing, more than 250 publications were collected and reviewed in an unbiased and clear manner.

As a result, the majority of uniform parts printed in polymer form are known up to this point. In a novel division for better researchers’ comprehension, uniform printing systems were classified into three categories: oxygen inhibition (OI), liquid lubrication (LL) and photon penetration (PP), and each was thoroughly investigated. Furthermore, these three approaches were evaluated in terms of printing speed, precision and accuracy, manufacturing scale and cost.

The parameters of each approach were compared independently, and then a practical comparison was conducted among these three approaches. Finally, a variety of technologies, opportunities, challenges and advantages of each significant method, as well as a future outlook for layerless rapid prototyping, are presented.

Flooding is China’s most frequent and catastrophic natural hazard, causing extensive damage. The aim of this study is to develop a comprehensive assessment of urban flood risk in the Hubei Province of China, focusing on the following three issues: (1) What are the factors that cause floods? (2) To what extent do these factors affect flood risk management? (3) How to build an effective comprehensive assessment system that can be used to reduce flood risk?

This study combines expert opinion and evidence from the extent literature to identify flood risk indicators across four dimensions: disaster risk, susceptibility, exposure and prevention and mitigation. The Criteria Importance Through Intercriteria Correlation (CRITIC) and the Grey Relational Analysis (RA)-based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) decision-making approach were applied to calculate the weighting of factors and develop a model of urban flood risk. Then, ArcGIS software visualizes risk levels and spatial distribution in the cities of Hubei Province; uncertainty analysis verified method accuracy.

The results show that there are significant differences in the level of urban flood risk in Hubei Province, with cities such as Tianmen, Qianjiang, Xiantao and Ezhou being at high risk, while cities such as Shiyan, Xiangyang, Shennongjia, Yichang, Wuhan and Huanggang are at lower flood risk.

The innovative method of combining CRITIC-GRA-TOPSIS reduces the presence of subjective bias found in many other flood risk assessment frameworks. Regional data extraction and uncertainty analysis enhance result reliability, supporting long-term decision-making and urban planning. Overall, the methodological approach developed provides an advanced, highly effective and efficient analysis and visualization of flood risk. This study deepens the understanding of flood risk assessment mechanisms and more broadly supports the development of resilient cities.

Female entrepreneurship remains a critical issue around the globe, particularly in developing economies where they confront various challenges during self-employment. This paper aims to investigate essential opportunities and challenges for Afghan women’s home-based enterprises (WHBEs) that may impact the decision of female entrepreneurs to establish a venture.

The study interviewed women home-based enterprise owners through a predesigned questionnaire to identify the main opportunities and challenges. The Delphi and Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach is employed to analyze casual relationships of the main obstacles confronting WHBEs.

The findings indicate that women home-based enterprise owners utilize substantial opportunities, such as family support and balancing home and business tasks. Challenges include cause and effect groups, while lack of access to finance, insecurity, social restrictions and limited access to digital platforms belong to the cause group. Notably, limited markets, lack of professional knowledge and legal limits have links with the effect group. However, among the identified challenges, legal restrictions remain the highest obstacle, while the lack of access to finance is the lowest challenge in women’s home-based enterprise context.

The cultural and legal barriers that still exist in Afghanistan have made it difficult for researchers to contact female entrepreneurs.

This study fills the gap in investigating casual relationships in an under-researched stream of disadvantaged entrepreneurship, i.e. the WHBE context of female entrepreneurship. It generates value for researchers interested in female entrepreneurship and international organizations that empower women and promote gender equality in developing economies.