Search results

Mauritius is a Small Island Development State (SIDS) with limited resources, and it has been witnessed that many containers used for storing household and industrial products are made from plastic. When discarded as waste, those plastic containers pose a serious environmental and economic challenge for Mauritius. Moreover, landfill space is getting increasingly scarce, and plastic waste is contaminating both land and water. Therefore, it is of the utmost necessity to develop solutions for Mauritius' plastic wastes. Due to its abundance and accessibility, plastic waste is a promising material for recycling and energy production. One potential solution is the use of machine learning and artificial intelligence (AI) to predict household plastic consumption, allowing policymakers to design effective strategies and initiatives to reduce plastic waste. Such information is a critical component to be able to efficiently plan for the collection and routing of trucks when collecting recyclable plastics. The development of new strategies for the recycling of plastic waste and development of new industry can address the import and export potential of the country to achieve self-sustainability as well as contribute to reduction in plastic pollution and amount of waste landfilled. These plastics can thereafter be used effectively for recycling and for the making of 3D printing filaments which fall under the SDGs 9 (Industry, Innovation and Infrastructure) and 12 (Responsible consumption and production).

Companies allowing employees to self-report business expenses face the risk of expense fraud because some occasionally engage in dishonest behavior to receive reimbursements for their use. Drawing on the technology acceptance model, this study aims to investigate the effects of perceived usefulness, perceived ease of use and perceived security on the trust in e-reimbursement systems and the relationship with honest disclosure intention.

A self-administered questionnaire was distributed to 254 respondents, with the partial least squares structural equation modeling used to analyze the data.

The findings showed that perceived security and perceived usefulness explained trust in e-reimbursement systems, whereas perceived ease of use had no significant effect on it. Corporate governance and trust in e-reimbursement systems have a positive relationship with whistleblowing intention. At the same time, corporate governance mediates the relationship between trust in e-reimbursement systems and honest disclosure intention.

This study sheds light on using e-reimbursement systems within organizations to prevent fraudulent reimbursements and offers recommendations to management on enhancing employees’ intention to engage in honest disclosure behavior through e-reimbursement systems.

Supplier evaluation and selection is an essential (multi-criteria decision-making) MCDM process that considers qualitative and quantitative factors. This research work attempts to use a MCDM technique based on merging fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS) and Quality Function Deployment (QFD) ideas. The study attempts to find the supplier's attributes (HOWs) to accomplish its goals after determining the product's characteristics to suit the company's needs (WHATs).

The proposed research methodology comprises the following four steps: Step 1: Determine the product purchase requirements (“WHATs”) and those pertinent to supplier evaluation (“HOWs”). In Step 2, the relative importance of the “WHAT-HOW” correlation scores is determined and also the resulting weights of “HOWs”. In Step 3, linguistic evaluations of possible suppliers in comparison to subjective criteria are given to the decision-makers. Step 4 combines the QFD and F-TOPSIS techniques to select suppliers.

A fuzzy MCDM method based on fusing and integrating fuzzy information and QFD is presented to solve the drawbacks of conventional decision-making strategies used in supplier selection. Using the F-TOPSIS method, fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS), the relative closeness coefficient values for all alternatives are computed. The suppliers are ranked by relating the closeness of coefficient values. This method permits the combination of ambiguous and subjective data expressed as fuzzy-defined integers or linguistic variables.

QFD and TOPSIS, two widely used approaches, are combined in this article to rank and evaluate suppliers based on the traits that the suppliers choose to prioritize. This study demonstrates that the method employed could address multiple-criteria decision-making scenarios in a computationally efficient manner. The effectiveness and applicability of the method are illustrated using an example.

Managing diversity requires an understanding of culture. The majority of businesses have realised that competitiveness no longer stems from formal organisational structures but rather from the mindsets, competencies, and functioning of individuals who create, develop, and support the organisation and who frequently come from different cultural backgrounds. Understanding the essence of a culture, its components, variations, and how all these things effect the business and the managerial process is very beneficial for international managers. Businesses in global value chains need cross-cultural management practices to obtain a competitive advantage. Global value chains make it possible to benefit from the comparative advantages of other nations, and without cross-cultural management, these multinational corporations would be unable to carry on with their business operations. Although there are many explanations on global value chains in the literature, there is no study on the effect of different cultures in value chain management and how different cultures can be managed in global value chains.

In this chapter, the definition of the concept of culture, which is comprehensive and crucial in managing differences, will be depicted. Then, the concept of cross-cultural management will be emphasised and what cross-cultural management means and why and to what extent it is important will be explained. In addition, the impact of cross-cultural management in the inclusive global value chain will be discussed, emphasising the value chain analysis, how it emerged, its basic concepts, and its importance in the international context.

This study aims to investigate the key determinants predicting users’ behavioural intention (BI) in adopting mobile payment (m-payment) in the new normal era.

The mobile technology acceptance model (MTAM) was extended through attitudes, perceived trust, perceived risk and personal innovativeness (PI) with government support (GS) functioning as a moderator. A total of 245 valid responses were gathered from Malaysian m-payment users with purposive sampling and subsequently evaluated through partial least square-structural equation modelling.

Mobile usefulness and PI significantly predicted user BI to use m-payment. Based on the moderation analysis, GS strengthened attitude-based impacts on BI towards m-payment adoption.

The empirical outcomes provide stakeholders with pivotal implications to develop holistic policies and strategies that potentially catalyse m-payment usage in the new normal era.

This research expands the current body of knowledge by assessing the factors impacting m-payment usage intention in the new normal era. The four aforementioned MTAM elements and GS (moderator) were recommended to boost model workability and offer novel evidence from a distinct viewpoint.

El objetivo de este estudio es investigar los determinantes clave que predicen la intención de comportamiento de los usuarios a la hora de adoptar el pago por móvil (m-payment) en la nueva era normal.

El modelo de aceptación de la tecnología móvil (MTAM) se amplió a través de las actitudes, la confianza percibida, el riesgo percibido y la capacidad de innovación personal, con el apoyo gubernamental como moderador. Se recogió un total de 245 respuestas válidas de usuarios malasios de pago por móvil mediante muestreo intencionado y se evaluó posteriormente mediante modelización de ecuaciones estructurales por mínimos cuadrados parciales (PLS-SEM).

La utilidad del móvil y la capacidad de innovación personal predijeron significativamente la intención de los usuarios de utilizar el pago por móvil. Según el análisis de moderación, el apoyo gubernamental reforzó los efectos basados en la actitud sobre la intención conductual de adoptar el pago por móvil.

Los resultados empíricos proporcionan a las partes interesadas implicaciones fundamentales para desarrollar políticas y estrategias holísticas que catalicen potencialmente el uso del pago móvil en la nueva era de la normalidad.

Esta investigación amplía el corpus actual de conocimientos al evaluar los factores que influyen en la intención de uso del pago por móvil en la nueva era normal. Se recomiendan los cuatro elementos MTAM mencionados y el apoyo gubernamental (moderador) para impulsar la viabilidad del modelo y ofrecer pruebas novedosas desde un punto de vista distinto.

本研究旨在探讨新常态时代用户使用移动支付（m-payment）行为意向的主要决定因素。

通过态度、感知信任、感知风险和个人创新能力, 并以政府支持作为调节因素, 对移动技术接受模型（MTAM）进行了扩展。通过有目的的抽样, 从马来西亚移动支付用户中收集了 245 份有效回复, 随后通过偏最小二乘法结构方程模型（PLS-SEM）进行了评估。

移动实用性和个人创新性可显著预测用户使用移动支付的行为意向。根据调节分析, 政府支持加强了态度对采用移动支付的行为意向的影响。

实证研究的结果为利益相关者提供了重要的启示, 有助于他们制定全面的政策和战略, 在新常态时代促进移动支付的使用。

本研究通过评估新常态时代影响移动支付使用意向的因素, 拓展了现有的知识体系。研究推荐了上述四个 MTAM 要素和政府支持（调节器）, 以提高模型的可操作性, 并从一个独特的视角提供了新的证据。

Single-shot multi-category clothing recognition and retrieval play a crucial role in online searching and offline settlement scenarios. Existing clothing recognition methods based on RGBD clothing images often suffer from high-dimensional feature representations, leading to compromised performance and efficiency.

To address this issue, this paper proposes a novel method called Manifold Embedded Discriminative Feature Selection (MEDFS) to select global and local features, thereby reducing the dimensionality of the feature representation and improving performance. Specifically, by combining three global features and three local features, a low-dimensional embedding is constructed to capture the correlations between features and categories. The MEDFS method designs an optimization framework utilizing manifold mapping and sparse regularization to achieve feature selection. The optimization objective is solved using an alternating iterative strategy, ensuring convergence.

Empirical studies conducted on a publicly available RGBD clothing image dataset demonstrate that the proposed MEDFS method achieves highly competitive clothing classification performance while maintaining efficiency in clothing recognition and retrieval.

This paper introduces a novel approach for multi-category clothing recognition and retrieval, incorporating the selection of global and local features. The proposed method holds potential for practical applications in real-world clothing scenarios.

Voice assistant technology represents one of the most radical artificial intelligence innovations. Drawing on the processing fluency theory and consumer learning literature, this study aims to explore how consumer acceptance of new products is influenced by voice assistant function (VAF), along with the impacts of role clarity and learning modality.

Four between-subjects experimental studies were conducted. Study 1 tested the main effect of VAF on consumer acceptance. Study 2 included role clarity as a mediator between VAF and consumer acceptance. Study 3 examined the moderation effect of learning modality and contrasted the effectiveness of experiential and verbal learning in helping increase consumer acceptance. Study 4, as a post hoc study, tested serial mediations to validate whether processing fluency was indeed the mechanism explaining the indirect relationship between VAF and consumer acceptance via role clarity.

The negative impact of VAF on consumer acceptance was demonstrated in all four studies. Studies 2 and 3 showed VAF decreased role clarity which further influenced consumer acceptance. Moreover, Study 3 evidenced that experiential learning was more effective than verbal learning in increasing consumer acceptance of voice-assisted products via role clarity. Study 4 demonstrated that VAF decreased role clarity, which in turn decreased processing fluency, leading to lower consumer acceptance.

This research views the usage of voice-assisted products as a coproduction process between consumers and the VAF. Accordingly, findings provide novel insights into processing fluency of tasks assisted by VAF through the lens of role clarity and learning modality, which enriches the understanding of potential barriers and opportunities for consumers to accept voice-assisted products.

The environmental performance of organizations has come under public policy limelight since the phenomenal increase of natural resource degradation and industrial waste. Thus, green concepts have been put forward, but the implementation of green practices faces many barriers and challenges. These barriers require attention as organizational practices are negatively affecting the environment leading to global warming and climate change. Therefore, this chapter systematically identifies four internal barriers including inadequate management commitment and support, insufficient technology competence and infrastructure, financial constraints, the uncertainty of economic benefits, and eight sub barriers within an organization concerning green concepts implementation. Moreover, this chapter also identifies four external barriers including lack of stakeholder's interest, inadequate environmental administrative support, scarce academic research, and lack of green collaborative practices, and eight sub barriers outside an organizational context concerning green concept implementation. The barriers in this research were identified by reviewing the existing literature on the topic. This chapter advances the green literature by identifying multiple barriers and challenges to the successful implementation of green concepts in organizations. This is of significance as if these barriers are tackled strategically, it would reduce environmental degradation problems and help make financial gains. Moreover, this research can help managers understand the key barriers to green concept implementation and provide guidance to them when attempting to implement green practices in their organizations. This research would also motivate researchers to extend further investigation on how to overcome such barriers and find out strategies to mitigate the barriers to green concept implementation to effectively address environmental issues.

The aim of this study is to investigate the impact of integration capabilities on reverse supply chain (RSC) adoption and, consequently, RSCs' effectiveness. Thus, supply chain (SC) integration capabilities and their types in relation to internal, supplier and customer integration capabilities are investigated.

In this paper a quantitative survey was conducted with Malaysian manufacturers with a certified the International Organization for Standardization (ISO) 14001 environmental management system. The entire population was utilized through census sampling; 150 useable survey responses were received. The partial least squares technique was used for the data analysis.

The results indicate that internal integration improves external integration. In addition, supplier and customer integration have a positive direct effect on the adoption of RSC activities. Though internal integration has no significant direct effect on the adoption of RSC activities, it has an indirect impact through both supplier integrative capabilities and customer integrative capabilities.

The findings of this study suggest that the managers of manufacturers whose internal integrative capabilities are the base and whose SC integrative capabilities and external integrative capabilities are reinforcing SC integrative capabilities should adopt RSC activities.

The paper offers in-depth insight into this issue and has shed light on the ambiguities in the literature regarding the role of SC integration in RSC adoption.

There is evidence in the literature suggesting the usage of performance measurement framework (PMF) has a positive impact on organisational performance. This is in line with resource based view (RBV) theory, which argues attaining competitive advantage through internal resources and capabilities. In this regard, PMF can be viewed as a “resource” that can be explored in enabling organisational performance. This paper is aimed at developing PMF for the oil and gas supply chain (SC) as a resource and strategic capability.

Drawing on RBV theory, a questionnaire survey was designed based on prior literature review and exploratory interview with five SC experts. Following this, the questionnaires were distributed to 550 companies in the UK and 120 companies in Malaysia, which resulted in 15% overall response rate.

This study presents the prevalence of performance measures (PM) for the oil and gas industry based on the level of importance. It also reveals the impact of the usage of PMF on overall organisational performance. In addition, it identifies the challenges in managing SC performance and factors to be considered in choosing PM.

This study identifies the challenges in managing SC performance and establishes distinctive factors to consider when choosing PM in the oil and gas SC.