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Financial institutions, including banks, have their responsibilities to contribute towards the preservation of the environment. Green banking is an emerging concept that involves eco-friendly initiatives by banks and although Mauritius lacks a comprehensive regulatory framework for green banking, there exists a few green regulations and guidelines. Accordingly, the purpose of this study is to critically analyse the existing legal and regulatory framework on green banking in Mauritius. It is expected that this study will showcase the need for some more robust and proper green banking legal and regulatory framework in Mauritius.

To achieve the research objective, a black-letter analysis is used to analyse the existing regulatory framework in Mauritius. Moreover, a comparative analysis of the current legal frameworks on green banking in countries like Bangladesh, Indonesia, Pakistan and the UK is carried out.

This study recommends the establishment of a guideline or legal framework for green banking, a Sustainable Finance Policy, a legal binding framework for issuance of bonds, adoption of a Task Force on Climate-related Financial Disclosure guideline, compulsory environmental reporting and disclosures and a green standard rating.

To the best of the authors’ knowledge, this research is among the first literature on green banking laws, especially in the context of a developing country being Mauritius, and it is anticipated that the findings are of use not only to academics but also to the wider community in general.

This study primarily aims to develop and solve an enhanced optimisation model for an assembly product multi-period inbound inventory routing problem (IRP). The many-to-one (inbound) model considers the bill of materials (BOM), supply failure risks (SFR) and customer demand uncertainty. The secondary objective is to study the influence of potential time-dependent model variables on the overall supply network costs based on a full factorial design of experiments (DOE).

A five-step solution approach is proposed to derive the optimal inventory levels, best sourcing strategy and vehicle route plans for a multi-period discrete manufacturing product assembly IRP. The proposed approach considers an optimal risk mitigation strategy by considering less risk-prone suppliers to deliver the required components in a specific period. A mixed-integer linear programming formulation was solved to derive the optimal supply network costs.

The simulation results indicate that lower demand variation, lower component price and higher supply capacity can provide superior cost performance for an inbound supply network. The results also demonstrate that increasing supply capacity does not necessarily decrease product shortages. However, when demand variation is high, product shortages are reduced at the expense of the supply network cost.

A two-echelon supply network for a single assembled discrete product with homogeneous vehicle fleet availability was considered in this study.

The proposed multi-period inbound IRP model considers realistic SFR, customer demand uncertainties and product assembly requirements based on a specific BOM. The mathematical model includes various practical aspects, such as supply capacity constraints, supplier management costs and target service-level requirements. A sensitivity analysis based on a full factorial DOE provides new insights that can aid practitioners in real-life decision-making.

The article addresses the optimization of safety stock service levels for parts in a repair kit. The work was undertaken to assist a public transit entity that stores thousands of parts used to repair equipment acquired over many decades. Demand is intermittent, procurement lead times are long, and the total inventory investment is significant.

Demand exists for repair kits, and a repair cannot start until all required parts are available. The cost model includes holding cost to carry the part being modeled as well as shortage cost that consists of the holding cost to carry all other repair kit parts for the duration of the part’s lead time. The model combines deterministic and stochastic approaches by assuming a fixed ordering cycle with Poisson demand.

The results show that optimal service levels vary as a function of repair demand rate, part lead time, and cost of the part as a percentage of the total part cost for the repair kit. Optimal service levels are higher for inexpensive parts and lower for expensive parts, although the precise levels are impacted by repair demand and part lead time.

The proposed model can impact society by improving the operational performance and efficiency of public transit systems, by ensuring that home repair technicians will be prepared for repair tasks, and by reducing the environmental impact of electronic waste consistent with the right-to-repair movement.

The optimization model is unique because (1) it quantifies shortage cost as the cost of unnecessary holding other parts in the repair kit during the shortage time, and (2) it determines a unique service level for each part in a repair kit bases on its lead time, its unit cost, and the total cost of all parts in the repair kit. Results will be counter-intuitive for many inventory managers who would assume that more critical parts should have higher service levels.

Output from the Irish Dairy Industry has grown rapidly since the abolition of quotas in 2015, with processors investing heavily in capacity expansion to deal with the extra milk volumes. Further capacity gains may be achieved by extending the processing season into the winter, a key enabler for which being the reduction of duration of the winter maintenance overhaul period. This paper aims to investigate if Lean Six Sigma tools and techniques can be used to enhance operational maintenance performance, thereby releasing additional processing capacity.

Combining the Six-Sigma Define, Measure, Analyse, Improve, Control (DMAIC) methodology and the structured approach of Turnaround Maintenance (TAM) widely used in process industries creates a novel hybrid model that promises substantial improvement in maintenance overhaul execution. This paper presents a case study applying the DMAIC/TAM model to Ireland’s largest dairy processing site to optimise the annual maintenance shutdown. The objective was to deliver a 30% reduction in the duration of the overhaul, enabling an extension of the processing season.

Application of the DMAIC/TAM hybrid resulted in process enhancements, employee engagement and a clear roadmap for the operations team. Project goals were delivered, and original objectives exceeded, resulting in €8.9m additional value to the business and a reduction of 36% in the duration of the overhaul.

The results demonstrate that the model provides a structure that promotes systematic working and a continuous improvement focus that can have substantial benefits for wider industry. Opportunities for further model refinement were identified and will enhance performance in subsequent overhauls.

To the best of the authors’ knowledge, this is the first time that the structure and tools of DMAIC and TAM have been combined into a hybrid methodology and applied in an Irish industrial setting.

The purpose of this paper is to assess the current legal framework on money laundering control in the insurance sector. Essentially, this examination is premised on the interrogation of whether it is still appropriate for Mauritius to apply such stringent, opaque and unyielding Anti-Money Laundering/Combating Financing of Terrorism norms and rules on general insurance when developed nations such as the UK and Singapore have done away with them for a more effective combat against money laundering. It would also be assessed why the financial services commission (FSC) is not able to draw inspiration from its British and Singaporean counterparts in fighting money laundering more effectively.

This paper uses the doctrinal legal research methodology which is colloquially described as “black-letter law” approach. It is backed up by a contextual legal analysis that is based on an analysis of relevant legal provisions. It relies ground experience from the insurance industry through the experience of the authors. A comparative approach is used with Singapore and the UK as case studies given that there are significant commonalities to the Mauritian jurisdiction as well as useful differences.

It is observed that a move towards a de-regulation of the legal framework on money laundering in the insurance sector with a more relaxed approach is more effective for the Mauritian insurance sector. Evidence is drawn from the Singaporean and British models. A re-structuring of the FSC of Mauritius is also warranted for such an approach to be adopted.

This paper is among the first academic contribution that proposes a de-regulation and the adoption of a relaxed approach of and by the Mauritian Insurance Industry for a more effective combat against money laundering. It serves as a legal foundational basis for further research in this direction.

This study aims to examine investors' reactions to bad financial news (IRBFN) based on complex financial accounting disclosures (CFAD) as well as how investors' herding behavior influences investor reactions in United Arab Emirates (UAE) project-based organizations (PBOs).

The primary data collection was furnished via online questionnaires, and 310 completed questionnaires were analyzed using structural equation modelling (SEM), moderation analysis, multiple regression simulations and path analysis.

The study shows that four out of the five CFAD dimensions observed – investors’ relations (IR), board and management structure, transparency disclosure and other disclosure channels – have a direct influence on investor's reactions to bad financial news, with the exception of “external auditing and audit service”. In addition, investor herding has a moderation impact on the relationship between CFAD and IRBFN.

There is a possibility that the broad view of the results may be limited by the size of the research sample. The paper's findings should therefore be authenticated at an intercontinental level with the same conceptual framework in other nations.

The purpose of modeling stakeholders' decision-making process is to improve their decisions and to control their reactions that may negatively affect PBOs in the UAE.

This research contributes to planned behavior theory and agency theory in the UAE context, both of which are empirically tested.

The unstable labor productivity and periodic planning method cause barriers to improving construction logistics management. This paper aims to explore a demand-driven mechanism for efficient construction logistics planning to record the material consumption, report the real-time demand and trigger material replenishment from off-site to on-site, which is aided by Building Information Modeling (BIM) and the Kanban technique.

This paper follows the design science research (DSR) principles to propose a system of designing and applying Kanban batch with 4D BIM for construction logistics planning and monitoring. Prototype development with comparative simulation experiments of a river remediation project is conducted to analyze the conventional and Kanban-triggered supply. Two-staged industrial interviews are conducted to guide and evaluate the system design.

The proposed BIM-enabled Kanban system enables construction managers and suppliers to better set integrated on- and off-site targets, report real-time demands and conduct collaborative planning and monitoring. The simulation results present significant site storage and schedule savings applying the BIM-enabled Kanban system. Feedback and constructive suggestions from practitioners are collected via interviews and analyzed for further development.

This paper brings to the limelight the benefits of implementing BIM-enabled demand-driven replenishment to remove waste from the material flow. This paper combines lean production theory with advanced information technology to solve construction logistics management problems.

This paper aims to examine and compare extant literature on the application of multi-criteria decision-making (MCDM) techniques in humanitarian operations (HOs) and humanitarian supply chains (HSCs). It identifies the status of existing research in the field and suggests a roadmap for academicians to undertake further research in HOs and HSCs using MCDM techniques.

The paper systematically reviews the research on MCDM applications in HO and HSC domains from 2011 to 2022, as the field gained traction post-2004 Indian Ocean Tsunami phenomena. In the first step, an exhaustive search for journal articles is conducted using 48 keyword searches. To ensure quality, only those articles published in journals featuring in the first quartile of the Scimago Journal Ranking were selected. A total of 103 peer-reviewed articles were selected for the review and then segregated into different categories for analysis.

The paper highlights insufficient high-quality research in HOs that utilizes MCDM methods. It proposes a roadmap for scholars to enhance the research outcomes by advocating adopting mixed methods. The analysis of various studies revealed a notable absence of contextual reference. A contextual mind map specific to HOs has been developed to assist future research endeavors. This resource can guide researchers in determining the appropriate contextual framework for their studies.

This paper will help practitioners understand the research carried out in the field. The aspiring researchers will identify the gap in the extant research and work on future research directions.

To the best of the authors’ knowledge, this is the first literature review on applying MCDM in HOs and HSCs. It summarises the current status and proposes future research directions.

Despite its significance, research on how attribute framing affects ordering decisions in dual sourcing remains insufficient. Hence, this study investigated the effects of attribute framing in a sourcing task involving certain and uncertain qualities of two suppliers and analysed the role of attention with respect to suppliers' information in framing effects.

The impacts of attribute framing on sourcing decisions were demonstrated in two online between-subject (2 × 2 factorial) experimental studies involving professional samples. Study 2 was an eye-tracking experiment.

In Study 1 (N = 251), participants presented with a “high-quality” rather than a “low-quality” frame made different sourcing decisions, opting for larger percentage of order(s) from a supplier under the “high-quality” frame. This pattern holds true for suppliers who differ in risk. This finding was replicated in Study 2 (N = 129). Attention asymmetry related to the information on supplier quality contributes to this effect. Attention directed towards information regarding the supplier's quality under a positive frame mediated the relationship between attribute framing and sourcing decisions.

Highlighting the positive attributes of a risky supplier is essential when ordering from the risky supplier is an optimal decision. It is advantageous for suppliers to highlight positive rather than negative attributes when describing the quality of their components against others.

This is the first study to examine the effect of attention on the relationship between attribute framing and dual sourcing. This presents a new behavioural perspective wherein managers' attention to information plays a vital role.