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The development of e-grocery allows people to purchase food online and benefit from home delivery service. Nevertheless, a high rate of failed deliveries due to the customer’s absence causes significant loss of logistics efficiency, especially for perishable food. The purpose of this paper is to propose an innovative approach to use customer-related data to optimize e-grocery home delivery. The approach estimates the absence probability of a customer by mining electricity consumption data, in order to improve the success rate of delivery and optimize transportation.

The methodological approach consists of two stages: a data mining stage that estimates absence probabilities, and an optimization stage to optimize transportation.

Computational experiments reveal that the proposed approach could reduce the total travel distance by 3-20 percent, and theoretically increase the success rate of first-round delivery approximately by18-26 percent.

The proposed approach combines two attractive research streams on data mining and transportation planning to provide a solution for e-commerce logistics.

This study gives an insight to e-grocery retailers and carriers on how to use customer-related data to improve home delivery effectiveness and efficiency.

The proposed approach can be used to reduce environmental footprint generated by freight distribution in a city, and to improve customers’ experience on online shopping.

Being an experimental study, this work demonstrates the effectiveness of data-driven innovative solutions to e-grocery home delivery problem. The paper also provides a methodological approach to this line of research.

This article aims to optimise energy use and consumption by integrating Lean Six Sigma methodology with the ISO 50001 energy management system standard in an Irish dairy plant operation.

This work utilised Lean Six Sigma methodology to identify methods to measure and optimise energy consumption. The authors use a single descriptive case study in an Irish dairy as the methodology to explain how DMAIC was applied to reduce energy consumption.

The replacement of heavy oil with liquid natural gas in combination with the new design of steam boilers led to a CO₂ footprint reduction of almost 50%.

A further longitudinal study would be useful to measure and monitor the energy management system progress and carry out more case studies on LSS integration with energy management systems across the dairy industry.

The novelty of this study is the application of LSS in the dairy sector as an enabler of a greater energy-efficient facility, as well as the testing of the DMAIC approach to meet a key objective for ISO 50001 accreditation.

This study aims to assess readiness for climate change mitigation in the Kingdom of Bahrain.

Two stages were followed aiming at understanding the situation related to climate change mitigation in Bahrain and assessing the mitigation readiness. Baseline and mitigation scenarios for the period 2019–2040 were developed using the Low Emissions Analysis Platform software based on historical emissions and energy data for the period 1990–2018. Using the analytic hierarchy process, the mitigation readiness was assessed by 13 experts, and priority areas for mitigation action were identified.

CO₂e emissions are projected to grow continuously. However, no explicit climate change strategy is in place yet. Mitigation is tackled implicitly through energy efficiency and renewable energy initiatives. These initiatives can make 23% reduction in CO₂e emissions by 2040. Adopting additional measures is needed to achieve the recently set emission reduction target of 30% by 2035. The findings revealed potential areas for improving mitigation efforts in Bahrain. Priority areas for mitigation actions, as identified by experts, were mainly related to policy and governance. Focus needs to be paid to the social aspect of climate change mitigation.

Literature on mitigation readiness in developing countries is sparse. Knowledge of the requirements for climate change mitigation and assessment of the country’s performance can prioritize areas for improving mitigation action. Several lessons can be learnt from the case of Bahrain. In addition, the adopted methodology can be applied to other developing or Arab countries at local or institutional levels. However, its application to specific sectors may require adjustments.

Framed within global policy debates over the need for private financial flows to align with the capital requirements of the Paris Agreement, this paper examines UK asset managers in their approaches to disclosing and managing climate risk. This paper identifies and evaluates climate risk management practices among this under-researched investor group in their capacity to address fundamental behavioural obstacles to low-carbon investment.

This paper takes an inductive approach to document analysis, applying content and thematic analysis to the annual disclosures of the 28 largest UK asset managers (by assets under management), including the investment management arms of insurance and pension companies.

The main takeaway from this research is that today’s climate risk management strategies hold potential to effectively address traditionally climate risk-averse investor behaviour and investment processes in the UK asset management context. However, this research finds that the use of environmental, social and governance (ESG) investment strategies to mitigate climate risks is a “grey area” in which climate risk management practices are undefined within broad sustainability and responsible investment agendas. In doing so, this paper invites further research into the extent to which climate risks are considered in ESG investment.

This paper contributes to research in sustainable finance and behavioural finance, by identifying the latest climate risk management techniques used among UK-headquartered asset managers and uniquely evaluating these in their capacity to address barriers to low-carbon investment arising from organisational behaviours and processes.

In this study, the impact of access to electricity on poverty reduction for Botswana is examined using the annual data from 1990 to 2021. The study was motivated by the need to establish if access to electricity could be a panacea on poverty reduction in Botswana. Given that the United Nations Sustainable Development Goals deadline is fast approaching, and Botswana being one of the signatories, is expected to end poverty in all its forms – Goal 1. Establishing the role that electrification plays in poverty alleviation, helps in refocusing Botswana’s poverty alleviation strategies on factors that have high impact on poverty. The main objective of this study, therefore, is to investigate the relationship between poverty alleviation and access to electricity in Botswana.

The study uses the autoregressive distributed lag (ARDL) approach to investigate the nature of the relations. Two poverty proxies were used in this study namely, household consumption expenditure and life expectancy.

The study found access to electricity to reduce poverty in the long run and in the short run, regardless of the poverty measure used. Thus, access to electricity plays an important role in poverty alleviation and Botswana is recommended to continue with the rural and urban electrification initiatives.

The study explores the impact of access to electricity on poverty reduction in Botswana, a departure from the current studies that examined the same relationship using energy consumption in general. This is on the back of increasing dependence of economic activities on electricity as a major source of energy.

The aim of this paper is to identify some of the challenges that need to be addressed to accelerate the deployment and adoption of smart health technologies for ubiquitous healthcare access. The paper also explores how internet of things (IoT) and big data technologies can be combined with smart health to provide better healthcare solutions.

The authors reviewed the literature to identify the challenges which have slowed down the deployment and adoption of smart health.

The authors discussed how IoT and big data technologies can be integrated with smart health to address some of the challenges to improve health-care availability, access and costs.

The results of this paper will help health-care designers, professionals and researchers design better health-care information systems.

The main goal of this paper is to examine the evolution of Latin American productive integration in terms of the regional value added incorporated in intra-regional exports of Argentina, Brazil, Chile, Colombia, Mexico and Peru. In addition, the study traces the trade and productive integration trajectories for each of these countries from 1995 to 2015.

Based on the use of OECD’s global ICIO input-output tables, this paper applies the methodological framework by Wang et al. (2018) for the analysis of trade flows at the bilateral level, which allows breaking down the value of gross exports of each sector-country, depending on the origin of the value added contained in exports, as well as their use.

The estimates show very low shares of value added from regional partners in the intra-regional exports of the countries studied. Conversely, the weight of the value added incorporated in these exports by countries outside the region has increased in tandem with China’s expanding involvement in Latin America. This development, along with the downward trend in domestic value added incorporated in exports, indicates a lack of a regional integration process of any depth.

This article addresses an economic problem of conventional importance from a global value chain perspective using a novel methodology based on the use of global input–output tables.

The impact of Goods and Service Tax (GST) on the motor and pump exports in the Coimbatore region is measured in this study using various parameters and scales. The data collected from exporters were used to identify the pros and cons of GST, stating their opinions on variables considered by the researchers through extensive literature on GST and exports.

The data were collected from 220 motors and pump exporters through a field survey from the month of January to September 2021. The impacts have been measured using principal component analysis (PCA) and confirmatory factor analysis (CFA). The factor analyses and CFA will derive the positive and negative impact of GST determined through critical empirical evidence in this study. Also, the problems faced by the exporters allied to GST, which the authors could not include in the questionnaire due to certain reasons, are concisely apportioned and discussed.

The study depicts the major advantages of GST, such as harmonized system, long-run performance, reduction in logistics cost, check-post operation, bonds and ease of doing business. Also, it highlights the disadvantages of GST, such as biases in the indirect tax system, the reimbursement of duty drawback being late or pending and document filing was still a tedious job under the GST regime.

The unavailability of considerable literature on the impact of GST on Indian exports signifies the novelty of this research. So far, this is the first empirical attempt to measure the impact of GST on exports which is a unique and original attempt to highlight the problem that lies under the GST regime and the necessary reforms the tax structure needs in the context of Indian exports.

The purpose of the current flow configurations is to bring to attention the thermophysical aspects of magnetohydrodynamics (MHD) Williamson nanofluid flow under the effects of Joule heating, nonlinear thermal radiation, variable thermal coefficient and activation energy past a rotating stretchable surface.

A mathematical model is examined to study the heat and mass transport analysis of steady MHD Williamson fluid flow past a rotating stretchable surface. Impact of activation energy with newly introduced variable diffusion coefficient at the mass equation is considered. The transport phenomenon is modeled by using highly nonlinear PDEs which are then reduced into dimensionless form by using similarity transformation. The resulting equations are then solved with the aid of fifth-order Fehlberg method.

The rotating fluid, heat and mass transport effects are analyzed for different values of parameters on velocity, energy and diffusion distributions. Parameters like the rotation parameter, Hartmann number and Weissenberg number control the flow field. In addition, the solar radiation, Joule heating, Prandtl number, thermal conductivity, concentration diffusion coefficient and activation energy control the temperature and concentration profiles inside the stretching surface. It can be analyzed that for higher values of thermal conductivity, Eckret number and solar radiation parameter the temperature profile increases, whereas opposite behavior is noticed for Prandtl number. Moreover, for increasing values of temperature difference parameter and thermal diffusion coefficient, the concentration profile shows reducing behavior.

This paper is useful for researchers working in mathematical and theoretical physics. Moreover, numerical results are very useful in industry and daily-use processes.

Efficient thermal management of central processing unit (CPU) cooling systems is vital in the context of advancing information technology and the demand for enhanced data processing speeds. This study aims to explore the thermal performance of a CPU cooling setup using a cylindrical porous metal foam heat sink.

Nanofluid flow through the metal foam is simulated using the Darcy–Brinkman–Forschheimer equation, accounting for magnetic field effects. The temperature distribution is modeled through the local thermal equilibrium equation, considering viscous dissipation. The problem’s governing partial differential equations are solved using the similarity method. The CPU’s hot surface serves as a solid wall, with nanofluid entering the heat sink as an impinging jet. Verification of the numerical results involves comparison with existing research, demonstrating strong agreement across numerical, analytical and experimental findings. Ansys Fluent® software is used to assess temperature, velocity and streamlines, yielding satisfactory results from an engineering standpoint.

Investigating critical parameters such as Darcy number (10⁻⁴ ≤ Da_D ≤ 10⁻²), aspect ratio (0.5 ≤ H/D ≤ 1.5), Reynolds number (5 ≤ Re_D,bf ≤ 3500), Eckert number (0 ≤ EC_bf ≤ 0.1) , porosity (0.85 ≤ ε ≤ 0.95), Hartmann number (0 ≤ Ha_D,bf ≤ 300) and the volume fraction of nanofluid (0 ≤ φ ≤ 0.1) reveals their impact on fluid flow and heat sink performance. Notably, Nusselt number will reduce 45%, rise 19.2%, decrease 14.1%, and decrease 0.15% for Reynolds numbers of 600, with rising porosity from 0.85 to 0.95, Darcy numbers from 10⁻⁴ to 10⁻², Eckert numbers from 0 to 0.1, and Hartman numbers from 0 to 300.

Despite notable progress in studying thermal management in CPU cooling systems using porous media and nanofluids, there are still significant gaps in the existing literature. First, few studies have considered the Darcy–Brinkman–Forchheimer equation, which accounts for non-Darcy effects and the flow and geometric interactions between coolant and porous medium. The influence of viscous dissipation on heat transfer in this specific geometry has also been largely overlooked. Additionally, while nanofluids and impinging jets have demonstrated potential in enhancing thermal performance, their utilization within porous media remains underexplored. Furthermore, the unique thermal and structural characteristics of porous media, along with the incorporation of a magnetic field, have not been fully investigated in this particular configuration. Consequently, this study aims to address these literature gaps and introduce novel advancements in analytical modeling, non-Darcy flow, viscous dissipation, nanofluid utilization, impinging jets, porous media characteristics and the impact of a magnetic field. These contributions hold promising prospects for improving CPU cooling system thermal management and have broader implications across various applications in the field.