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The main goal of this paper is better understand the risk/return trade-off of investing in socially responsible investment funds (SRIF) and green investment funds (GIF).

To achieve our aim a green investment fund portfolio, a socially responsible investment portfolio and a conventional fund (CF) portfolio from the United States of America (USA) were selected to compare the efficiency of these three different portfolios, by using Value-Based Data Envelopment Analysis (DEA) methodology.

The results point out that SRIF and GIF are more efficient than CF. For five years, the CFs have not outperformed the GIF.

The results suggest that there is a growing awareness on the part of investors that sustainable companies are the companies that will allow a better quality of life and a more sustainable environment. It seems that somehow managers and investors are aware that the market will compensate them for thinking about a cleaner and more equitable world.

This study aims to ascertain consumption values of Muslim tourists, attitudes, satisfaction and loyalty towards a Muslim-friendly accommodation, which has gained recognition from the Malaysian Government. Subsequently, an overall Muslim-friendly image was examined as a moderating variable within the associated relationship.

A quantitative research design with a purposive sampling technique was chosen through a sample size of 378 people in Malaysia and distributed via social media. The respondents were selected based on the Muslim-friendly accommodation recognition (MFAR) initiatives, a procedure of accreditation which acknowledges Muslim-friendly accommodation for tourists. To obtain data from those travellers, structured questionnaires were used. SmartPLS was used for data analysis in this study.

The values which were found to have an influence on attitude towards a Muslim-friendly accommodation are related to social, emotional, economic, functional, monetary and epistemic elements. On the other hand, hedonic, conditional, Islamic and altruistic values were found to be insignificant in determining the attitude towards a Muslim-friendly accommodation. Subsequently, an overall Muslim-friendly image was found to moderate the relationship between social, monetary and altruistic values and its link concerning attitude towards the accommodation, while the rest of the relationships were not significant. More importantly, attitude seems to have an impact on satisfaction, as well as its loyalty towards a Muslim-friendly accommodation.

Firstly, it begins with understanding Malaysia, one of the developing countries in Southeast Asia. Secondly, data was collected from participants using a survey method, from purposive sampling which may limit the findings’ generalizability. Thirdly, this study focussed exclusively on the perceived value dimensions associated with Muslim-friendly accommodation, thus, disregarding consumers who may associate with other types of tourism and hospitality elements.

The results provide a fresh insight and a better understanding regarding the consumption values and all of its related components towards customer loyalty of the Muslim-friendly accommodation in Malaysia. In addition, the findings deliver new information and a deeper understanding of relevant values in Malaysia’s Muslim-friendly accommodation, which can be used as a standard guideline by industry practitioners, local and abroad.

This research supports service providers in developing effective brand management strategies for their own businesses. Apparently, this study discovers that emotional values tend to be the most important values in determining attitude towards Muslim-friendly accommodation.

To the best of the authors’ knowledge, this is one of the studies examining the overall perceived Muslim-friendly image within the consumption values that are relevant from an Islamic viewpoint. It provides policymakers, as well as the industry players, some reliable approaches for enhancing Muslim-friendly accommodation.

The purpose of this paper is to determine if there is a link between corporate shareholder value creation and economic growth. The first objective of this paper is to determine which specific shareholder value measurement best explains shareholder value creation for a particular industry. The next objective of the study is to establish, for each of nine different categories of firms examined, a set of value drivers that are unique and significant in expressing shareholder value for that particular category of firms. Lastly, the relationship between shareholder value creation and economic growth is tested.

To quantify and measure value creation, the paper investigates the various value creation measurements that are being applied. The next step is to ascertain whether various industries have different value creation measures that best explain value creation for the respective industries. Then, the value drivers of these specific value creation measures can be determined and their relationship with economic growth tested.

The results of this study indicate that each industry does have a specific shareholder value creation measurement that best explains shareholder value creation for that industry; for example, for five of the nine categories (industries) that were analyzed, market value added was found to be the best shareholder value creation measurement, but for capital-intensive firms and manufacturing firms, the Qratio is the best measure, while for the food and beverage industry, the market to book ratio was found to be a better measure of shareholder value creation than other measures tested. It was further found that an increase in corporate shareholder value creation is to the detriment of economic growth.

The contribution of the present study is its determination of a unique shareholder value creation measurement for particular industries. In addition, a specific set of variables per industry that create shareholder value is identified. Lastly, the important link between shareholder value creation and economic growth is exposed.

This paper aims to characterize and develop a new ecological lightweight concrete reinforced by addition of palm plant fibers (from vegetal waste) to be used in the thermal and acoustical insulation of local constructions. The date palm plant fibers are characterized by their low sensitivity to chemical reactions, low cost and large availability in local regions. Therefore, the newly obtained lightweight concrete may suggest a great interest, as it seems to be able to achieve good solutions for local construction problems, technically, economically and ecologically.

The experimental program focused on developing the composition of palm-fiber-reinforced concrete, by studying the effect of the length of the fibers (10, 20, 30 and 40 mm) and their mass percentage (0.5%, 1%, 1.5% and 2%), on the mechanical and acoustical properties of the composite. The main measured parameters were the compressive strength and flexural strength, sound absorption coefficient, noise reduction coefficient (NRC), etc. These tests were also borne out by the measure of density and water absorption, as well as microstructure analyses. To fully appreciate the behavior of the material, visualizations under optical microscope and scanning electron microscope analyses were carried out.

The addition of plant fibers to concrete made it possible to formulate a new lightweight concrete having interesting properties. The addition of date palm fibers significantly decreased the density of the concrete and consequently reduced its mechanical strength, particularly in compression. Acceptable compressive strength values were possible, according to the fibers content, while better values have been obtained in flexion. On the other hand, good acoustical performances were obtained: a considerable increase in the sound absorption coefficient and the NRC was recorded, according to the content and length of fibers. Even the rheological behavior has been improved with the addition of fibers, but with short fibers only.

Over the recent decades, many studies have attempted to search for more sustainable and environmentally friendly building materials. Therefore, this work aims to study the possibility of using waste from date palm trees as fibers in concrete instead of the conventionally used fibers. Although many researches have already been conducted on the effect of palm plant fibers on the mechanical/physical properties of concrete, no information is available neither on the formulation of this type of concrete nor on its acoustical properties. Indeed, due to the scarcity of raw materials and the excessive consumption of energy, the trend of plant fibers as resources, which are natural and renewable, is very attractive. It is therefore a major recycling project of waste and recovery of local materials.

In many of today’s manufacturing industries, such as automobile, aerospace, defence, die and mould making, medical and electrical discharge machining (EDM) has emerged as an effective material removal process. In this process, a series of discontinuous electric discharges is used for removing material from the workpiece in the form of craters generating a replica of the tool into the workpiece in a dielectric environment. Appropriate selection of the tool electrode material and combination of input parameters is an important requirement for performance enhancement of an EDM process. This paper aims to optimize an EDM process using single-valued neutrosophic grey relational analysis using Cu-multi-walled carbon nanotube (Cu-MWCNT) composite tool electrode.

This paper proposes the application of grey relational analysis (GRA) in a single-valued neutrosophic fuzzy environment to identify the optimal parametric intermix of an EDM process while considering Cu-MWCNT composite as the tool electrode material. Based on Taguchi’s L9 orthogonal array, nine experiments are conducted at varying combinations of four EDM parameters, i.e. pulse-on time, duty factor, discharge current and gap voltage, with subsequent measurement of two responses, i.e. material removal rate (MRR) and tool wear rate (TWR). The electrodeposition process is used to fabricate the Cu-MWCNT composite tool.

It is noticed that both the responses would be simultaneously optimized at higher levels of pulse-on time (38 µs) and duty factor (8), moderate level of discharge current (5 A) and lower level of gap voltage (30 V). During bi-objective optimization (maximization of MRR and minimization of TWR) of the said EDM process, the achieved values of MRR and TWR are 243.74 mm³/min and 0.001034 g/min, respectively.

Keeping in mind the type of response under consideration, their measured values for each of the EDM experiments are expressed in terms of linguistic variables which are subsequently converted into single-valued neutrosophic numbers. Integration of GRA with single-valued neutrosophic sets would help in optimizing the said EDM process with the Cu-MWCNT composite tool while simultaneously considering truth-membership, indeterminacy membership and falsity-membership degrees in a human-centric uncertain decision-making environment.

The purpose of this paper is to evaluate the causal relationship between Lean practices and team performance. Specifically, the authors tried to demonstrate which practices act as enablers of continuous improvement and waste elimination and what is their impact on team performance.

A survey was carried out in a Higher Education Institution (HEI) in Southern Brazil. The authors obtained a sample of 785 respondents. The data analysis procedures involved confirmatory factor analysis and structural equations modeling.

The results of the research provided support for the positive influence of continuous improvement on waste elimination and of these two practices on team performance. In addition, empirical support was obtained for the effect of leadership support, employee involvement and internal process customers on continuous improvement.

Data collection was carried out online, so we were not able to maintain full control of the research respondents. This research generates relevant insights for decision-makers in the HEI environment, especially concerning Lean practices and team performance. The effects analyzed are even more relevant given the pandemic context.

This study shows how some higher education Lean practices can positively affect continuous improvement and better team performance. The results raise important insights for decision-makers to offer better higher education public services, especially given the context and changes imposed by the pandemic situation.

This paper initiates the discussion about enablers of continuous improvement and waste elimination in HEI and demonstrates their impact on team performance.

This study aims to assess the efficacy of thermal analysis of concrete slabs by including different insulation materials using ANSYS. Regression equations were proposed to predict the thermal conductivity using concrete density. As these simulation and regression analyses are essential tools in designing the thermal insulation concretes with various densities, they sequentially reduce the associated time, effort and cost.

Two grades of concretes were taken for thermal analysis. They were designed by replacing the natural fine aggregates with thermal insulation aggregates: expanded polystyrene, exfoliated vermiculite and light expanded clay. Density, temperature difference, specific heat capacity, thermal conductivity and time were measured by conducting experiments. This data was used to simulate concrete slabs in ANSYS. Regression analysis was performed to obtain the relation between density and thermal conductivity. Finally, the quality of the predicted regression equations was assessed using root mean square error (RMSE), mean absolute error (MAE), integral absolute error (IAE) and normal efficiency (NE).

ANSYS analysis on concrete slabs accurately estimates the thermal behavior of concrete, with lesser error value ranges between 0.19 and 7.92%. Further, the developed regression equations proved accurate with lower values of RMSE (0.013 to 0.089), MAE (0.009 to 0.088); IAE (0.216 to 5.828%) and higher values of NE (94.16 to 99.97%).

The thermal analysis accurately simulates the experimental transfer of heat across the concrete slab. Obtained regression equations proved helpful while designing the thermal insulation concrete.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Trust in pharmaceutical firms has fluctuated over the years, with highs reached during the COVID-19 pandemic. Work needs to now be done to rebuild trust levels and work out boosting lived values.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Big data marketing analytics (BDMA) has been discovered to be a key contributing factor to developing necessary marketing capabilities. This research aims to investigate the impact of the technology and information quality of BDMA on the critical marketing capabilities by differentiating between firms with low and high perceived market performance.

The responses were collected from marketing professionals familiar with BDMA in North America (N = 236). The analysis was done with partial least squares-structural equation modelling (PLS-SEM).

The results indicated positive and significant relationships between the information and technology quality as exogenous constructs and the endogenous constructs of the marketing capabilities of marketing planning, implementation and customer relationship management (CRM) with mainly moderate effect sizes. Differences in the path coefficients in the structural model were detected between firms with low and high perceived market performance.

This research indicates the critical role of technology and information quality in developing marketing capabilities. The study discovered heterogeneity in the sample population when using the low and high perceived market performance as the source of potential heterogeneity, the presence of which would likely cause a threat to the validity of the results in case heterogeneity is not considered. Thus, this research builds on previous research by considering this issue.

The explosion of data due to the sophistication of information and communication technology makes it simple for prospective tourists to learn about previous hotel guests' experiences. They prioritize the rating score when selecting a hotel. However, rating scores are less reliable for suggesting a personalized preference for each aspect, especially when they are in a limited number. This study aims to recommend ratings and personalized preference hotels using cross-domain and aspect-based features.

We propose an aspect-based cross-domain personalized recommendation (AsCDPR), a novel framework for rating prediction and personalized customer preference recommendations. We incorporate a cross-domain personalized approach and aspect-based features of items from the review text. We extracted aspect-based feature vectors from two domains using bidirectional long short-term memory and then mapped them by a multilayer perceptron (MLP). The cross-domain recommendation module trains MLP to analyze sentiment and predict item ratings and the polarities of the aspect based on user preferences.

Expanded by its synonyms, aspect-based features significantly improve the performance of sentiment analysis on accuracy and the F1-score matrix. With relatively low mean absolute error and root mean square error values, AsCDPR outperforms matrix factorization, collaborative matrix factorization, EMCDPR and Personalized transfer of user preferences for cross-domain recommendation. These values are 1.3657 and 1.6682, respectively.

This study assists users in recommending hotels based on their priority preferences. Users do not need to read other people's reviews to capture the key aspects of items. This model could enhance system reliability in the hospitality industry by providing personalized recommendations.

This study introduces a new approach that embeds aspect-based features of items in a cross-domain personalized recommendation. AsCDPR predicts ratings and provides recommendations based on priority aspects of each user's preferences.