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The uncertain supply chain network design (SCND) problem, considering suppliers’ environmental, social and governance (ESG) ratings, has been infrequently addressed in the literature. Looking at the importance of ESG ratings in achieving supply chain sustainability, this study aims to fill the gap by incorporating supplier ESG factors into SCND within an uncertain environment.

This paper presents a multi-period, multi product SCND model that integrates ESG factors and accounts for uncertainties in supply and production capacities. The model seeks to minimize total operational costs by determining the optimal selection of plant and warehouse locations across multiple time periods. Uncertainties in supply and production capacities are managed through a chance-constrained programming approach with right-hand side stochasticity. A Lagrangian relaxation-based heuristic method is applied to address the NP-hard nature of the problem.

The efficacy of the proposed model is illustrated through a numerical example, demonstrating its capability to optimize material flows across the supply chain under uncertain conditions. The model simultaneously considers economic and ESG factors in procurement decisions. A sensitivity analysis is conducted to examine different operational scenarios and their implications on the model’s outcomes.

To the best of the authors’ knowledge, this study is one of the first to integrate ESG factors into SCND under uncertainty. The proposed model provides a robust framework for decision-makers to optimize supply chain operations while considering both economic and ESG objectives in an uncertain environment.

The purpose of this paper is to explore the effects of population growth (PG), environmental quality and trade openness on economic growth of major developed and developing countries.

The authors have used the panel unit root and panel co-integration tests over the period 1960-2013. Granger causality test is used to find out the direction of causality between the variables.

There is a bi-directional relationship between economic growth and trade openness, and a unidirectional relation, running from trade openness to CO₂ emissions in the three developed countries. PG has a positive effect on economic growth in three developing countries and there exists a bidirectional relationships between CO₂ emissions and PG and a unidirectional relationship from PG to economic growth and from trade openness to economic growth. Furthermore, there is a unidirectional relationship from PG to economic growth and bidirectional relationships between trade openness and economic growth for the six selected countries.

This is the first comprehensive research that combined the selected three major developed and three major emerging countries of the world to explore the effects of three important variables on economic growth. The authors’ findings will help the policy makers as well as the people of these six countries. this study has shown the aggregate and disaggregate results, so a comparison between the groups of countries is possible. Therefore, this research has significant contributions.

The purpose of this paper is to propose an optimization method by combining artificial immune algorithm and finite element analysis to find the optimal exciting electrode of a piezoceramic plate type ultrasonic motor vibrator.

The artificial immune algorithm is selected as optimizer for its merit of fast convergence to global optimal solution. The finite element analysis is used to calculate the motion trajectory of contact point. The objective function is the work that the vibrator does to rotor. The design variables are the boundaries of exciting electrode on piezoceramic plate vibrator surface.

The calculated results and the experimental results show that using this method, both the position and the size of optimal exciting electrode of this ultrasonic motor can be quickly and accurately determined.

In order to successfully design an ultrasonic motor, both the position and the size of the exciting electrode must be investigated, so as to change more electric energy into mechanical energy. In this paper, an optimization method by combining artificial immune algorithm and finite element analysis is proposed for the exciting location optimization of a piezoceramic plate type ultrasonic motor to obtain large power output.

The purpose of this study is to address a critical gap in the existing literature on business excellence implementation. While various studies have examined different aspects of business excellence, there is still a lack of comprehensive research on the optimal organizational excellence architecture (OEA) for an award-winning business excellence journey. The absence of a unified framework has led to inconsistent practices across organizations. The aim of this research based on data collected from 50 organizations across 17 countries is to address this gap and present a refined OEA model.

This study employed quantitative and qualitative data collection methods. Member organizations from the Global Excellence Model (GEM) Council participated through an online survey administered via the Qualtrics software platform. Quantitative data were analyzed using the SPSS and Microsoft Excel software tools, while content analysis techniques were applied to the qualitative data to gain detailed insights.

The findings refine and extend the OEA model. These contributions lead to a refined OEA definition and open avenues for future research, enriching the current understanding of BE implementation.

This study introduces a novel concept of OEA to the literature on business excellence implementation. The refined OEA model provides a fresh perspective on the critical components necessary for an award-winning business excellence journey. This research offers significant value to both practitioners and academics by presenting a unified approach to BE implementation, effectively addressing the previously identified gap in BE research.

The purpose of this paper is to investigate how successful lean six sigma (LSS) manifests in the Australasian (Australian and New Zealand) context relative to the context in the USA in terms of LSS project definition, structure and practices.

In-depth investigation through case studies – 12 Australian/New Zealand cases and 4 US cases – on the implementation mechanisms of successful LSS initiatives.

A significant difference was found between Australasian and US definitions of an LSS project. However, firms in both regions followed similar project selection, initiating and execution practices. LSS reporting structures were found to be well-established in US organizations, but none of the Australasian organizations were found to be equipped with such a structure, although the effectiveness of LSS implementation success remained unaffected.

Sufficient uniformity of LSS was found across two regions implying its usefulness/generalizability, but the findings are based only on 12 cases.

The paper provides the groundwork to develop a unique LSS model for Australasian organizations to improve processes in an effective and efficient manner.

The purpose of this study is to present a hybrid analytic network process (ANP) and data envelopment analysis (DEA) method for ranking organizational units as well as prioritizing organization’s human capital management criteria.

In the proposed DEA model, human capital management criteria are considered as the inputs and organizational commitment considered as the output of DEA model. Afterward, the organizational unit’s efficiency and the weight of human capital management criteria are evaluated through DEA and the data are considered as the basis of ANP model.

The results of prioritizing the drivers of human capital management were showed that leadership practices, human capital management and learning capacity are the most important ones. Also, the findings proved that the proposed integrated DEA/ANP can be helpful in managerial issues.

Filling the super-matrix and designing the questionnaire of ANP have always been the challenge of scholars because of the large number of data it requires. One of the main advantages of the proposed hybrid method in this research is that it resolves the above-mentioned problem of ANP.

The results of the proposed method may provide managers this opportunity to better analyze the condition of organizational units from human capital management perspective and focus on the most important activities in this context. Moreover, the proposed hybrid method can help scholars to better use both DEA and ANP techniques and obtain more reliable findings.

In this study, DEA efficiency measures of units, and the weights of inputs and outputs of DEA model are used to fill the super-matrix of ANP. In addition to having a logical approach, this method provides more reliable results and enjoys the advantages of both ANP and DEA techniques.

The purpose of this study is to (1) improve the spectral features of the second-order uniformly non-oscillatory (UNO) slope limiters, and (2) numerical simulation of the unified-form of generalized fully-coupled saturated thermo-poro-elastic systems in the axisymmetric cylindrical coordinate via cell-adaptive Kurganov-Tadmor (KT) central high-resolution scheme using the UNO limiters.

(1) The spectral features of the UNO limiter are improved by compression-adaptive MINMOD (MM) limiters, achieved by blending different types of MM limiters to achieve less numerical dissipation and dispersion. These blended MM limiters preserve the total variation diminishing (TVD) feature over non-uniform non-centered cells. Also, the spectral features of the central schemes using the UNO limiters are investigated. (2) For the thermo-poro-elastic problem, corresponding first-order hyperbolic system is provided, including flux, source, diffusion and nonlinear terms. Where, there are different interacting components in the source and flux terms. The nonlinear terms are also considered by the Picard-like linearization concept.

Compression-adaptive UNO limiters would be stable over adapted cells with centered and non-centered cells. The benchmarks confirm that both spectral features and numerical accuracy are improved. For the generalized thermo-poro-elastic problem, corresponding responses including the shock waves can properly be captured.

Studying heat effects (e.g. hot fluid or freezing) and explosions on tunnels. Also, the UNO limiters could be used for simulations of various systems of conservation laws.

Additive manufacturing is a recent technology used in the production of composite materials. The use of continuous fibres as reinforcement is necessary to achieve high mechanical performance. However, making these materials more environmentally friendly is still challenging. The purpose of this study was to investigate the feasibility of 3D printing a composite made of continuous regenerated cellulose fibres using a standard 3D printer generally used for printing polymers.

The production process was based on a pre-impregnated filament made from a tape containing continuous cellulose fibres and Pebax^® matrix. 3D printed composite samples were fabricated using fused deposition modelling. The tape, filament and 3D printed composites were first analysed by means of modulated differential scanning calorimetry and micrography. Tensile tests were then performed, and the mechanical characteristics were determined at each step of the production process. Fracture surfaces were investigated by field-emission gun–scanning electron microscopy.

Results showed that the mechanical behaviour of the material was maintained throughout the production process, and the 3D printed biocomposites had a stiffness equivalent to that of traditionally manufactured continuous cellulose fibre composites. The obtained 3D printed composites showed an increase in strength value by a factor of 4 and in tensile modulus by a factor of 20 compared to those of unreinforced Pebax^® polymer.

This paper demonstrates the feasibility of 3D printing composites based on continuous cellulose fibres, paving the way for new biocomposites made by additive manufacturing.

Pharmaceutical market value in Iran exceeded to more than US$4bn in 2013, indicating annually over 20 per cent growth. In the past decades, Iranian pharmaceutical industry was supported by government policies, namely, generic substitution, import limitation and local production support; however, the local pharmaceutical manufacturer’s market share in value has been decreased gradually. This study aims to provide historical data on Iran pharmaceutical market to show the importance of new product development to attain greater market share and tries to motivate the pharmaceutical industry located in developing countries to develop more innovative medicines.

This is a descriptive cross-sectional study that investigates the Iranian pharmaceutical market by focusing on new products over a five-year period (2009-2014), and that was augmented by an expert panel to rank subjectively firms’ performance indicators to shed light on the importance of new product development to firms’ performance.

The expert panel results find out that new product development is one of the most important “result indicators” for Iranian pharmaceutical companies. Historically, in line with the experts’ opinion on the new product development, the Iranian pharmaceutical industry has shown its capability to develop new medicines by developing 3,095 new products (mostly new-to-firm) across about 100 firms. Despite this fact, the share of local manufacturers in new medicines’ market decreased from 52 per cent at the beginning of studied period to 24 per cent at the end, and the gap between the unit value of imported and domestically produced medicines has been significantly increased due to low-innovative medicines locally produced.

This research was challenged with limitations such as lack of reliable published data on new medicines in the Iran pharmaceutical market.

This study highlights the fact that developing more innovative products in the generic pharmaceutical industry such as Iran can grant its market share.

This is an original study that shows the effect of innovative product development on market share through historical data.