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Wind as a major source of renewable energy has received tremendous attentions due to its unique features to reduce carbon emission and also to keep the environment safe. Nevertheless, to use wind energy properly, the environmental circumstances and geographical location related to wind intensity should be considered as a priority. Different factors may affect the selection of a suitable location for developments of wind power plants; thus, these factors should be considered concurrently to identify the optimum location of wind plants.

In this study, first, basic data envelopment analysis (DEA) was used, then dual DEA was used and, finally, Anderson Petersen (AP) model of dual DEA was selected to prioritize cities or decision-making units (DMUs). Numerical Taxonomy (NT) method was also used to assess the validity of AP dual model in DEA. The prescribed approach was applied for five cities in East Azerbaijan province of Iran.

The results indicate that wind power as a renewable energy can be harnessed in few cities, and the ranking by DEA illustrated that the city of Tabriz is the first priority.

Low environmental degradation effects in comparison to other methods and the ability to utilization at a widespread level include the benefits of using wind energy in the generation of electricity. In this regard, the study of relevant potentials and finding suitable locations for the deployment of wind energy utilization equipment are essential. Using DEA method helps us to choose optimal locations according to different criteria.

Wind energy is justifiable in reducing social costs in comparison with fossil fuel plants, which includes negative effects, and its electricity can be used as a sustainable energy in the country's economic, social and cultural development.

For identifying the most proper location for development of wind power plants in Iran, DEA is applied for the first time to prioritize the suitable locations for installations of wind turbines among five different cities in the East Azerbaijan region. A number of crucial factors including land price, distance to power, rate of natural hazards, wind speed and topography are considered for location optimization of wind turbines for the first time. Also, to validate the results of DEA method, NT method is used to assess the validity of AP dual model in DEA.

This paper aims to present a smart, sustainable supply chain practices structure on the basis of the relational view.

A method based on fuzzy cognitive map was applied to construct a relational map to introduce and implement such relational methods. Considering this relational map as a guideline, observations into particular methods and ways of applying relational methods to attain sustainable development goals across organizations has been introduced.

Primary outcomes provided a series of relational methods for the purpose of giving advice to those organizations and their suppliers for smart, sustainable supply chain. Reliance between relational methods were examined and assessed under seven meaningful groups: economic internet of things (IoT), green internet of things, social internet of things, economic supply chain, green supply chain, social supply chain and other variables.

This study guides managers toward an improved perception of the connection among IoT instances and sustainable supply to modeling smart, sustainable supply chain. Managers can determine the practices that need more focus along with the practices that are less relevant. Thus, this will help managers in the decision-making process and to organize their decisions by planning and calculating the relative importance and influence of smart, sustainable practices on each other and on the company’s smart, sustainable program.

To the best of the authors’ knowledge, this is the first approach that promptly examines and determines the interdependencies between relational methods and constructs a relational map for the purpose to introduce and analyze smart, sustainable supply chain.

With ambidextrous innovation (AI) gaining paramount importance in the manufacturing sectors of emerging markets, this research aim to explore how leadership and management support (LMS) amplify this type of innovation by leveraging knowledge sources (KS). The study further probes the knowledge management capability (KMC) as moderating effect between KS and AI.

Using the convenient random sampling technique of a sample of 340 professionals within Pakistan’s manufacturing realm, data was collated via a structured questionnaire. The subsequent analysis harnessed the power of the variance-based partial least squares structural equation modelling approach.

This research underscores the pivotal role of LMS in elevating both facets of AI i.e. exploitative innovation (ERI) and exploratory innovation (ERT). KS emerge as a vital intermediary factor that bridges LMS with both types of innovation. Notably, the potency of KS in driving AI is significantly boosted by an organization’s KMC.

This study fills existing gaps in contemporary research by offering a nuanced perspective on how LMS enrich an organization’s dual innovation spectrum via KS. It sheds light on the symbiotic interplay of leadership, knowledge flows and innovation in Pakistan’s burgeoning manufacturing sector.

Despite the expansion of women's entrepreneurial activities and its positive effects on the economic development of societies, women still face numerous difficulties in starting and running a business compared to men, especially in developing countries because of gender discrimination in the field. The cultural context in societies is a significant factor affecting the status of entrepreneurship among the Iranian women. Therefore, the present research is an attempt to identify the challenges affecting entrepreneurship among Iranian women. The results obtained from 30 semi-structured interviews with women entrepreneurs and women with entrepreneurial roles showed that sociocultural challenges faced by women entrepreneurs are classified into: “the society's perception of entrepreneurship among women,” “women's social security,” and “common family norms governing a society.”

Despite the undoubted role of knowledge in the small family business (FB) in the restaurant and fast-food industry, there are some main challenges in the knowledge-sharing (KS) orientation for promoting their business. This study tries to recognise and explore the drivers influencing these enterprises' KS processes.

The authors applied combined exploratory and confirmatory analysis in two studies. In the first study, by the Delphi method, the 22 experts consisting of managers, FB owners and academic professors explore and forecast significant items and drivers. The second study is a confirmatory factor analysis (CFA) for validating the first study's indicators using the survey collected amongst 218 restaurants and fast foods employees.

The findings indicate 23 indicators in three main drivers of individual, organisational and technological, are critical for KS in small FBs in the investigated industry.

This research supports the understanding of knowledge management and the FB and contributes to recognising the influential factors for KS amongst small and medium-sized family businesses in the food-related industry. Also, by identifying and ranking the most significant factors, this research will help entrepreneurs facilitate FB entrepreneurship. Finally, the results provide practical implications for current and future KM and FB decision-makers.

A literature review or review article is an integral part of a scientific body of research which synthesizes prior knowledge and provides a holistic overview of a subject domain. While several studies emphasize the significance of literature reviews and include the guidelines for conducting a review, limited studies demonstrated different types of literature review methodologies in a comprehensive way. Accordingly, this chapter presents various types of review methodologies which includes narrative, descriptive, systematic, meta-analysis, hybrid, umbrella, scoping, theoretical, and critical reviews. In addition, the authors' skills including logical reasoning, content analysis, literature mapping, critical writing, and ethical consideration are presented. Further, quality aspects of the literature review are discussed such as the rigor and relevance of the selected studies. Overall, this chapter provides implications for researchers in understanding types of literature review methodologies along with their objectives, strengths, and weaknesses which can assist them in selecting a suitable methodology while conducting a review.

The purpose of this paper is to develop an effective, yet simple analytical framework for optimization of permanent-magnet synchronous machines. Also, single/multi-objective optimizations are performed for a case-study machine with surface-mounted permanent magnets.

First, an accurate magnetic equivalent circuit is developed which takes all the material such as iron saturation and PM parameters into account. Then, through a Fourier analysis, it is combined with the d-q model of PM synchronous machines to achieve an optimization framework including the developed torque, back-EMF and a number of design considerations. Finally, a genetic algorithm (GA) is employed in the single/multi-objective design optimizations, which offers several design characteristics upon different desired outcomes.

An analytical design framework for the optimization of permanent-magnet synchronous machines is developed in this paper that can effectively account for all material properties such as iron saturation and PM characteristics, and take into account the design considerations, all of which are shown as superiorities of the proposed approach over the existing method. In addition, the proposed framework is relatively simpler in terms of implementing. The model is verified by employing finite element method. Moreover, sensitivity analysis is carried out to investigate the influence of the design parameters on the machine performance, which provides valuable information for the designer of such devices. Finally, a GA is utilized to perform single/multi-objective optimization schemes whose objectives are minimizing the torque ripples, back-EMF total harmonic distortion and PM volume.

The proposed framework is new approach that could be employed in the design optimization of PM synchronous machines. Contrary to existing method, it is simpler and more effective in taking the material properties such as iron saturation and PM characteristics into account.

The purpose of this paper is to investigate the ionization and dispersion effects in combination with the inhomogeneity of soil simultaneously on the effective lengths of counterpoise wires.

Improved multi-conductor transmission line model is used for computing effective length of counterpoise wires considering all aspects of soils.

The simulation results show that the ionization and dispersion effects simultaneously results in placing the effective length between situations where only one effect is considered. Also, predicting formulae for effective length of counterpoise wires considering all effects are proposed.

A sensitivity analysis on the effective lengths of counterpoise wires considering all aspects of soils is carried out.

This paper attempts to explore the green-lean-six sigma (GLSS) practices in the continuous process industry particularly in the flexible packaging (FP) industry in an emerging economy for addressing environmental sustainability issues.

The authors have employed a qualitative multiple-case approach to examine managerial perspectives on GLSS adoption in the flexible packaging industry. Semi-structured interviews with senior corporate managers in two large FP organizations in Pakistan were conducted as the primary source of data collection.

Drawing on the natural resource-based view (NRBV), the analysis revealed that organizations are implementing key GLSS practices such as environmental management system (ISO 14001), cause–effect analysis, renewable energy sources, total productive maintenance, and statistical process control to effectively manage waste, conserve resources, control air emissions, and improve environmental and workplace safety.

The authors argue that this is one of the first research studies that has utilized NRBV to investigate the application of the GLSS approach in the process industry, specifically in the FP industry in an emerging economy.

Despite differing strategies towards environmental sustainability in developed and developing nations, the manufacturing sector in these regional domains faces substantial environmental issues. The purpose of this study is to examine the green-lean-six sigma (GLSS) enablers and outcomes for enhancing environmental sustainability of manufacturing firms in both, a developed and developing country context by using an environment-centric natural resource-based view (NRBV).

First, a framework of GLSS enablers and outcomes aligned with the NRBV strategic capabilities is proposed through a systematic literature review. Second, this framework is used to empirically investigate the GLSS enablers and outcomes of manufacturing firms through in-depth interviews with lean six sigma and environmental consultants from New Zealand (NZ) and Pakistan (PK) (developed and developing nations).

Analysis from both regional domains highlights the use of GLSS enablers and outcomes under different NRBV capabilities of pollution prevention, product stewardship and sustainable development. A comparison reveals that NZ firms practice GLSS to comply with environmental regulatory requirements, avoid penalties and maintain their clean-green image. Conversely, Pakistani firms execute GLSS to reduce energy use, satisfy international customers and create a green image.

This paper provides new insights on GLSS for environmental sustainability which can assist industrial experts and academia for future strategies and research.

This is one of the early comparative studies that has used the NRBV to investigate GLSS enablers and outcomes in manufacturing firms for enhancing environmental performance comparing developed and developing nations