• The adoption of operational environmental sustainability approaches in the Thai manufacturing sector

      Piyathanavong, V., Garza-Reyes, J.A., Kumar, V., Maldonado-Guzman, G., Kumar Mangla, S.; University of Derby (Elsevier, 2019-02-19)
      Evidence suggests that manufacturing companies have tried to address the current environmental challenges derived from their operations by implementing various operational environmental sustainability approaches, including green manufacturing (GM), cleaner production (CP), green lean (GL), green supply chain management (GSCM), reverse logistics (RLs) and circular economy (CE). However, although their adoption is well documented in developed nations and few other countries, very little has been done to understand such phenomenon in a rapid developing country such as Thailand. This paper aims at filling this gap by providing light into some fundamental issues regarding the implementation of these approaches in the manufacturing sector of Thailand. A survey-based exploratory research was carried out based on 287 Thai manufacturing companies. The data was analysed using a combination of descriptive and inferential statics. The study revealed that a large amount of investment capacity, and proper training & knowledge are needed to fully implement the studied operational approaches. This resulted in some of the weakest elements of Thai manufacturing firms and hence the main barriers to their implementation. The study also showed that Thai manufacturing firms consider the impact on the environment and benefits from adopting these operational approaches as company’s policy and own initiative, environmental awareness, and cost saving from conservation of energy as the main reasons for adopting the studied operational approaches. Finally, the findings also indicate that Thai manufacturing firms tend to implement them because of internal factors and that they lack of motivation from external factors and involvement from other stakeholders. The paper extends the current limited knowledge on the deployment of operational environmental sustainability approaches in Asia, and its results can be beneficial for organisations that aim at effectively adopting them to improve their operation’s sustainability.
    • An analysis of managerial factors affecting the implementation and use of overall equipment effectiveness.

      Binti Aminuddin, Nur Ainunnazli; Garza-Reyes, Jose Arturo; Kumar, Vikas; Antony, Jiju; Rocha-Lona, Luis; University of Warwick; University of Derby; University of the West of England; University of Edinburgh; National Polytecnic Institute of Mexico (Taylor and Francis, 2015-06-15)
      To ensure manufacturing organisations remain competitive, most of them are turning to total productive maintenance (TPM) and lean manufacturing to ensure seamless operations. Overall equipment effectiveness (OEE) is the foundation of these two business improvement strategies as it tackles the underlying losses that impede equipment efficiency. This study presents the prevalence of managerial issues related to the implementation and use of OEE in the manufacturing industry. To do this, five hypotheses and four research questions were formulated and tested using a combination of descriptive statistics and cross-tabulation, chi-square, analysis of variance, Tukey’s pairwise comparison, Z-test and correlation tests. Data were collected through a survey questionnaire responded by 139 manufacturing organisations worldwide. The results establish, among other ‘soft’ aspects, the linkage of the OEE implementation with that of TPM and lean manufacturing, and the drivers, most critical factors, barriers and the role of management in its implementation. The study also identifies how manufacturing organisations employ the information provided by OEE and how the data for its computation are collected. This study supports the very limited empirical research on the implementation and use of OEE. Thus, this research provides organisations, and their managers, with a better understanding of different factors that affect the successful deployment and management of this highly used measure in industry.
    • Barriers in green lean implementation: a combined systematic literature review and interpretive structural modelling approach

      Cherrafi, Anass; Elfezazi, Said; Garza-Reyes, Jose Arturo; Benhida, Khalid; Mokhlis, Ahmed; Cadi Ayyad University; University of Derby (Taylor and Francis, 2017)
      Green Lean has recently emerged as an alternative strategy for organizations to pursue both operational and sustainability excellence. The interest on this approach has rapidly risen in both academic and industry circles. However, despite this interest, very limited research has focused on its implementation, and no research has investigated the barriers that hinder the success of such activity. This study investigates the Green Lean implementation barriers and their contextual relationships and effects on the integration and deployment of this approach. A Systematic Literature Review (SLR), Interpretative Structural Modelling and fuzzy Matriced’ Impacts Croise’s Multiplication Appliqée a UN Classement (MICMAC) analyzes were carried out. Fifteen barriers were extracted from the SLR and then validated in consultation with industry and academic experts. The Interpretive Structural Modelling (ISM) method was used to understand the relationship between the fifteen barriers and to develop a hierarchical model of these. The different barriers were classified into ‘linkage’ and ‘dependent’ barriers by using MICMAC analysis. The results suggested that all the identified barriers play an important role, and hence can equally act as a significant hurdle to the implementation of Green Lean projects. This study can help managers and policy makers in better understanding these barriers. Thus, they can be assisted in managing and prioritizing barriers towards the successful implementation of Green Lean initiatives for better financial and environmental performance.
    • Barriers to innovation in service SMEs: Evidence from Mexico

      Maldonado-Guzman, Gonzalo; Garza-Reyes, Jose Arturo; Pinzon-Castro, Sandra Yesenia; Kumar, Vikas; The University of Derby (Emerald, 2017)
      Purpose – Specific research related to the study of innovation barriers in service SMEs in the Latin American region is limited. This study thus investigates the effects that external environmental, financial and human barriers have on innovation activities, particularly, within the context of Mexican service SMEs. Design/methodology/approach – Three hypotheses were formulated and tested using structural equation modelling (SEM). Data were collected through an instrument that was developed based on relevant constructs adapted from the literature. The instrument was validated using Confirmatory Factor Analysis, Cronbach’s alpha test and Composite Reliability Index to ensure the reliability of the theoretical model. The instrument was distributed among service SMEs in the Aguascalientes state of Mexico, from were 308 valid responses were obtained. Findings – In general, the results indicate that all of the three barriers investigated (i.e. external environmental, financial and human) hinder innovation in service SMEs, with the external environmental barrier being the most significant of the three. Practical implications – The findings of this research can inform managers of service SMEs and policy makers when formulating and implementing strategies to reduce innovation barriers. Originality/value – Evidence suggests that specific research related to the study of innovation barriers in service SMEs in the Latin American region is limited. This paper fills this research gap by expanding the limited body of knowledge in this field and providing further evidence on this phenomenon. The study also enables the distinctive characteristics of innovation barriers to be understood within a particular context, expanding in this way the body of knowledge on this field.
    • Best supply chain management practices and high- performance firms: the case of Gulf manufacturing firms.

      AL-Shboul, Moh’d Anwer; Garza-Reyes, Jose Arturo; Kumar, Vikas; University of Derby; German-Jordanian University; University of West of England (Emerald, 2018-10)
      Purpose – The study aims to investigate the best supply chain management practices that are implemented in medium and large-sized Gulf manufacturing firms. Design/methodology/approach – This study has explored seven supply chain management practices, i.e. supplier collaboration, flexibility with partners, usage of Internet, customer focus, lean production, Internal integration, and quality management. It assumes that the best performing firms must be the ones implementing the best practices. T-test and multiple linear regression analyses were used to establish the best practices, implemented by medium and large-sized Gulf manufacturing firms. Findings – The results showed that quality management, customer focus, and supplier collaboration are considered as best supply chain management practices in Gulf manufacturing firms. Usage of internet may have been the best practice previously, but not anymore. Lean production cannot yet be qualified as, but may develop into the best supply chain management practice. Practical Implications – The study provides a useful contribution to the field of best supply chain management practices as it provides better decision-making insights and a benchmarking base to top managers, policy makers, and academics. It is likely to result in increased overall performance of their firms. Originality/value – The study provides an understanding of the distinctive characteristics of the best supply chain management practices, implemented by Gulf manufacturing firms. It has broader implications for all manufacturing firms, particularly in developing economies where the growth of manufacturing and effective management of their supply chains is a key element for the economic development.
    • Capturing user sentiments for online Indian movie reviews.

      Trivedi, Shrawan Kumar; Dey, Shubhamoy; Kumar, Anil; Indian Institute of Management Sirmaur, Sirmaur, India; Indian Institute of Management Indore, Indore, India; University of Derby; Department of IT and Systems, Indian Institute of Management Sirmaur, Sirmaur, India; Department of Information Systems, Indian Institute of Management Indore, Indore, India; Department of Decision Science, BML Munjal University, Gurgaon, India (Emerald Insight, 2018-08-06)
      Sentiment analysis and opinion mining are emerging areas of research for analysing Web data and capturing users’ sentiments. This research aims to present sentiment analysis of an Indian movie review corpus using natural language processing and various machine learning classifiers. In this paper, a comparative study between three machine learning classifiers (Bayesian, naïve Bayesian and support vector machine [SVM]) was performed. All the classifiers were trained on the words/features of the corpus extracted, using five different feature selection algorithms (Chi-square, info-gain, gain ratio, one-R and relief-F [RF] attributes), and a comparative study was performed between them. The classifiers and feature selection approaches were evaluated using different metrics (F-value, false-positive [FP] rate and training time).The results of this study show that, for the maximum number of features, the RF feature selection approach was found to be the best, with better F-values, a low FP rate and less time needed to train the classifiers, whereas for the least number of features, one-R was better than RF. When the evaluation was performed for machine learning classifiers, SVM was found to be superior, although the Bayesian classifier was comparable with SVM. This is a novel research where Indian review data were collected and then a classification model for sentiment polarity (positive/negative) was constructed.
    • Causal modelling and analysis evaluation of online reputation management using Fuzzy Delphi and DEMATEL

      Kumar, Anil; Dash, Manoj Kumar; BML Munjal University; Indian Institute of Information Technology and Management, Gwalior; School of Management, BML Munjal University, Gurgaon, India; Behavioural Economics Experiments and Analytics Laboratory, Indian Institute of Information Technology and Management, Gwalior, India (IGI Global, 2017-01)
      Online reputation management (ORM) is a significant and proactive tool that can reinforce the credibility of the service provider. Literature existing today on this topic has rarely reported on the causal modeling analysis from an ORM perspective. Therefore, the objective of this paper is to build a factor structure of ORM and to build the inter-relationship map amongst the criteria of each factor. To allow for vague human judgment, a fuzzy concept is employed in a form of Fuzzy Delphi. The DEMATEL technique has been used to develop a Network Relationship Map (NRM) among the criteria of each factor. Data has been gathered through a structured questionnaire conducted with a survey of experts. The study divided the criteria of each factor into cause-effect criteria. Findings of the study show that criteria such as distributed reputation system, trust, online competitive branding, website management, customer relationship, search engine optimization, corporate social responsibility, users' reach, competition/page views, purchase discounted products and cash back or money back fall under the cause group of ORM's factors. The results of this study can not only help service providers to enhance their reputation but can also guide them towards targeting their customers in an online platform.
    • The challenges of GSCM implementation in the UK manufacturing SMEs.

      Kumar, Vikas; Sabri, Shahruzzaman; Garza-Reyes, Jose Arturo; Nadeem, Simon Peter; Kumari, Archana; Akkaranggoon, Supalak; University of the West of England; University of Warwick; Khon Kaen University; University of Derby (IEEE, 2019-01-31)
      The importance of green supply chain management has long attracted the interest of both researchers and practitioners in the industry. As environmental concerns are becoming one of the major issues discussed in the 21st century, countries with manufacturing as its principal economy contributor are always on the lookout for innovations and new approaches to balance both environmental considerations and profit making. The UK, being one of the top manufacturing countries in the world already considered green initiatives among their manufacturers. According to reports from the industry, large and international manufacturing companies from the UK have successfully implemented some green initiatives with significant improvements across the supply chain. However, the adoption of green initiatives is mainly focused on large companies rather the real backbone of the UK manufacturing industry, which is the small and medium-sized enterprises (SMEs). This paper therefore sets out to determine the implementation level of green supply chain among the SMEs. The paper adopts a mixed methods based approach and findings are based on 57 survey responses and 5 semi-structured interviews from UK manufacturing SMEs. The findings show that the level of GSCM implementation among the UK manufacturing SMEs is low compared to large organisations. Cost of implementing GSCM practices emerged as a key challenge faced by the UK manufacturing SMEs which was followed by the lack of knowledge within the organisation. This study thus adds to the limited literature on the manufacturing SMEs and provides evidence from the UK manufacturing sector on the adoption of GSCM practices.
    • The circular economy impact on small to medium enterprises

      Thorley, J., Garza-Reyes, J.A., Anosike, A.; University of Derby (WIT Press, 2019-01-30)
      In recent years, the literature surrounding the circular economy has grown. While the notion of reducing, recycling and reusing have become adopted practices in many organisations under the umbrella of sustainability, having a circular economy is arguably the next generation step, in terms of sustainability. A systematic literature review on the circular economy identified a gap in the research, regarding the impact at the micro level to be placed on small to medium enterprises. The research concludes that a paradigm shift in circular thinking at the micro level is required, and that further research is needed to identify new skills, resources, approaches, and business models to enable subject matter experts (SMEs) to adopt a circular practice.
    • A circularity measurement toolkit for manufacturing SMEs.

      Garza-Reyes, Jose Arturo; Valls, Ailin Salomé; Nadeem, Simon Peter; Anosike, Anthony; Kumar, Vikas; University of Derby; University of Warwick; University of the West of England (Taylor and Francis, 2018-12-24)
      The development and adoption of the concept of circular economy in the last two decades have been remarkable. However, despite its widespread adoption, little progress has been made regarding its measurement, especially in manufacturing SMEs. This paper, therefore, proposes a Circularity Measurement Toolkit (CMT) which enables the assessment of the degree of circularity in manufacturing SMEs. A conceptual CMT framework, which provided the basis for the proposed tool and that defined the different types of circular practices and a classification or levels of circularity was developed from an extensive literature reviewed. To ensure the structure’s accuracy of the proposed CMT in terms of requirements to be measured, the monitoring process and actions involved, the tool was verified through a Delphi-study. Furthermore, its practicality was validated through a case study approach in a manufacturing SME. This paper contributes by filling a gap in the CE measurement field through the proposal of the CMT. Besides providing an evaluation of the degree of circularity in the practices of manufacturing SMEs, companies can also employ the proposed CMT to identify corrective actions or future efforts for the adoption of CE practices.
    • Combined artificial bee colony algorithm and machine learning techniques for prediction of online consumer repurchase intention

      Kumar, Anil; Kabra, Gaurav; Mussada, Eswara Krishna; Dash, Manoj Kumar; Rana, Prashant Singh; Xavier Institute of Management, Bhubaneswar, India; BML Munjal University; Indian Institute of Information Technology & Management, Gwalior (Madhya Pradesh), India; Thapar University Patiala, Punjab, India (Springer, 2017-05-30)
      A novel paradigm in the service sector i.e. services through the web is a progressive mechanism for rendering offerings over diverse environments. Internet provides huge opportunities for companies to provide personalized online services to their customers. But prompt novel web services introduction may unfavorably affect the quality and user gratification. Subsequently, prediction of the consumer intention is of supreme importance in selecting the web services for an application. The aim of study is to predict online consumer repurchase intention and to achieve this objective a hybrid approach which a combination of machine learning techniques and Artificial Bee Colony (ABC) algorithm has been used. The study is divided into three phases. Initially, shopping mall and consumer characteristic’s for repurchase intention has been identified through extensive literature review. Secondly, ABC has been used to determine the feature selection of consumers’ characteristics and shopping malls’ attributes (with > 0.1 threshold value) for the prediction model. Finally, validation using K-fold cross has been employed to measure the best classification model robustness. The classification models viz., Decision Trees (C5.0), AdaBoost, Random Forest (RF), Support Vector Machine (SVM) and Neural Network (NN), are utilized for prediction of consumer purchase intention. Performance evaluation of identified models on training-testing partitions (70-30%) of the data set, shows that AdaBoost method outperforms other classification models with sensitivity and accuracy of 0.95 and 97.58% respectively, on testing data set. This study is a revolutionary attempt that considers both, shopping mall and consumer characteristics in examine the consumer purchase intention.
    • A conceptual framework for the implementation of quality management systems

      Garza-Reyes, Jose Arturo; Rocha-Lona, Luis; Kumar, Vikas; University of Derby (Taylor and Francis, 2014-06-25)
      Some evidence suggests that Quality Management Systems (QMSs) make a positive contribution towards the competitiveness of organisations. However, evidence also suggests that organisations find their implementation difficult, and in many cases they are unsuccessful. This paper presents a conceptual framework that systematically guides organisations through a five-stage process to effectively implement and/or improve their QMSs and core business processes. The framework can be modified or amended to be adapted to the needs of specific industries and organisations. The paper discusses some of the main issues associated with the implementation of QMSs and summarises some of the frameworks and models that have been suggested for this purpose. Then, the paper explains, in detail, all the stages and activities of which the proposed conceptual framework consists. This paper's main contribution consists of the proposal of an alternative and novel approach for the implementation/improvement of QMS and business processes.
    • A conceptual framework for the implementation of sustainability business processes

      Gallotta, Bruno; Garza-Reyes, Jose Arturo; Anosike, Anthony; Lim, Ming K.; Roberts, Ian; The University of Derby (Production and Operations Management Society, 2016-05)
      This research aims to provide a complete solution to achieve true sustainability in business processes, evaluating all relevant aspects. This paper demonstrates a conceptual framework with a case study to simulate scenarios of potential applications, and discusses the simulation results of different aspects organisations struggle to succeed in the implementation.
    • Construction of capital procurement decision making model to optimize supplier selection using Fuzzy Delphi and AHP-DEMATEL

      Kumar, Anil; Pal, Amit; Vohra, Ashwani; Gupta, Sachin; Manchanda, Suryakant; Dash, Manoj Kumar; BML Munjal University; Indian Institute of Information Technology and Management; BML Munjal University, Gurugram, India; MBA-Hero Lead, BML Munjal University, Gurugram, India; MBA-Hero Lead, BML Munjal University, Gurugram, India; MBA-Hero Lead, BML Munjal University, Gurugram, India; MBA-Hero Lead, BML Munjal University, Gurugram, India; Indian Institute of Information Technology and Management, Gwalior, India (Emerald, 2018-07-02)
      Purpose – Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken systematically with the utmost transparency. Therefore, the aim of this study is the construction of capital procurement decision making models to optimize supplier selection in the Indian automobile industry. Design/methodology/approach – To achieve the stated objective, a combined approach of fuzzy theory and AHP-DEMATEL is applied. Evaluation parameters are identified through an extensive literature review and criteria validation has been introduced through a Fuzzy Delphi method by using fuzzy linguistic scales to handle the vagueness of information. AHP is employed to find the priority weight of criteria although an inter-relationship map among criteria is not possible through AHP alone since it considers all criteria as independent. To overcome this, DEMATEL is used to establish cause-effect relationships among criteria. Findings – The results show that the total cost of ownership is the first weighted criterion in supplier selection for capital procurement, followed by manufacturing flexibility and maintainability, then conformity with requirement. The cause-effect model shows that supplier profile, total cost of ownership, service support and conformity with requirement are in the cause group and are considered to be the most critical factors in selecting the supplier. Originality/value – The study’s outcome can help the automobile industry to optimize their selection process in selecting their suppliers for capital procurement; the proposed model can provide guidelines and direction in this regard.
    • Decision modeling for evaluating risks in pharmaceutical supply chains

      Moktadir, M. A.; Ali, S; Kumar Mangla, S; Sharmy, T; Luthra, S; Mishra, N; Garza-Reyes, Jose Arturo (Emerald, 2018-01)
      Purpose - Managing risks is becoming a highly focused activity in the health service sector. In particular, due to the complex nature of processes in the pharmaceutical industry, several risks have been associated to its supply chains. This paper therefore aims at identifying and analyzing the risks occurring in the supply chains of the pharmaceutical industry and proposing a decision model, based on the Analytical Hierarchy Process (AHP) method, for evaluating risks in pharmaceutical supply chains. Design/methodology/approach – The proposed model was developed based on the Delphi method and AHP techniques. The Delphi method helped to select the relevant risks associated to pharmaceutical supply chains. Sixteen sub-risks within four main risks were identified through an extensive review of the literature and by conducting a further investigation with experts from five pharmaceutical companies in Bangladesh. AHP contributed to the analysis of the risks and determination of their priorities. Findings – The results of the study indicated that supply related risks such as fluctuation in imports arrival, lack of information sharing, key supplier failure and non-availability of materials should be prioritised over operational, financial and demand related risks. Originality/value – This work is one of the initial contributions in the literature that focused on identifying and evaluating PSC risks in the context of Bangladesh. This research work can assist practitioners and industrial managers in the pharmaceutical industry in taking proactive action to minimize its supply chain risks. To the end, we performed a sensitivity analysis test, which gives an understanding of the stability of ranking of risks.
    • Decision policy scenarios for just-in-sequence deliveries: A supply chain fluidity approach

      Cedillo-Campos, Miguel Gaston; Morones Ruelas, Dario; Lizarraga-Lizarraga, Giovanni; Garza-Reyes, Jose Arturo; Mexican Institute of Transportation; CEVA Logistics; Universidad Autónoma de Nuevo León; Ecole des Mines de Saint-Étienne; University of Derby (OmniaScience, 2018)
      Purpose: The Just-in-Sequence (JIS) approach is evidencing advantages when controlling costs due to product variety management, and reducing the risk of disruption in sourcing, manufacturing companies and third-party logistics (3PL). This has increased its implementation in the manufacturing industry, especially in highly customized sectors such as the automotive industry. However, despite the growing interest from manufacturers, scholarly research focused on JIS still remains limited. In this context, little has been done to study the effect of JIS on the fluidity of supply chains and processes of logistics suppliers as well as providing them with a decision making tool to optimise the sequencing of their deliveries. Therefore, the aim of this paper is to propose a genetic algorithm to evaluate different decision policy scenarios to reduce risks of supply disruptions at assembly line of finished goods. Consequently, the proposed algorithm considers a periodic review of the inventory that assumes a steady demand and short response times is developed and applied. Design/methodology/approach: Based on a literature review and real-life information, an abductive reasoning was performed and a case study application of the proposed genetic algorithm conducted in the automotive industry. Findings: The results obtained from the case study indicate that the proposed genetic algorithm offers a reliable solution when facing variability in safety stocks that operate under assumptions such as: i) fixed costs; ii) high inventory turnover; iii) scarce previous information concerning material requirements; and iv) replenishment services as core business value. Although the results are based on an automotive industry case study, they are equally applicable to other assembly supply chains. Originality/value: This paper is of interest to practitioners and academicians alike as it complements and supports the very limited scholarly research on JIS by providing manufacturers and 3PL suppliers competing in mass customized industries and markets, a decision support system to help decision making. Implications for the design of modern assembly supply chains are also exposed and future research streams presented.
    • Developing green supply chain management taxonomy-based decision support system.

      Kumar, Vikas; Holt, Diane; Ghobadian, Abby; Garza-Reyes, Jose Arturo; University of the West of England; University of Essex; University of Reading; University of Derby (Taylor and Francis, 2014-05-21)
      The aim of this paper is to develop a comprehensive taxonomy of green supply chain management (GSCM) practices and develop a structural equation modelling-driven decision support system following GSCM taxonomy for managers to provide better understanding of the complex relationship between the external and internal factors and GSCM operational practices. Typology and/or taxonomy play a key role in the development of social science theories. The current taxonomies focus on a single or limited component of the supply chain. Furthermore, they have not been tested using different sample compositions and contexts, yet replication is a prerequisite for developing robust concepts and theories. In this paper, we empirically replicate one such taxonomy extending the original study by (a) developing broad (containing the key components of supply chain) taxonomy; (b) broadening the sample by including a wider range of sectors and organisational size; and (c) broadening the geographic scope of the previous studies. Moreover, we include both objective measures and subjective attitudinal measurements. We use a robust two-stage cluster analysis to develop our GSCM taxonomy. The main finding validates the taxonomy previously proposed and identifies size, attitude and level of environmental risk and impact as key mediators between internal drivers, external drivers and GSCM operational practices.
    • Developing textile entrepreneurial inclination model by integrating experts mining and ISM-MICMAC

      Kapse, Chanduraj Pious; Kumar, Anil; Dash, Manoj Kumar; Zavadskas, Edmundas Kazimieras; Luthra, Sunil; Government Polytechnic, Nagpur, India; BML Munjal University; Indian Institute of Information Technology and Management; Vilnius Gediminas Technical University; State Institute of Engineering & Technology,Nilokheri, India; Department of Textile Manufacturing, Government Polytechnic , Nagpur, India; School of Management, BML Munjal University , Gurgaon, India; Behavioural Economics Experiments & Analytics Laboratory, Indian Institute of Information Technology and Management, Gwalior, India; Faculty of Civil Engineering, Institute of Sustainable Construction, Vilnius Gediminas Technical University, Vilnius, Lithuania; State Institute of Engineering & Technology (Formerly known as Government Engineering College) , Nilokheri, India (Taylor and Francis, 2018-03-05)
      The Indian textile industry is lacking in an entrepreneurial inclination of a skilled young generation; because of this, the industry is facing a challenge to achieve sustainable development and growth. To overcome this problem, the goal of this work is to build an entrepreneurial inclination model in the context of the textile industry. For achieving this goal, a combined approach of an extensive literature review and experts mining has been used to establish the entrepreneurial inclination factors in phased of the study. In the second phase, an Interpretive Structural Modelling (ISM) with Matrice d'Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) has been applied to build a structural model and to find the driving force factors and dependence power. The results show that effective entrepreneurship courses, institutional policy, training and internship, institutional corporation and the involvement of institutional heads play a very significant role in encouraging youth towards entrepreneurship. The outcomes of the study can help both the government and academic institutes to draw up effective policy and develop an entrepreneurial culture which can help to create more entrepreneurs in the textile field.
    • Editorial: Seeing green: Achieving environmental sustainability through lean and six sigma

      Garza-Reyes, Jose Arturo; Kumar, Vikas; Chen, Frank, F.; Wang, Yi-Chi; University of Derby; University of West England (Emerald, 2017-01)
    • The effect of lean methods and tools on the environmental performance of manufacturing organisations.

      Garza-Reyes, Jose Arturo; Kumar, Vikas; Chaikittisilp, Sariya; Tan, Kim Hua; University of Derby; University of the West of England; University of Warwick; University of Nottingham (Elsevier, 2018-04-01)
      Evidence suggests that lean methods and tools have helped manufacturing organisations to achieve operational excellence, and in this way meet both traditional and contemporary organisational objectives such as profitability, efficiency, responsiveness, quality, and customer satisfaction. However, the effect of these methods and tools on environmental performance is still unclear, as limited empirical research has been conducted in this field. This paper therefore investigates the impact of five essential lean methods, i.e. JIT, autonomation, kaizen/continuous improvement, total productive maintenance (TPM) and value stream mapping (VSM), on four commonly utilised measures for the compliance of environmental performance, i.e. material use, energy consumption, non-product output, and pollutant releases. A correlation analysis modelled the relationship and effect of these lean methods on the environmental performance of 250 manufacturing organisations around the world. Structural equation modelling (SEM) was used as a second pronged verification approach to ensure the validity of the results. The results indicate that TMP and JIT have the strongest significance on environmental performance, whereas kaizen/continuous improvement only showed an effect on the use of materials and release of pollutants. Autonomation and VSM did not show any impact on environmental performance. The research holds important implications for industrialists, who can develop a richer knowledge on the relationship between lean and green. This will help them formulate more effective strategies for their simultaneous or sequential implementation. The paper extends our knowledge in the lean and green field by helping us to establish and explain the given relationships between five of the most important and commonly used lean methods and the environmental performance of manufacturing organisations. No previous research had considered the studied lean methods and environmental measures of performance.