Now showing items 1-20 of 148

    • How selection of collaborating partners impact on the green performance of global businesses? An empirical study of green sustainability

      Ramanathan, U., Mazolla, E., Mohan, U., Bruccoleri, M., Awasthi, A., Garza-Reyes, J.A.; University of Derby (Taylor & Francis, 2020)
      In recent days, both collaboration and sustainability have become an integral part of many global supply chains to achieve business excellence. Although previous literature and actual practices confirmed the successful implementation of sustainability practices through supply chain collaborations, it is not clear how collaborating partners can support financial and environmental performance, and hence strengthen the partnership performance in the global supply chains. To address this practice-based research question, we test the theoretical underpinning of suppliers and logistics partners in relation to required skills selection. We capture the depth of interdependencies in collaborations for routine operations and sustainability, through empirical evidence. We used case study observations from three global companies to develop a conceptual model and also conducted a questionnaire survey to test the conceptual model. The results of case analysis confirmed two dimensions of collaborations that could strengthen relationship; namely, partners’ selection and sustainability team formation. Data analysis strongly support business collaborations having careful choice of supply chain partners and logistics operators who are ready to maintain green operations with transparent information sharing. Results of this study also inform managers about the importance of commitment from collaborating partners to achieve sustainability in their global supply chains. It is clear from the results that both the business and financial performances will be strengthened by environmental positioning (green objectives) of the companies.
    • An MCDA cause-effect factors model for the implementation of Greenstone digital library soft-ware

      Rathee, S; Kumar, A; Kaushik, S; Kazimieras Zavadskas, E; Banaitis, A; Garza-Reyes, J.A.; Ganga Institute of Management and Technology, Haryana, India; University of Derby; PDM University, Bahadurgarh, India; Vilnius Gediminas Technical University, Vilnius, Lithuania (Emerald, 2020-06-16)
      The selection of an effective library software plays an important role not only for students, academic staff, and the library staff but it also helps an institution by having the library management system more centralized. Therefore, the aim of this study is to develop a Multiple- Criteria Decision Analysis (MCDA) cause and effect factor model for the implementation of the Greenstone digital library (GSDL) software. A thorough review of the literature is conducted to develop an initial list of the appropriate evaluation factors that play a significant role in the implementation of GSDL software. The data was collected from a domain of experts in the library sciences field. A combined approach of Delphi-DEMATEL methods is employed for the definition of these factors and to construct an MCDA cause-effect model which represent their relationships. The DEMATEL analysis resulted in the division of all factors into two groups, i.e., causes and effects. The results show that content management, having a user-friendly interface and usability, information search and retrieval, authentication and authorization fall into the cause group. These factors directly affect the remaining factors. Content acquisition, classification, access, control and privacy management, plus metadata submission and support fall into the effect group. The research findings can help library professionals to make effective decisions to facilitate the successful implementation of GSDL software in a library and the enhancement of library technology. The results of this study can be useful for library professionals and decision-makers to select the most appropriate software for the implementation of library technology. The study analysis shows that for GSDL, having a user-friendly interface and usability, information search and retrieval plus authentication, and authorization factors have seven positive relationships with other factors. Secondly, content management and classification have six relationships with other factors. Thirdly, access control plus privacy and management have two relationships. Content acquisition has only one relationship with other factors. It is recommended that the user-friendly interface and usability, information search and retrieval, as well as authentication and authorization should be the initial areas of focus if GSDL is to be implemented successfully in digital libraries. The proposed MCDA cause-effect model can be useful for library professionals or decision-makers in the context of selecting software to be implemented in a library and to minimize implementation costs.
    • A decision-support framework for lean, agile and green practices in product life cycle stages

      Udokporo, Chinonso; Anosike, Anthony; Lim, Ming; University of Derby; Coventry University (Taylor & Francis, 2020-05-19)
      Improving operations performance is often achieved through the application of practices such as Lean, Agility and Green (LAG) practices. However, the wide choice of LAG practices available to address customer requirements can be challenging for those with limited knowledge of LAG practices and their efficacy. Therefore, this research provides a framework for selecting appropriate LAG practices that considers product life cycle (PLC) stages for more effective application of practices. The framework was developed following thorough literature review to capture LAG practices. These form the basis for decision making tools incorporated within the framework including an analytic hierarchy process (AHP), statistical inference and regression analysis, ensuring a systematic approach to the analysis and decision support. The framework was verified and validated through a Delphi study and case study respectively. This research makes a contribution to the body of knowledge by providing a framework which could serve as a guide for businesses in the fast moving consumer goods (FMCG) industry to systematically integrate and adopt LAG to better manage their processes and meet customer requirements.
    • The role of organizational motivation and coordination in continuous improvement implementations: an empirical research of improvement project success

      Lameijer, B; Antony, J; Chakraborty, A; Does, R.J.M.M.; Garza-Reyes, J.A.; University of Amsterdam; Heriot Watt University, Edinburgh; Indian Institute of Management; University of Derby (Taylor & Francis, 2020-04-30)
      The paper aims to elicit the understanding of process improvement (PI) project success by researching the effects of organizational- motivation and coordination in continuous improvement (CI) implementations in the financial services sector. The data analyzed using structural equation modeling (SEM) comes from a sample of 198 survey respondents in financial service organizations that have implemented CI. This research shows that a strong organizational motivation is driving the embeddedness of PI methodology in, and alignment with the CI implementation of, the organization and thus affecting PI project success. In addition, central coordination is found to affect the alignment of the organization to the CI implementation activities and objectives and affects PI project success. These findings show how the organizational level constructs of organizational- motivation and coordination affect PI project success following the mediating constructs of alignment, embeddedness, and routinization specifically in the context of financial services. Thus, the work provides a better understanding of how organizational level drivers affect the organizational context of PI projects and consequently affect PI project success. There is little empirical research on determinants of PI project success. Our work explains how factors in the organizational context in which PI projects take place are affecting project outcome.
    • A new perspective of e-trust in the era of social media: Insights from customer satisfaction data

      Ramanathan, U; Williams, N.L.; Zhang, M; Sa-nguanjin, P; Garza-Reyes, J.A.; Borges, L.A.; Nottingham Trent University; University of Portsmouth; Global University Systems, 30 Holborn, London; University of Derby; et al. (IEEE, 2020-05-20)
      In this era of social media, products and services are sold globally using a few simple clicks online. In such online purchases, trust and familiarity are considered two important driving forces of consumer decision making. While online sales advocate high levels of flexibility and choices for consumers, they also hold the online service provider responsible for ensuring the security of the online user’s data. Using a Structural Equation Model (SEM) with data collected from the online service industry, we test the direct effects of ‘social media-induced purchase intention’ on customer satisfaction. We also test the mediating role of e-commerce/online sales (e-advertisement, e-safety and e-information) on customer satisfaction. In addition to social media advertising and information sharing, we find that a new factor – ‘e-safety’ – mediates the relationship between customer purchase intention and customer satisfaction. Our analysis indicates that online e-trust can be established between the customer and the service company when online purchases are made. At the same time, the quality of online information and e-safety of online payments make the service company trustworthy for future purchases. We relate data analysis directly to managerial decision making to avoid any delay in online customer services in the era of social media.
    • Performance measurement for supply chains in the Industry 4.0 era: A balanced scorecard approach

      Frederico, G.F.; Garza-Reyes, J.A.; Kumar, A; Kumar, V; University of Paraná, Curitiba, Brazil; University of Derby; University of the West of England (Emerald, 2020-05-06)
      The purpose of this paper is to present a theoretical approach based on the Balanced Scorecard (BSC) with regards to Performance Measurement (PM) in supply chains for the Industry 4.0 era. This paper combines the literature on PM and specifically the BSC related to the dimensions of supply chain in the context of Industry 4.0. Dimensions extracted from the literature based on supply chains within the context of Industry 4.0 showed a strong alignment with the four perspectives of the BSC, which make it suitable to be considered as a Performance Measurement System (PMS) for supply chains in this new context. From theoretical perspective, this study contributes to the limited literature on PM for supply chains in industry 4.0 era. The study proposes a supply chain 4.0 scorecard and strongly support researchers to conduct future empirical researches in order to get a deeper understanding about PM in supply chains in the Industry 4.0 era. As limitations, the theoretical framework proposed needs further empirical research in other to validate it and obtain new insights over the investigation conducted and presented into this paper. Practitioners can use this study as a guide to develop more effective Performance Measurement Systems (PMSs) in their organizations. This research is unique as it addresses a significant knowledge gap related to PM in Supply Chains in the Industry 4.0 era. It brings a significant contribution in terms of understanding how to measure performance in supply chains in this new era.
    • Benchmarking of cleaner production in sand mould casting companies

      Guilherme da Silva, H; Espíndola Ferreira, J.C; Vikas, K; Garza-Reyes, J.A.; Universidade Federal de Santa Catarina, Florianópolis, Brazil; University of the West of England; University of Derby (Emerald, 2020-04-29)
      The purpose of this research was to develop new sustainability indicators consistent with the sand mould casting industry, through Benchmarking of Cleaner Production (CP), in order to identify the levels of practice and performance of companies of the casting sector. In addition, a lean manufacturing checklist was specified in order to verify the presence of lean manufacturing techniques employed to eliminate waste towards CP. No previous work was found in the literature that attempts to assess practices and performance of companies performing sand mould casting (a significantly polluting manufacturing process) in the context of cleaner production and lean manufacturing. For the application of this benchmarking, nine companies from the sand mould casting sector were studied, where the profile of each company was analysed through 8 variables and 47 indicators. Data were obtained through face-to-face visits and questionnaire application in the companies, and the data were analysed both quantitatively and qualitatively. The results obtained were the diagnosis of companies' practices and performance resulting from their position in the benchmarking charts, as well as the identification of the areas in which companies should implement improvements aiming at achieving CP. This research was developed specifically for sand mould casting companies, and each process has its own characteristics. 14 companies that perform sand mould casting were invited to participate in this survey, but unfortunately five companies declined to participate. It is important to diagnose casting companies regarding cleaner production practices, performance and deployment potential. Thus, important negative issues in the company can be identified and, with this information, they can develop actions focused on cases that need more attention. In addition, this work contributes to evaluate the relationship and efficiency of improvement actions developed by companies in the context of both lean manufacturing and cleaner production, aiming to reduce or eliminate the environmental impact. The improvement of practices and performance of a company regarding cleaner production is considered to be beneficial to supply chain management in the context of sustainability, as the other participating companies are likely to seek ways to reduce environmental impact, and the diagnostics provided by this work may also be used by those companies.
    • Decision making for risk evaluation: integration of prospect theory with failure modes and effects analysis (FMEA)

      Sagnak, M; Kazancoglu, Y; Ozkan Ozen, Y.D; Garza-Reyes, J.A.; Izmir Katip Celebi University, Izmir, Turkey; Yasar University, Izmir, Turkey; University of Derby (Emerald, 2020-08-22)
      The aim of the present study is to overcome some of the limitations of the FMEA method by presenting a theoretical base for considering risk evaluation into its assessment methodology and proposing an approach for its implementation. Fuzzy AHP is used to calculate the weights of the likelihood of occurrence (O), severity (S) and difficulty of detection (D). Additionally, the Prospect Theory-based TODIM method was integrated with fuzzy logic. Thus, fuzzy TODIM was employed to calculate the ranking of potential failure modes according to their RPNs. In order to verify the results of the study, in-depth interviews were conducted with the participation of industry experts. The results are very much in line with Prospect Theory. Therefore, practitioners may apply the proposed method to FMEA. The most crucial failure mode for a firm’s attention is furnace failure followed by generator failure, crane failure, tank failure, kettle failure, dryer failure, and operator failure, respectively. The originality of this paper consists in integrating Prospect Theory with the FMEA method in order to overcome the limitations naturally inherent in the calculation of the FMEA’s Risk Priority Numbers (RPNs).
    • Assessing systematic literature review bias: kaizen events in hospitals case study

      Gonzalez Aleu, Flores, F.F., Perez, J., Gonzalez, R., Garza-Reyes, J.A.; University of Derby (IEOM Society, 2020-04)
      A systematic literature review (SLR) is a protocol used to identify publications, select relevant publications, collect data, conduct scientometric analyses, and report research results (SLR outcomes or findings). Despite the increasing use of SLR to assess the maturity or evolution of a research field, as Engineering Management, there are a limit number of publications focused to test SLR biases. Therefore, the purposes of this investigation are to test search field bias (precise SLR vs. sensitive SLR) and to identify statistically significant differences between SLR outcomes. In order to achieve these goals, a three steps methodology was used in three platforms/databases. First, a precise SLR in ProQuest (search terms only in abstract) was conducted to identify publications describing a single Kaizen event in a hospital. From these publications, five metrics were assessed: new authors per year, number of authors per paper, number of publications per year, Kaizen event duration (days), and number of tools used during the Kaizen event per paper. Second, a sensitive SLR in ProQuest (search term in full text) was conducted using the same search terms, exclusion criteria, and metrics from the first step. Third, t-test hypotheses were conducted in SPSS version 20 to identify statistically significant difference for each metric between precise SLR vs. sensitive SLR. The same three steps were used in two more platforms/databases: EBSCOhost and Scopus. Initial results from this ongoing investigation show statistically significant differences between precise SLR and sensitive SLR for some of the five metrics assessed, such as the number of publications per year. Final results will be available in November 2018.
    • A multi-objective linear optimization model for designing sustainable closed-loop agricultural supply chain

      Reyhani Yamchi, Hossein; Jabarzadeh, Younis; Ghaffarinasab, Nader; Kumar, Vikas; Garza-Reyes, J.A.; University of Tabriz, Tabriz, Iran; University of the West of England; University of Derby (IEOM Society, 2020-03)
      Demand for agricultural products will grow by nearly 70 percent in 2050 and high volume of chemical pesticides and agricultural fertilizers along with considerable waste in this sector induces serious environmental concerns. Hence it is not a priority but a necessity to modify unsustainable procedures to make them sustainable. The aim of this study is developing and analyzing a multi-objective (MO) linear mathematical model for sustainable close-loop agricultural supply chain (CLASC) with a deteriorating product to determine (1) the optimal flow to every echelon and (2) the optimal location of some facilities to achieve three objectives: reducing costs and carbon dioxide (CO2) emissions throughout the proposed supply chain (SC) network, and increasing the responsiveness. Finally, a numerical example is used to evaluate the optimization model.
    • Lean readiness level of the Azerbaijan construction industry

      Aghayev, Hajibaba; Kumar, Vikas; Rocha-Lona, Luis; González-Aleu, Fernando; Nadeem, Simon; Garza-Reyes, Jose; University of Warwick; University of Derby; University of the West of England; Instituto Politécnico Nacional, Mexico; et al. (IEOM Society, 2020-03)
      This paper identifies and measures the Lean readiness of the Azerbaijan construction industry. A survey questionnaire was utilised to evaluate the Lean readiness of this industry by measuring its quality practices and to test three hypotheses. The Lean readiness framework developed by Al-Najem et al. (2013) was taken as a basis for this study; however, there can also be seen some adaptations made from the framework developed by Diekmann et al. (2003). The questionnaire was sent to 57 Azerbaijan construction companies, from where 20 responses were obtained. The results derived from the questionnaire showed that the Azerbaijan construction industry is not ready to implement the Lean methodology. It also found that there remains a lack of trust between employee and employer relations. Lastly, it is evident that the size of the companies does not play any considerable role on Lean readiness of construction companies and does not make any sense for choosing construction prerequisites. This study can be beneficial for those Azerbaijan construction companies that are interested in the implementation of Lean construction, or which are interested to increase their level of competitiveness.
    • Eco-innovation practices’ adoption in the automotive industry

      Maldonado-Guzman, G; Garza-Reyes, Jose Arturo; University of Derby (Emerald, 2020-02-22)
      Eco-innovation is a construct that is gaining increasing interest from academics and researchers since it is commonly considered in the literature as one of the strategies that allow manufacturing companies not only to significantly reduce the negative impacts on the environment but also the generation of pollutants. However, little is known about the adoption of eco-innovation practices in manufacturing companies, particularly in the automotive industry. Therefore, this research has as main objective to fill this gap in the literature and explore the interdependence between eco-innovation of products, processes and management. The study is conducted through a research framework consisting of 3 measurement scales, 14 items and 3 hypotheses and an extensive review of the literature. A self-administered questionnaire was distributed to a sample of 460 companies in the automotive and auto parts industry in Mexico. Data were analyzed through Confirmatory Factor Analysis, Descriptive Statistics and Structural Equation Modelling. The results obtained show that product eco-innovation, process eco-innovation and management eco-innovation are good indicators for the adoption of eco-innovation practices for companies in the automotive and auto parts industry. The paper addresses a research gap in the academic literature in the eco-innovation field by providing evidence on the interdependence between eco-innovation of products, processes and management and the implementation of their practices in the automotive industry.
    • Learning orientation and innovation performance: the mediating role of operations strategy and supply chain integration

      Kumar, Vikas; Jabarzadeh, Younis; Jeihouni, Paria; Garza-Reyes, Jose Arturo; University of the West of England; University of Tabriz, Tabriz, Iran; University of Derby (Emerald, 2020-03-19)
      The purpose of this study is to explore the effect of operations strategy (cost, quality, flexibility, and delivery) and supply chain integration on innovation performance under influence of learning orientation. Taking a quantitative and deductive approach, a conceptual framework was developed and tested by analyzing data gathered through survey questionnaire from 243 UK manufacturing firms using structural equation modeling. Our findings show that learning orientation influences operations strategy and supply chain integration, but it does not have a direct impact on innovation performance. Additionally, quality and flexibility strategies affect innovation performance and supply chain integration positively, while cost and delivery strategies don’t have a significant effect on these variables. Operations strategy types (cost, quality, flexibility delivery) were studied as distinct variables whereas supply chain integration also has several dimensions but that has not been investigated separately in the present research. The findings are also based on limited 243 responses from UK manufacturing firms. Innovation performance of manufacturing firms can be improved through a more integrated supply chain if managers embody flexibility and quality capabilities in their operations and become learning oriented. The effect of supply chain integration on innovation performance and learning orientation on supply chain integration and operations strategy types have not been fully explored in literature. Also, having all four operations strategy types in a direct relation to supply chain integration and innovation performance is another original aspect of the current study.
    • A systematic literature review on machine learning applications for sustainable agriculture supply chain performance

      Sharma, Rohit; Kamble, Sachin; Kumar, Vikas; Gunasekaran, Angappa; Kumar, Anil; National Institute of Industrial Engineering; University of the West of England; California State University, Bakersfield; University of Derby (Elsevier, 2020-02-24)
      Agriculture plays an important role in sustaining all human activities. Major challenges such as overpopulation, competition for resources poses a threat to the food security of the planet. In order to tackle the ever-increasing complex problems in agricultural production systems, advancements in smart farming and precision agriculture offers important tools to address agricultural sustainability challenges. Data analytics hold the key to ensure future food security, food safety, and ecological sustainability. Disruptive information and communication technologies such as machine learning, big data analytics, cloud computing, and blockchain can address several problems such as productivity and yield improvement, water conservation, ensuring soil and plant health, and enhance environmental stewardship. The current study presents a systematic review of machine learning (ML) applications in agricultural supply chains (ASCs). Ninety three research papers were reviewed based on the applications of different ML algorithms in different phases of the ASCs. The study highlights how ASCs can benefit from ML techniques and lead to ASC sustainability. Based on the study findings an ML applications framework for sustainable ASC is proposed. The framework identifies the role of ML algorithms in providing real-time analytic insights for pro-active data-driven decision-making in the ASCs and provides the researchers, practitioners, and policymakers with guidelines on the successful management of ASCs for improved agricultural productivity and sustainability.
    • Impact of lean, agile and green (LAG) on business competitiveness: An empirical study of fast moving consumer goods businesses

      Udokporo, C.K.; Anosike, A.I.; Lim, M.K.; Nadeem, S.P.; Garza-Reyes, J.A.; Ogbuka, C.P.; University of Derby; Coventry University; Eneyserv Ltd, Nottingham (Elsevier, 2020-02-08)
      The adoption/utilisation of Lean, Agile and Green (LAG) practices in both the manufacturing and service sector is rising. However, there yet remain a research gap to precisely evaluate the relationship between LAG practices and business competitiveness (e.g, achieving reduction in cost, lead time and environmental recyclable waste). This research aims to explore this relationship, specifically in fast-moving consumer goods (FMCG) businesses. The hypothesised relationships are tested with data collected from 96 FMCG companies. Structural Equation Modelling is applied to evaluate different channels of achieving business competitiveness through the adoption of Lean, Agile and Green. The findings suggest that competitive outcomes vary with the adoption of LAG practices in specific product life cycle stages. This implies that awareness of the product life cycle concept is essential. A combination of LAG practices for the sole purpose of reducing environmental waste is negatively related to environmental waste reduction. LAG practices are more efficiently adopted when the adopters are equipped with expert knowledge on the paradigms and their individual practices. This research has approached the attainment of competitiveness in the FMCG businesses by analysing management efforts that improve cost performance, lead time and environmental sustainability aspects of business operations. The research has also considered the product life cycle stages in analysing the impacts of management efforts.
    • Performance factors for successful business incubators in Indonesian public universities

      Gozali, Lina; Masrom, Maslin; Zagloel, Teuku Yuri M.; Haron, Habibah N.; Garza-Reyes, Jose Arturo; Tjahjono, Benny; Purna Irawan, Agustinus; Daywin, Frans Jusuf; Syamas, Asril Fitri; Susanto, Sani; et al. (IJTech Universitas Indonesia, 2020-01-29)
      Measuring the performance of business processes is already a main concern for both faculty and enterprise players, since organizations are motivated to reach the productivity stage. Employing a performance achievement framework for the relationship between business incubator success factors will guarantee connection with commercial schemes, which support a high level of performance indicators in successful business incubator models. This research employs a quantitative approach, with the data analyzed using the IBM SPSS version 23 and Smart PLS version 3 statistical software packages. Employing a sample of 95 incubator managers from 19 universities which geographically located in Indonesia, it is shown that the image of business incubator factors has a positive effect on incubator performance. The study investigates the relationship between incubator performance and business incubator success factors in Indonesia. It was found that IT, as part of the business incubators’ facets/abilities, partially supports their performance; that the entry criteria directly support the performance of the incubators; that mentoring networks also support the performance, with good infrastructure systems as a moderating factor; that funding supports the performance of business incubators, also with good infrastructure systems as a moderating factor; and that university regulations and government support and protection enhance the performance of business incubators, with credits and rewards as a moderating factor. In addition, a variety of indicators from the local context affiliate positively to promote a community that highlighted the incubators’ strategies.
    • Behavioural factors on the adoption of sustainable supply chain practices

      Kumar, Anil; Moktadir, Md. Abdul; Rehman Khan, Syed Abdul; Garza-Reyes, Jose Arturo; Tyagi, Mrinal; Kazançoğlu, Yiğit; University of Derby; University of Dhaka, Bangladesh; Tsinghua University, Beijing, China; BML Munjal University, Gurgaon, India; et al. (Elsevier, 2020-02-05)
      Sustainable supply chain management (SSCM) has become a popular research topic among scholars as evidence suggests it has significantly contributed to achieve more environmentally conscious and socially responsible supply chains. Operational excellence (OE), on the other hand, can be achieved by incorporating SSCM practices within existing supply chain operations. However, due to human expertise, involvement and commitment towards excelling at sustainable and operational performance, the effective deployment of SSCM practices now depends on various humanbased behavioural factors (BFs). Human behaviour is dynamic in nature and hence has an effect on the implementation of SSCM practices. Nevertheless, research on BFs in view of SSCM practices is limited. To fill this knowledge gap, this study examines the nature of BFs for SSCM practices towards OE in supply chains, particularly within the context of the footwear industry of Bangladesh. In the first phase, the BFs were identified and determined through a literature review and empirical investigation. In the second phase, the Hesitant Fuzzy DEMATEL method was used to establish the cause-effect relationships among the factors. The influence of group validation by experts and a literature survey, along with managerial implications, was discussed and explained in the third phase of the study. The results suggest that the factor, 'organisation culture' is the most influencing behavioural factor, followed by 'commitment from higher authority'. Both theoretical and practical contributions of the study are drawn from its findings, helping footwear industry managers to more effectively adopt SSCM practices in the supply chain operations of their organisations to achieve OE.
    • A step to clean energy - Sustainability in energy system management in an emerging economy context

      Mangla, Sachin; Luthra, Sunil; Jakhar, Suresh; Gandhi, Sumeet; Muduli, Kamalakanta; Kumar, Anil; Plymouth Business School (PBS), University of Plymouth, Plymouth, PL4 8AA, United Kingdom; Department of Mechanical Engineering, State Institute of Engineering & Technology (Also Known As Government Engineering College), Nilokheri, 132117, Haryana, India; Operations Management Group, Indian Institute of Management, Lucknow, India; Kirloskar Pneumatic Company Ltd, Pune, Maharashtra, 411013, India; et al. (Elsevier, 2019-09-23)
      Due to high consumption of energy, its associated concerns such as energy security and demand, wastage of resources, and material-energy recovery are leading to the importance of sustainable energy system development. This is a high time to assess the sustainability in energy systems for meeting the requirements of energy with an enhanced economic, ecological, and social performance from a nation context. The energy system plays a significant role in deciding the economic progress of emerging economies such as India, China, Brazil, and Africa. In this paper, an original attempt has been made to list and evaluate important indicators for sustainability assessment of energy systems development and management in an emerging economy especially India. Firstly, based on the analysis of the extant literature and then followed by expert opinion, potential key sustainability assessment indicators for energy systems development and management were identified. Further, grey based Decision-Making Trial and Evaluation Laboratory technique to understand the causal interactions amongst indicators and segregate them into cause and effect groups, is used. This work can provide useful aids to decision making bodies, sustainability practitioners and business organisations in selective implementation, monitoring and control of sustainable strategies in energy systems development and management and meeting sustainable development goals of clean energy in a nation context.
    • Evaluating the impact of lean practices on environmental performance: evidences from five manufacturing companies

      Dieste, M; Panizzolo, R; Garza-Reyes, J. A.; University of Derby; University of Padova, Italy (Taylor and Francis, 2019-10-29)
      Previous evidence suggests that both lean and green production paradigms are focused on waste reduction and that lean practices help organizations to enhance sustainability objectives, and particularly environmental performance. However, the impact of lean practices on the environment is still unclear. This study therefore aims to analyse the relationship between lean and environmental performance in manufacturing with a strong empirical focus. This research was conducted in two main stages: first, an extensive review of the relevant literature was carried out, followed by a multiple case study analysis conducted in five manufacturing companies. Onsite data were collected from the firms during a five years’ time span of research and developing semi-structured interviews. Furthermore, a cross-case analysis was carried out to map the results. Findings indicate that the environmental performance of the companies analysed is generally enhanced in the long-term after the implementation of lean. Moreover, the results from the multiple case study suggest that the environmental performance of the firms under analysis is mainly improved by using JIT and TQM practices in a lean transformation context. The research findings provide further results remarking the possible negative impact of practices such as Kanban deliveries, 5S and TPM on various environmental performance indicators.
    • Social and environmental sustainability model on consumers’ altruism, green purchase intention, green brand loyalty, and evangelism

      Panda, T. K.; Kumar, Anil; Jakhar, S; Luthra, S; Garza-Reyes, J. A.; Kazancoglu, I; Nayak, S.S.; University of Derby; OP Jindal Global University, India; Indian Institute of Management Lucknow, India; et al. (Elsevier, 2019-09-26)
      Across the globe, the awareness for environmental degradation and its harmful effects is rapidly growing. The whole world has come together to work in the direction to protect the environment. Consumers are increasingly becoming cautious towards the impact of their consumption pattern on environment and organisations can attain a competitive edge by leveraging this cautiousness by offering them green products/brands. However, it is importance for the marketers to understand that how increasing levels of sustainability awareness impacts other factors which explain pro-environmental behaviour of customers. To fill the existing gap in the current literature in this regard, the current study aims to build a structural model which includes social and environmental sustainability awareness in measuring customer altruism, buying intention, loyalty and customer evangelism. The theoretical model extends the existing framework of the Theory of Planned Behaviour (TPB) and explores the decision-making framework regarding ethical behaviour. Through existing literature review and expert input, the indicators (variables) for each construct were recognised. After that, data was collected from 331 respondents through a structurally designed questionnaire; the hypothetical model was test using the Structural Equation Modelling (SEM) technique. The findings of the study indicate that sustainability awareness positively influence the consumer altruism which in turn enhances the consumer purchase intention, green brand loyalty and green brand evangelism and altruism can and can bridge value-action gap for green brands. Current analysis supports the view that there are significant positive associations among the identified constructs.