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Cloud technology is extremely critical for the continuing progress of Industry 4.0 and it helps in pooling centralized information for the business. Further, it offers a platform for collaboration for improving the performance of the industry. This paper aims to investigate the factors affecting the implementation of cloud technology for boosting Industry 4.0 adoption in micro, small and medium enterprises (MSMEs) of the manufacturing sector.

A total of 14 enablers were considered for the case study which were obtained from the literature survey and shortlisted by the experts of the domain (academia and industries). The interpretive structural modelling (ISM) approach has been used as a methodology for exploring the relationships between the enablers. Matrices impact croises multiplication applique and classment (MICMAC) analysis has been carried out for the validation of the developed structural model. MICMAC analysis helps to identify driving power and dependency potential of all considered enablers.

The results of the investigation indicate that three factors, namely, system integration, project management and competitive pressure, were significant. These factors drive all other considered factors in the implementation process.

The opinions of the experts from the industry and academia were analyzed for the development of the hierarchical model and these inputs could be biased. This investigation intends to help the decision makers in the effective adoption of the cloud and Industry 4.0 technologies and for the formulation of the efficient implementation policies.

The present study aims to focus on cloud technology as well as Industry 4.0 in the context of manufacturing MSMEs and none of the previous investigations analyzed the enablers that influence the adoption of cloud technology for boosting Industry 4.0, especially using the ISM approach.

The goal of this research is to create a conceptual model that identifies the relationship between organizational learning and green human resource management practices and its contribution to the circular economy. The focus of this research is to identify the organizational learning and green human resource factors that lead to a more circular economic transformation.

The importance of the interaction of factors benefiting both individuals and organizations has been comprehensively explained by combining two well-known theories: resource-based view theory and organizational learning theory. As learning entails change, a climate of organizational learning combined with green human resource practices will efficiently help firms transition to a circular economy. The authors establish a conceptual model in this study, which they then apply to the small- and medium-sized manufacturing industry and report on in the second paper.

This study concentrates on the factors of organizational learning and green human resource management practices that help to create a circular economy after conducting a thorough literature analysis and consulting with experts.

The conceptual model can be applied to organizations in any industry. In the second part, the authors would investigate the interaction of the indicated factors and build their structural hierarchy using the total interpretive structural modelling method for the small- and medium-sized industries and then present the findings.

The proposed framework might facilitate decision-makers, practitioners and academicians to comprehend the relationship between organizational learning and green human resource management factors and their influence on organizations’ transition into a circular economy. The study’s findings will help HR managers clarify the significant organizational learning and green human resource management factors that play a vital role in transitioning organizations into a circular economy.

This research adds to our understanding of the intricate interactions between organizational learning and green human resource management as they relate to the circular economy. To the best of the authors’ knowledge, the conceptual model illustrating the inter-relationship between organizational learning and green human resource management is the first of its type, and it is a novel notion because no previous research has looked into it.

This chapter aims to contribute to the literature on sustainability in the public sector by discussing how human resource and human resource management can help to integrate environmental management into organizations and improve environmental performance. Public sector scholars have neglected the study of Green Human Resource Management (GHRM) until now. Nevertheless, implementing such practices could lead to positive outcomes regarding awareness of environmental issues, organizational reputation and attractiveness, job satisfaction and organizational performance. The authors discuss the relevance and the necessity of developing a field of research on GHRM in public organizations. Starting from a conceptual review of the main literature on GHRM, this chapter provided some directions for future research.

This study conceptualises the construct – green competencies. The concept is in the niche stage and needs further elaboration. Hence, to address the research gap, this study follows the steps proposed by Tranfield et al. (2003). The major part of the study comprises descriptive analysis and thematic analysis. Descriptive analysis of the selected 66 articles was examined with the classification framework, which contains year-wise distribution, journal-wise distribution, the focus of the concept, the economic sector, and dimensions of sustainable development. The paper conducts a thematic analysis of the following research questions. What are the green competencies and their conceptual definition? What are their dimensions?

This paper applies a systematic literature review of green competencies literature, extends the state-of-the-art using the natural resource-based view, and discusses future research directions for academicians and practitioners.

In recent years, there was considerable interest in green competencies (GC), as reflected in the surge of articles published in this genre. This paper asserts that green competencies are a multidimensional construct comprised of green knowledge, green skills, green abilities, green attitudes, green behaviours, and green awareness.

Despite the significance of green competencies, there has been a dearth of study to define the constructs and identify the dimensions. Hence, this study addresses the literature gap by conceptualisation and discusses dimensions of the construct.

The purpose of this study was to determine how environmentally specific transformational leadership (ETFL), green training (GT) and psychological green climate (PGC) affect environmental passion (EP) of employees which leads to pro-environmental behaviors (PEBs).

The context of the study was set in textile industry of Pakistan which holds a promising future in the international markets as an emerging export-based industry. Using purposive sampling technique, cross-sectional self-report data were collected from the employees of textile exporting firms (n = 239) of Pakistan. Hypotheses were tested using PLS-SEM.

The findings revealed that ETFL and PGC act as important predictors of EP, whereas GT plays no role in influencing EP. EP predicts green behavioral intention (GBI) of employees, in turn, GBI predicts employees' PEBs. Further, mediation analyses revealed that EP and GBI sequentially mediated the link between PGC and PEBs.

The present study is not free from its limitations. First, the study adopted cross-sectional design that prevents the causal inferences which the researcher can make from the population. Second, the present study adopted purposive sampling technique which is a non-probability sampling technique. Third, the constructs of this study were assessed with self-report measures which are associated with social desirability bias (Podsakoff and Organ, 1986) or common-method variance (Podsakoff et al., 2003). Hence, this research suggests on the future direction of research based on these limitations.

As per the results of this study, it is also suggested that managers may focus more on the overall organizational and psychological climate rather than on leadership styles alone. While conducting training, the leaders must pay close attention to training objectives to ensure that they do not lead to counterproductive behaviors.

This research adds to the literature in the area of PEBs at micro-level by focusing on how and why employees engage in PEBs.

This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms.

The optimal modulation index along with the switching angles are calculated for an 11 level inverter. Harmonics are used to estimate the quality of output voltage and measuring the improvement of the power quality.

The simulation is carried out in MATLAB/Simulink for 11 levels of symmetric MLI and compared with the conventional inverter design. A solar photovoltaic array-based experimental setup is considered to provide the input for symmetric MLI. Field Programmable Gate Array (FPGA) based controller is used to provide the switching pulses for the inverter switches.

Attempted to develop a system with different optimization techniques.

In today’s competitive world, the adoption of cloud enterprise resource planning (ERP) has become one of the critical criteria for running a successful business. In this regard, knowing the factors that influence cloud ERP adoption plays a significant role. The purpose of this paper is to rank the factors influencing the cloud ERP adoption in multi-national companies (MNCs) in India. This research would enable the cloud ERP vendors to identify the expectations of MNC customers and develop suitable strategies.

The research is being conducted among the cloud ERP consultants of designation middle managers and above from 29 different ERP consulting firms located in India. Analytical hierarchical processing approach was used to rank the factors influencing the cloud ERP adoption in MNCs located in India. The primary factors considered for this study are usability, assurance, agility, security and privacy, and vendor-related factors.

The three most preferred criteria were usability, assurance and agility. The five most preferred sub-criteria were data accessibility, availability, user friendliness, scalability, and data backup and recovery.

The study is limited to the perspective of cloud ERP consultants in India.

The outcome of this research provides cloud ERP vendors with a better understanding of factors that influence the adoption of cloud ERP in MNCs so that they can develop a focused strategy. From the MNCs point of view, the study provides a guideline on what factors they should consider while going for a cloud ERP implementation.

The research model is developed based on the cloud ERP literature, and the research results and findings would add value to the body of knowledge.

The purpose of this paper is to analyse the processes of collecting used non-returnable packaging. The objective is to increase the quality and quantity of recycling material used in the production of new packages.

A reverse logistics network is proposed, nevertheless the focus of the study is addressing the collection routing problem. Specifically a new “profitable visit algorithm” (PVA) based on the well-known Nearest Neighbor is proposed and tested, in both real and simulated scenarios, in order to achieve higher volume of collected material while lowering the cost of collection.

The proposed algorithm is set to compete against the well-known Nearest Neighbor. The “PVA” showed a far better performance than the Nearest Neighbor. The latter was assessed with real data in a real scenario and was also confirmed by a simulation.

Further research should envisage stochastic models and tighter time constraints.

Managers can use the algorithm in similar scenarios to address different routing needs. New business activities could be foreseen by starting a logistics scheme of this type. Additionally, new savings in material procurement processes could be achieved in current operations.

Social responsibility and environmental awareness can be approached by this type of endeavors. While reducing waste disposal, the recovering of these materials yields savings and offer new labor opportunities for people.

The “PVA” introduced in this paper, showed substantial advantages. First it automatically determines the visit frequency for each client. Also, it evaluates whether a visit should be granted or not based on its “profitability.” The latter ensures that even if the routing circuit is broken at any moment, the company will not lose “profit.” Additionally, this research provides performance evaluation in real and simulated scenarios, which is hard to obtain in a single study.

 Reverse logistics, Recycling, Routing algorithm, Non-returnable packages, Real scenarios

 Research type

Objetivo

Este artículo analiza los procesos de recolección deenvases no retornable usados. El objetivo es aumentar la calidad y cantidad de material reciclable usado en la producción de nuevos envasados.

Se propone una red de logística reversa, no obstante el enfoque del estudio es abordar el problema de la ruta de recolección. Específicamente, se propone un nuevo “algoritmo de visita rentable” basado en el bien conocido Vecino Más Próximo y se testea en ambos escenarios reales y simulados, para poder lograr un volumen más alto de material recolectado y a su vez disminuir los costo de recolección.

El algoritmo propuesto está definido para competir contra el bien conocido Vecino Más próximo. El “algoritmo de visita rentable” mostro un rendimiento mucho mejor que el de Vecino Más próximo. Este último se evaluó con datos reales en un escenario real y también se confirmo a través de una simulación.

Investigaciones futuras deberían visualizar modelos estocásticos y restricciones de tiempo más limitadas.

Administradores pueden usar el algoritmo en escenarios similares para dirigir las diferentes necesidades de la ruta. Nuevas actividades de negocios podrían ser previstas iniciando un esquema logístico de este tipo. Adicionalmente, nuevos ahorros en procesos de material de adquisición podría ser logrado en las operaciones actuales.

La responsabilidad social y conciencia ambiental puede ser abarcado con este tipo de actividad. No sólo se reducen los residuos, pero también la recuperación de estos materiales genera ahorros y ofrece nuevas oportunidades de trabajo para las personas.

El “algoritmo visita rentable” introducido en este articulo, mostró ventajas substanciales. Primero, determina automáticamente la frecuencia de visitas para cada cliente. Además, evalúa si una visita basada en su “rentabilidad” debería ser dada o no. Esta última asegura que aunque el circuito de la ruta se quiebra en cualquier momento, la empresa no perderá “ganancias.” Adicionalmente, esta investigación provee evaluaciones de desempeño en escenarios reales y simulados, lo cual es difícil de obtener en un sólo estudio.

Trabajo de investigación

Objetivo

Este artigo analisa o processo de coletade embalagens não retornáveis usadas. O objetivo é aumentar a qualidade e as quantidades de materiais recicláveis utilizados na produção de novas embalagens.

Uma rede de logística reversa é proposta, embora o enfoque da pesquisa é abordar o problema da roteamento da coleta. Especificamente, um novo algoritmo de “Profitable Visit” baseado no conhecido Nearest Neighboré proposto Dois cenários são testados, um real e um simulado, com objetivos deatingimento de um volume maior de material coletado e também de diminuir os custos decoleta.

O algoritmo foi proposto para competir com o conhecido Nearest Neighbor. O algoritmo de “Profitable Visit” mostra um rendimento melhor que o Nearest Neighbor. Este último foi avaliado com dadosreais em um cenário real e também confirmado através de simulação.

Pesquisas futuras deveriam abordar modelos estocásticos e maiores restrições de tempo.

Gerentes podem utilizar o algoritmo em cenários similares para gerenciar diferentes necessidades de roteamento de coleta. Novos processos de negócios poderiam ser previstos com base em projetos logísticos deste tipo. Adicionalmente, ganhos adicionais em processos de compra de materiais poderiam ser obtidosem operações presentes.

A responsabilidade social e a consciência ambiental podem ser abordadas com este tipo de projeto. Junto com a eliminação de resíduos, a recuperação desses materiaistambém gera renda e oferece novas oportunidades de trabalho para as pessoas.

O algoritmo Profitable Visit” apresentadoneste artigo mostra vantagens substanciais. Primeiro, determina automaticamente a freqüência de visitas para cada cliente. Também, avalia se uma visita com base na “rentabilidade” deveria ocorrer ou não. Este aspecto assegura que quando o circuito da rota é modificado em qualquer momento, a empresa não perderá seus “ganhos.” Adicionalmente, esta pesquisa fornece avaliações de desempenho em cenários reais e simulados, o que é difícil de ocorrer em um único estudo.

Trabathos de pesquisa