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The new customer churn prediction (CCP) utilizing deep learning is developed in this work. Initially, the data are collected from the WSDM-KKBox’s churn prediction challenge dataset. Here, the time-varying data and the static data are aggregated, and then the statistic features and deep features with the aid of statistical measures and “Visual Geometry Group 16 (VGG16)”, accordingly, and the features are considered as feature 1 and feature 2. Further, both features are forwarded to the weighted feature fusion phase, where the modified exploration of driving training-based optimization (ME-DTBO) is used for attaining the fused features. It is then given to the optimized and ensemble-based dilated deep learning (OEDDL) model, which is “Temporal Context Networks (DTCN), Recurrent Neural Networks (RNN), and Long-Short Term Memory (LSTM)”, where the optimization is performed with the aid of ME-DTBO model. Finally, the predicted outcomes are attained and assimilated over other classical models.

The features are forwarded to the weighted feature fusion phase, where the ME-DTBO is used for attaining the fused features. It is then given to the OEDDL model, which is “DTCN, RNN, and LSTM”, where the optimization is performed with the aid of the ME-DTBO model.

The accuracy of the implemented CCP system was raised by 54.5% of RNN, 56.3% of deep neural network (DNN), 58.1% of LSTM and 60% of RNN + DTCN + LSTM correspondingly when the learning percentage is 55.

The proposed CCP framework using the proposed ME-DTBO and OEDDL is accurate and enhances the prediction performance.

JIT is a manufacturing philosophy, successfully implemented mostly in large‐scale industries. Research reviews indicate it is rarely adopted in SMEs; there appear to be problems in promoting and deploying the concept of JIT to such organizations. Reports on a study performed in SMEs to select and prioritize various techniques for the implementation of JIT in a seasonal order‐manufacturing environment through the QFD technique. Analysis indicates that buffer stock removal and lot size reduction were the key issues to be assigned higher priority than throughput improvement. However, this prioritization has to be carried out on a case‐by‐case basis as each manufacturing system has different predefined goals and targets, and is set within a different context.

The purpose of this paper is to determine the use of BLA along with SiC as economical reinforcements to enhance the mechanical behavior of hybrid composite. The purpose of this research is the development of cost-effective aluminum hybrid metal matrix composites.

The present research work investigation evaluated the mechanical properties of Al-4.5%Cu alloy, Al-4.5Cu/10SiC, Al-4.5Cu/10SiC/2BLA and Al-4.5Cu/10SiC/4BLA composites by the Stir casting method. The fabricated composites were analyzed using optical microscopy (OM), scanning electron microscopy (SEM), and hardness and tensile test.

The microstructure modification with the addition of reinforcement particles in the matrix alloy and clear interface in between matrix and particles are observed. The density of the composite increased with the addition of SiC and decreased with the addition of BLA in comparison with that of matrix alloy. The hardness and tensile strength of the single-reinforced composite and hybrid composites improved with the addition of reinforcement particles. The strengthening of composites was due to load-bearing capacity of reinforcement particles over the matrix alloy and increased dislocation density of composites materials. The tensile failure mechanism of the composites is reveled with SEM analysis.

The papers reports the development of cost-effective and light weight aluminum hybrid composites with remarkable enhancement in the mechanical and tribological properties with the addition of BLA as economical reinforcement along with SiC.

The density, hardness and tensile values of fabricated aluminium composites were presented in this paper for the use in the engineering applications where the weight and cost are consider as a primary factors.

The present study aims to assess the role of supply chain resilience as an operational excellence approach to deal with disruptions caused by coronavirus pandemic in the food supply chain of an agri-food supply firm.

The case study method was used to analyse the disruptions faced by the agricultural food supply chain during the pandemic. The study applies a dynamic capability theory as a foundation to develop a contextualised resilience framework for agri-food supply chain to achieve operational excellence. The case has been analysed by using situation-actor-process (SAP) and learning-action-performance (LAP) framework.

The SAP aspect of framework points that the flexibility amongst actors for a resilient agriculture supply chain worsened due to the lockdown measures post COVID-19. The LAP aspect of framework suggests how resilience can be built at the supply, demand and logistics end through various proactive and reactive practices such as collaboration, coordination, ICT and ground-level inputs. Lack of commitment and inadequate support from top management towards supply chain resilience are also observed as significant challenges to maintain operational excellence during the pandemic.

One of the major implications of the study is that a mix of capabilities rather than a single capability can be the most appropriate way for making the supply chain resilient to maintain operational excellence during the pandemic. However, the sources of disruptions need to be duly recognised to derive the best-contextualised resilience framework for agri-food supply chains.

The development of a contextualised research framework as well as research propositions for analysing supply chain resilience are the major contribution of this study.

Growth in a number of the supply chain (SC) disruptions threatens the enterprises globally. Earlier studies and reports say that many organizations go out of businesses within two or three years after they experience a major disruption. Therefore, companies in today’s volatile business arena need to possess the necessary resilience level to combat supply china disruptions. This is even more important for organizations of developing nations, which are constantly struggling to gain the advantages of globalization and to grab the new opportunities. Thus, this paper aims to help organizations understand their SC resilience level through a framework.

The methodology comprises integrated Delphi – fuzzy logic approach in identifying formative elements of SC resilience from a diverse resilience related body of knowledge and distinguish key obstacles of SC resilience based on their performance level.

Findings reveal that SC flexibility components such as sourcing, manufacturing and logistic flexibility are the major contributors of SC resilience index of case organization. Similarly, lack of risk management culture, inter-organizational relationships, information sharing and integration of SC stakeholders are the major inhibitors of resilience. Thus, the organization needs to overcome these identified obstacles to enhance their SC resilience level.

Present study offers a novel focus of research on SC resilience measurement that is significant for understanding the level of immunity enterprises possess to unanticipated SC interruptions, and the ability to bounce back after an unforeseen event.

This paper proposes an integrated Delphi – fuzzy logic framework for measuring SC resilience. In doing so, the study identifies key potential inhibitors of SC resilience of the case company under study.

The purpose of this paper is to analyze the impact of integrated management systems (IMSs) on sustainability (based on the triple bottom line (TBL) concept). To accomplish this objective, this paper seeks to answer the following research questions: How can IMS impact organizational sustainability performance? And, how the key challenges of IMS can influence companies in practice?

A case-based approach is used based on the following four cases from different sectors: an electric power distributor; an environmental consulting firm; a public transport firm; and a firm with a broad portfolio of equipment, products and provisions for industrial services in different markets.

The results show that the integration of management systems was driven by the companies' strategies toward sustainability. The stakeholders' perception is that a firm's image as a sustainable company also enhances environmental and social performance. The economic performance was not emphasized. Companies noted that the main challenge was motivating and engaging human resources.

This paper shows that sustainability was not a motivation for implementing an IMS. But, implementing an IMS was a driver of sustainability performance. Also, the relationship between IMS and organizational performance can be presented based on TBL perspectives, and implementing an IMS can be challenging in practice.

This paper aims at reviewing the extant knowledge management (KM) research field within a strategic alliance context to understand the historical roots, its temporal progression, current state and potential future in a meaningful way.

Data for this study was retrieved from the Scopus database using a systematic literature search process. The bibliometric characteristics of 393 research documents were analyzed using bibliometric and structured network analysis.

The findings of the study suggest that the publication in the field have been growing with an average rate of 8.48%. This analysis also lists the most productive and impactful authors, main outlets, and the most impactful secondary and primary publication in the field. In addition, the conceptual and intellectual structure of the research field was constructed and discussed.

This paper uses an objective and quantitative approach by reviewing the related publications and virtually included all the relevant publications in the analysis, which was seen to be uneconomical when doing traditional literature reviews.

The purpose of this paper is to analyze the impact of the integration of management systems that include economic, social and environmental standards on economic performance.

The methodology consists of analyzing reports of certified companies and secondary data on economic performance indicators. Two sample groups of companies were compared against each other. The core group is composed of companies that have integration of certification on each triple bottom line (TBL) dimensions, economic, environmental and social (ISO 9001 and ISO 14001 and OHSAS 18001). The control group is composed of companies of the same size and sector (mirror sample) but without standards related to social and environmental dimensions. The comparative analysis of both core and control groups was performed based on non-parametric methods, such as the mood median test and structural equation modeling.

Several economic performance indicators of both groups were statistically analyzed and compared. The results show that companies with integrated management systems (IMS) (core group) on a TBL perspective showed better economic performance compared to other companies of the control group. Moreover, this study shows that the industry sector influences this relation, particularly in the energy, chemical and petrochemicals, services and transportation sectors.

For executives and managers, the results suggest that the amount invested in IMS in a TBL perspective increases the economic performance of companies, resulting in profitability, increased equity and sales growth. It reinforces the win–win perspective on sustainability in companies instead of the mindset on negative trade-offs on economics.

This research sheds light on controversies, discussed in the literature, concerning the positive vs negative effects on the economic performance of IMS, with social and environmental standards. The results show that economic performance is improved in companies of the core group.