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Bitcoin has indeed been universally acknowledged as an investment asset in recent decades, after the boom-and-bust of cryptocurrency values. Because of its extreme volatility, it requires accurate forecasts to build economic decisions. Although prior research has utilized machine learning to improve Bitcoin price prediction accuracy, few have looked into the plausibility of using multiple modeling approaches on datasets containing varying data types and volumetric attributes. Thus, this paper aims to propose a bitcoin price prediction model.

In this research work, a bitcoin price prediction model is introduced by following three major phases: Data collection, feature extraction and price prediction. Initially, the collected Bitcoin time-series data will be preprocessed and the original features will be extracted. To make this work good-fit with a high level of accuracy, we have been extracting the second order technical indicator based features like average true range (ATR), modified-exponential moving average (M-EMA), relative strength index and rate of change and proposed decomposed inter-day difference. Subsequently, these extracted features along with the original features will be subjected to prediction phase, where the prediction of bitcoin price value is attained precisely from the constructed two-level ensemble classifier. The two-level ensemble classifier will be the amalgamation of two fabulous classifiers: optimized convolutional neural network (CNN) and bidirectional long/short-term memory (BiLSTM). To cope up with the volatility characteristics of bitcoin prices, it is planned to fine-tune the weight parameter of CNN by a new hybrid optimization model. The proposed hybrid optimization model referred as black widow updated rain optimization (BWURO) model will be conceptual blended of rain optimization algorithm and black widow optimization algorithm.

The proposed work is compared over the existing models in terms of convergence, MAE, MAPE, MARE, MSE, MSPE, MRSE, Root Mean Square Error (RMSE), RMSPE and RMSRE, respectively. These evaluations have been conducted for both algorithmic performance as well as classifier performance. At LP = 50, the MAE of the proposed work is 0.023372, which is 59.8%, 72.2%, 62.14% and 64.08% better than BWURO + Bi-LSTM, CNN + BWURO, NN + BWURO and SVM + BWURO, respectively.

In this research work, a new modified EMA feature is extracted, which makes the bitcoin price prediction more efficient. In this research work, a two-level ensemble classifier is constructed in the price prediction phase by blending the Bi-LSTM and optimized CNN, respectively. To deal with the volatility of bitcoin values, a novel hybrid optimization model is used to fine-tune the weight parameter of CNN.

The purpose of this paper is to propose an innovative solution for prioritizing “Whats” and “Hows” and resolving contradictions among “Whats” in House of Quality (HoQ).

Prioritization of the influence of the weights in correlation matrices of “Whats” and “Hows” (i.e. top roof and side roof) of HoQ and integration with TRIZ contradiction matrix have been studied. Explained through a case example of banking services, initially, contradictions among requirements of 180 customers have been identified by side roof matrix and then, the 12 by 12 non-technical contradictions matrix of service TRIZ have been used to suggest principles for resolving contradictions.

Findings imply that the use of roof and side roof weights can influence the priorities of “Whats” and “Hows.”

Findings may assist researchers and practitioners in resolving ambiguity of the voice of customers, which in turn make the results of HoQ more accurate.

A new approach has been proposed in this paper for resolving contradictions of customer requirements by service TRIZ and adjusting priorities of “Whats” and “Hows” in HoQ.

The purpose of this paper is to identify the relevant enablers and barriers related to technical education. It seeks to critically analyze the relationship amongst them so that policy makers can focus on relevant parameters to improve the service quality of technical education.

The present study employs the interpretive structural modeling (ISM) approach to model the crucial parameters of technical education. The parameters discussed are categorized under “enablers” and “barriers”. The enablers would help policy makers to improve and develop the curriculum of the technical education and the identifying barriers would help the decision maker to improve upon those variables.

The major findings of this study are to prioritize the strategic parameters in reducing the risks associated with technical education. The model also proposes a hierarchical structure classifying the parameters as drivers and enablers.

The study proposes a scientific way to model the enablers and barriers to become a progressive institution in the emerging era of globalization and modernization. This would help to prioritize the issues as the enablers and barriers are hierarchically structured and categorized.

The paper maps out a course of action and the adoption of the proposed framework would provide a competitive edge for India over others. Also, the various stakeholders would be satisfied, which would be beneficial for the system as a whole.

The application of ISM to the decision making process is the unique feature in the field of technical education in India. The integrated framework of policy related parameters would contribute towards overall growth and development.

The literature of lean six sigma (LSS) is flooded with frameworks. But to date, there has been no attempt to expose the inconsistencies in the existing frameworks and associated research trends. The purpose of this paper is to critically review 26 LSS frameworks and highlight inconsistencies. The study also helps in analysing research trends and constructs of LSS frameworks, and facilitates new applications.

It uses Scopus database and finalises 26 frameworks in the LSS domain considering a timeframe from 2000 to 2017, using a structured literature review approach and involving domain experts. It uses a battery of systematic requirements-based questions to understand trends and covers building blocks/constructs also.

It reveals inconsistencies at three different stages, namely, the framework stage, usage stage capturing existing research trends and construct stage. It also offers details at building block/construct level. Thus, it offers guidance in reducing inconsistencies and possible modifications in the existing frameworks. It not only exposes existing constructs and sub-constructs but also guides about the new upcoming changes in the business influencing the LSS domain. It also educates about the strengths and weaknesses of each framework.

This study tries to reduce inconsistencies, but does not offer new generalised or sector-specific framework.

This study will assist for modification/corrections in the existing frameworks by reducing inconsistencies and will encourage new frameworks to facilitate applications.

This is a unique study which offers frameworks-based review, portrays research trends and guides about constructs of a framework by exposing inconsistencies at each stage. It helps in reducing inconsistencies and offers guidance regarding modifications in the LSS framework considering upcoming challenges.

This study aims to identify the enablers of supply chain resilience (SCR) through a literature review and expert panel input in the context of Pakistan and the post-pandemic era. This study also aims to categorize and rank the identified enablers using expert panel input.

A review of the extant literature was conducted to investigate and identify the factors that contribute to SCR. The relative ranking of the enablers was carried out by a group of industry and academic experts. The expert panel was convened to compare the main categories and each enabler in pairs and to score the enablers using triangular fuzzy numbers.

This study identified 16 critical SCR enablers. Using the fuzzy analytic hierarchy process (AHP), these enablers were divided into three groups and analyzed. The results show that financial enablers, technology enablers and then social enablers are prioritized when it comes to SCR in emerging markets. The robustness of the ranking of enablers is tested through sensitivity analysis.

The results shall be helpful for policymakers and managers to understand the important enablers and also help allocate resources to important enablers. Managers will be able to formulate strategies to achieve SCR in an uncertain environment.

This is one of the first attempts to identify and rank the enablers of SCR in an emerging economy context.

Firms have been adopting lean manufacturing to improve their business performances. However, they are facing failures or less success in implementation, mainly due to lack of understanding in relating the lean practices (LPs) from the required performance measures perspective. In view of the lack of research and the importance of understanding them, the purpose of this paper is to prioritize LPs.

As LPs are scattered in the literature and a variety of performance measures are used, an extensive literature review is first carried out to identify the LPs and performance measures. The blend of interpretive structural modeling and interpretive ranking process interpretive tools is adopted in establishing the contextual relationship among LPs and then ranking them based on the performance measures. A three-dimensional priority matrix is proposed for better explanation of the results.

The proposed framework can help firms better understand LPs and their levels of importance in lean implementation.

The involvement of lean experts may produce some bias in evaluating the LPs.

The proposed framework can help practitioners to develop an industry-specific road-map for the result-oriented LP implementation. Based on the area of performance to be improved, practitioners can prioritize LPs for implementation.

This is the first study that provides a comprehensive review of LPs available in the literature and prioritizes them in accordance with performance with interpretive tools.

The ever-widening competitive global markets demand food business to demonstrate safe food supplies across the world. The causes of food borne illness are complex to determine and require a careful evaluation of all stages of food supply chain and food safety practices. The purpose of this paper is to systematically investigate the factors responsible for the assessment of food supply chain and evaluation of food safety system in India.

The study utilizes a combination of qualitative and quantitative approach by exploring expert’s opinion systematically using a semi-structured interview followed by careful grouping of responses using the grounded theory approach to build the research theme. The prioritization of the critical factors is carried out using Pareto analysis. The methodological review was carried out to identify factors and categorize them based on their impact on hierarchical logical relationship using total interpretive structural modeling approach to determine the enablers.

This paper attempts to deliver an inimitable list of seven vital factors for the effective design of evaluation system for food safety practices. The study provides a careful insight on the issue pertaining to designing of assessment system including competence building for assessor and availability of well-defined technical protocol. The recommendation for developing a robust food safety inspection system by implementing stricter regulation, enhancing competence and design initiatives is provided.

The study provides a unique list of factors for the assessment of food safety practices and develops the relationship. Food safety assessment is an integral part of food safety study which is systematically explored and conceptualized in this paper. The study is carried out using the opinion of Indian experts.

The purpose of this paper is to understand the deficiencies in Six Sigma project capability and empirically validating its impact on project success.

Deficiencies are identified from literature focusing on Six Sigma challenges or barriers. The study used a survey approach by circulating questionnaires to 400 Six Sigma professionals from 40 multinational organisations. The conceptual model is composed of 16 items measuring five constructs for hypothesis testing. Furthermore, structural equation modelling was used to identify the relationship between Six Sigma project capability deficiency and project success.

The findings of the study suggest that inadequate top management support, inadequate resources and change management and inadequate quality maturity form Six Sigma project capability deficiency and affect project success.

The study uses resource-based view to understand the deficiencies in Six Sigma project capability and their impact on project success. The study confirms that organisational capabilities in implementing Six Sigma affect the success of the projects.

The results of this study reveal that inadequate top management support, inadequate quality maturity of the organisation and inadequate resources and change management result into a deficiency in Six Sigma project capability. Quality managers in manufacturing and service organisations should attempt to improve these capabilities to achieve competitive advantage.

The study contributes to the literature by exploring the capability outlook of Six Sigma. The study attempts to fill the gap in Six Sigma literature by providing a structural model for understanding Six Sigma project capability deficiency and its impact on Six Sigma project success.

The purpose of this paper is to explore the link between TQM/Six Sigma practices and their impact on performance.

Based on the literature review of research that investigated the TQM and Six Sigma best practices and performance, the TQM/Six Sigma practices are classified into three key categories: top management commitment and support (TMCS), infrastructure and core practices. This paper proposes a path model linking these practices and performance. The empirical data were obtained from a survey of 91 Tunisian companies in different sectors. The research model was tested using partial least squares (PLS) technique based on SmartPLS software.

The result shows that the implementation of Six Sigma practices is based majorly on the TQM practices. Also, it reveals the positive impact of TQM/Six Sigma practices on performance. Furthermore, the analysis of path model reveals the relative interdependence and significant link between TMCS, infrastructure, core practices and performance.

The path model tested in this study combines the TQM/Six Sigma practices and reveals their link with performance, which enhance the research theory of both two approaches. Moreover, it will be a useful support for the quality expert on the effective integration of TQM and Six Sigma methods.

This study is the first one which studies the link between TQM/Six Sigma practices and company’s performance in the Tunisian context based on PLS technique.

The purpose of this paper is to develop and validate a model for key barriers to lean implementation in the Indian coal mining industry.

Interpretive structural modeling (ISM) has been used to develop a proper hierarchy and contextual relationship of key barriers to lean implementation in the Indian coal mining industry through literature review and expert opinion which is followed by the classification of barriers using Matrice d’ Impacts Croisés-Multiplication Appliquée á un Classement (MICMAC) and questionnaire-based survey to validate the ISM model using structural equation modeling (SEM).

In this study, 14 key barriers to lean implementation in the Indian coal mining industry have been identified, modeled and analyzed. The lack of top management commitment, financial constraints and lack of inter-departments co-ordination are found to be the most important barriers to lean implementation in the mining industry. The ISM-based model is validated using the SEM.

The analysis of data represents that relatively more participants were from the mines located in eastern India and the maximum participants were managers and executives holding different levels (lower, middle or upper), although key participants in different mines were encouraged to distribute the survey to other employees also.

This model on lean barriers would help the decision makers, researchers and practitioners to anticipate potential barriers to lean implementation and support the existing academic research on lean. Accordingly, the focus on the lean barriers can be prioritized for the better utilization of the available resources for eliminating or minimizing the barriers.

This paper is an original contribution of analysis of the lean barriers in Indian mining industry using the integrated ISM–MICMAC and SEM approach.