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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.

This chapter makes a brief incursion through a trajectory of over three decades of activism by the Centre for the Study of Violence at the University of São Paulo (Núcleo de Estudos da Violência in Portuguese, NEV) in Brazil, recovering the legacy of its forms of activism and academic reflection while analysing the interfaces between violence and democracy in Brazil. The 1980s in Brazil were marked by expectations of profound political and social changes in the context of democratic transition. After 21 years of dictatorship (1964–1985), the military gradually withdrew from government, returning the state’s executive branch to civilian representatives. This was a moment of optimism for progressive groups and social movements, which had fought to dismantle the tradition of arbitrariness and violations of rights perpetrated by the state during the military dictatorship. In this context, NEV was founded as a research unit linked to the Faculty of Philosophy, Letters and Human Sciences. Its core academic objective was to analyse and scientifically denounce the conjuncture of violence and human rights violations that remained recurrent; consequently, it demonstrated the continuity of unequal power relations, social and cultural practices that fuel authoritarianism in times considered not authoritarian.

In contemporary cities, private actors, such as luxury fashion houses, increasingly participate in projects, affirming themselves as relevant players in urban transformation. Based on the case of “SouPra” district (Milan, Italy), this chapter focuses on the effects of the opening of a fashionable artistic venue on the tourism development. It explores the promotional actions implemented by tourism entrepreneurs after the opening of the Prada Foundation. The analysis leads to two main results: actors in tourism exploit the urban brand conveyed by Prada, which becomes an integral part of the city branding. Fashion houses also act as marketing devices, producing new urban narratives that influence both the tourist and the real estate market.

Construction organizations' investment in effective talent-development programs is a key strategy in attracting, developing and retaining staff. Such programs are especially important given the current challenges in the construction workforce, including labor shortages, an aging workforce, generational differences in the workforce, supply chain disruptions and the need to effectively train staff in the skills that are essential in a constrained labor environment. To address these challenges, this study proposes a performance measurement strategy that construction companies can use as input to design their talent development programs.

The strategy intends to assess the performance of project managers and develop criteria that define categories of their performance, including the top performers' category. This enables construction organizations to provide each project manager with individualized training that addresses areas of weakness and in turn, develops the skills that correspond with being top performers. The proposed strategy was developed and tested by surveying the immediate supervisors of 187 project managers working for general and specialty contractors in the United States. Principal component analysis was used to develop a single performance construct from seven performance criteria.

This construct was used to organize the project managers into the categories of top, above-average and below-average performers. According to the findings, top-performing project managers have well-rounded skills in the areas of leadership, communication, technical proficiency and overall job knowledge.

The outcomes of this study can help construction organizations focus their talent-development programs on the skills most associated with PMs being top performers.

This study provides construction organizations with a comprehensive performance-measuring construct to focus their talent-development programs on the skills most associated with top-performing project managers. Researchers can use this study as a foundation for further understanding how performance is related to various construction professions.

Existing research of modern literature have shown that the phenomenon of digital entrepreneurship is lacking in robust theoretical foundations on several occasions. This article is a comprehensive literature study that focuses on the phenomena of digital entrepreneurship and offers views on the subject to provide insights into recent advancements in the area.

In order to achieve a conception of the phenomena, using the PRISMA flow chart, the significant findings were organised into themes, contexts and approaches. A comprehensive evaluation of the relevant previous research was carried out. Both the Web of Science and Scopus were utilised to locate, extract, select and evaluate relevant papers based on the keywords found during the search. In the end, papers from 92 different publications that are indexed by SSCI were chosen for this investigation.

This comprehensive literature analysis was to identify current research routes on digital entrepreneurship. In conclusion, this study generates outcomes that describe the process by which digital entrepreneurship are recognised and discussed: digital business models; digital entrepreneurship process; platform tactics; technology adoption; entrepreneurship and digital business.

By setting the framework for additional research development and motivating scholars to pursue this issue, the study contributes to the understanding of the conceptualisation of digital entrepreneurship.

The Design For Six Sigma (DFSS) methodology is one of the most important to achieving excellence in an organization’s product development process. This paper aims to propose a roadmap for product development based on the DFSS for the consumer durables manufacturing industries. The proposed roadmap presents a systematic approach to the phases of the product development process, integrating the statistical techniques and quality tools that should be used in each phase.

This study presents a detailed roadmap for product development, which was built by identifying gaps in the DFSS methods, based on previous studies on the subject. In this step, the opportunities are provided in all phases from creation to discontinuation of the product in the market. In addition, the roadmap presented was validated by team of stakeholders in the product development process of different industrial companies.

The proposed roadmap for the product development process based on six sigma design suggests a visual tool with sequential steps and techniques that allow you to follow the evolution of the development process from idea conception until the product is discontinued in the market. Identifying the priorities of organizations, especially the consumer, regarding the quality and reliability of the product.

The roadmap seeks to facilitate an understanding of the important stages of the product development process and to provide an approach to improving and optimizing the product before the manufacturing process step through the principles of DFSS methodology. This research provides a guide step by step to apply statistical techniques and quality tools in the product development process to achieve high quality and six sigma level in the manufacturing process.

The proposed roadmap of this research combines design for sigma and product development concepts, covering a wide spectrum of relevant activities that include the product development process, the application of statistical techniques and the design of high-quality durable consumer goods to match manufacturing technologies.

This paper aims to investigate the direct and indirect links between good corporate governance (GCG) and firm value using corporate social responsibility (CSR) as a mediating variable.

The data used in this research was collected from the Thomson Reuters Eikon ASSET4 database, involving 108 financial institutions belonging to 12 European countries listed on the stock exchange between 2007 and 2019. A multivariate linear regression analysis was conducted to test the hypotheses of this study.

Our results show that GCG has a positive effect on the firm value and CSR practices. Interestingly, the results indicate that CSR positively influences firm value. The results also reveal that CSR partially mediates the relationship between GCG and firm value.

This study contributes to the literature by providing evidence on how GCG increases firm value with the mediation mechanism of CSR in the link between GCG and firm value. To the best of our knowledge, it is the first research work documenting that GCG leads to better CSR, which ultimately results in increasing firm value of companies from the financial sector by bridging the information gap for this critical industry in the context of a developed market like Europe.

The purpose of this paper is to distinguish different types of sustainable digital entrepreneurs (SDEs) and explore their approaches toward enhancing organizational resilience.

Investigation of entrepreneur characteristics using Grounded Theory methodology; 12 semi-structured telephone interviews with (owner-)managers of digital-resilient small and medium-sized enterprises (SMEs) and start-ups in Germany; adaptation of a sustainability-digitalization-matrix for initial clustering; investigation of reoccurring patterns (within and between clusters) through variable-oriented content analysis; application of the capability-based conceptualization of organizational resilience for synthesis and extension.

First, the authors present a new typology of SDEs, including descriptions of the four main types (Process-Oriented System Thinker, Unconventional Strategist, Dynamic Visionary and Success-Oriented Opportunist). Second, the authors propose a conceptual framework with six success factors of organizational resilience. The framework accentuates the influence of SDEs on organizational culture and the macro-environment.

Digital sustainability and resilience are emerging management principles. The insights gained will allow (future) entrepreneurs to perform a self-assessment and replicate approaches toward enhancing SME resilience; for example, governing the co-creation of an organizational culture with a strong integrative view on sustainability and digitalization.

SMEs are characterized by high vulnerability and a reactive response to the disruptions caused by sustainability crises and digitalization. Blending sustainable and digital entrepreneurship at a micro-level, the authors identified the success factors underpinning organizational resilience that are associated with the characteristics of four types of SDEs.

This study theoretically investigates the extant literature published about circular economy and sustainable development to identify significant research themes, the most relevant authors, countries and journals.

Bibliometric analysis is used, followed by cluster formation using co-citation analysis. The clusters are discussed in-depth to identify emerging themes and future research areas.

By systematically reviewing 596 research articles, significant themes of research in this field were found. These include frameworks and indicators to define and assess the circular economy, circular business models and use cases, global and industrial contexts of application of circular economy and different dimensions of the circular economy.

Publications from only one database have been used. Only articles published in relevant academic journals have been used for the bibliometric analysis. For co-citation analysis and cluster formation, only articles with a high number of citations were selected.

The analysis of the various clusters revealed research areas that can be explored in future research to understand the circular economy better and implement its practices to attain sustainability.