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This paper aims to propose a system for generating actionable knowledge from Big Data and use this system to construct a comprehensive knowledge base (KB), called GrandBase.

In particular, this study extracts new predicates from four types of data sources, namely, Web texts, Document Object Model (DOM) trees, existing KBs and query stream to augment the ontology of the existing KB (i.e. Freebase). In addition, a graph-based approach to conduct better truth discovery for multi-valued predicates is also proposed.

Empirical studies demonstrate the effectiveness of the approaches presented in this study and the potential of GrandBase. The future research directions regarding GrandBase construction and extension has also been discussed.

To revolutionize our modern society by using the wisdom of Big Data, considerable KBs have been constructed to feed the massive knowledge-driven applications with Resource Description Framework triples. The important challenges for KB construction include extracting information from large-scale, possibly conflicting and different-structured data sources (i.e. the knowledge extraction problem) and reconciling the conflicts that reside in the sources (i.e. the truth discovery problem). Tremendous research efforts have been contributed on both problems. However, the existing KBs are far from being comprehensive and accurate: first, existing knowledge extraction systems retrieve data from limited types of Web sources; second, existing truth discovery approaches commonly assume each predicate has only one true value. In this paper, the focus is on the problem of generating actionable knowledge from Big Data. A system is proposed, which consists of two phases, namely, knowledge extraction and truth discovery, to construct a broader KB, called GrandBase.

This study aims to reduce the redundant weight of the anti-roll torsion bar brought by the traditional empirical design and improving its strength and stiffness.

Based on the finite element approach coupled with the improved beluga whale optimization (IBWO) algorithm, a collaborative optimization method is suggested to optimize the design of the anti-roll torsion bar structure and weight. The dimensions and material properties of the torsion bar were defined as random variables, and the torsion bar's mass and strength were investigated using finite elements. Then, chaotic mapping and differential evolution (DE) operators are introduced to improve the beluga whale optimization (BWO) algorithm and run case studies.

The findings demonstrate that the IBWO has superior solution set distribution uniformity, convergence speed, solution correctness and stability than the BWO. The IBWO algorithm is used to optimize the anti-roll torsion bar design. The error between the optimization and finite element simulation results was less than 1%. The weight of the optimized anti-roll torsion bar was lessened by 4%, the maximum stress was reduced by 35% and the stiffness was increased by 1.9%.

The study provides a methodological reference for the simulation optimization process of the lateral anti-roll torsion bar.

Engaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings.

We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.

The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.

These findings help managers optimize their webcare strategy for better business results and develop automated webcare.

We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.

Free guided walking tours are one of the most successful tourism segments in the digital platform economy. It is beginning to be associated with negative impacts in some of the destinations where it is spreading rapidly. Although the platform economy is generating increasing academic interest, the free tour model remains largely unexplored area in the literature. This study aims to examine how such activity affects cultural destinations.

Focussing on the largest Free Tours platform operating in Spain, GuruWalk, the methodology used analyses its impact in six cultural destinations on two of the sustainability dimensions: the territorial dimension and the governance, through an exploratory study.

The findings help to understand the differences that such activity generates in each destination depending on the phase of its life cycle, and to implement, if necessary, corrective measures. The research confirms that the impacts differ according to the tourist destination’s maturity, concluding that such activity contributes to the increase of tourist agglomerations and the overcrowding of cultural destinations in their middle and mature life cycles. The findings highlighted the importance of the role of local governance on free tour activity.

The main contribution is the association of the impacts they produce (especially in terms of massification) with destination life cycle phases. There were no similar precedents with a spatial or territorial analysis to reliably demonstrate not only that this activity has an impact on the territory but also what type of impact is produced.

The paper aims to promote the development of intelligent materials and the 4D printing technology by introducing recent advances and applications of additive layered manufacturing (ALM) technology of intelligent materials and the development of the 4D printing technology. Also, an arm-type ALM technology of shape memory polymer (SMP) with thermosetting polyurethane is briefly introduced.

This paper begins with an overview of the development and applications of intelligent materials around the world and the 4D printing technology. Then, the authors provide a brief outline of their research on arm-type ALM technology of SMP with thermosetting polyurethane.

The paper provides the recent developments and applications of intelligent materials and 4D printing technology. Then, it is suggested that intelligent materials mixed with different functional materials will be developed, and these types of materials will be more suitable for 4D printing.

This paper overviews the current developments and applications of intelligent materials and its use in 4D printing technology, and briefly states the authors’ research on arm-type ALM technology of SMP with thermosetting polyurethane.

The purpose of this study is to investigate the perceived effects between soft management practices, employee behaviours and the implementation of digital technologies in manufacturing plants, as well as how these relate to the emergence of digital waste.

This paper uses case-based research. Data was collected in two large manufacturing companies based in Norway and Sweden through semi-structured interviews with two management representatives and four shop-floor employees. The data was used to evaluate 29 variables describing lean- and total quality management (TQM)-associated employee behaviours and soft management practices, in light of digital transformation.

The results suggest that several variables were positively influenced by the digital transformation process. These were top management leadership, middle management involvement, employee education, corporate social responsibility focus, innovation, knowledge sharing, work-family balance, psychological capital, job satisfaction and career commitment. Training employees, creativity, discretionary effort, turnover intention and proactivity appear to be negatively influenced by digital transformation The findings also indicate that several soft management practices and employee behaviours were not only influenced by manufacturing digitalization but also themselves influenced the process. The potential for digital waste creation was also detected in several variables, including reward and recognition and training employees.

Managers, practitioners and academics may learn about the importance of certain managerial practices and employees’ behavioural needs during the digital transformation process. The findings may help in prioritizing TQM and soft lean management practices and certain employee behaviours during the digital transformation and in creating awareness of digital waste.

This study builds on several existing studies discussing the impact of digital transformation on soft management practices and employee behaviours. It provides insights from a lean and TQM angle and offers a means of prioritizing certain practices and behaviours during a digital transformation. This study also highlights the significance of digital waste.

The purpose of this paper is to analyze the potential of strategic environmental assessment (SEA) to mainstream consideration of climate change adaptation (CCA) in Bangladesh, particularly for the coastal zone, to improve disaster risk reduction (DRR) strategies in this region. Continuing climate risks require adaptation at all levels of society. The densely populated and resource-rich coastal zone of Bangladesh is at risk to the impacts of climate change.

This research is based on secondary sources (gray and published literature) of information on climate change impacts on the coastal zone of Bangladesh. The sources include research reports, online publications, governmental reports, scientific journals, international reports, books, journal articles and other academic resources on SEA, climate change adaptation and mitigation, and DRR. In addition to examining SEA in Bangladesh, this paper investigates SEA cases in different countries to obtain insights from the successful application of SEA for CCA.

The paper draws on several cases from different countries demonstrating that SEA has a significant potential to coordinate CCA objectives. The findings reveal that the appropriate use of SEA can enable DRR through CCA.

This study argues that SEA has a potential role in supporting CCA.