Search results

Heavy industrial construction often relies on large mobile cranes to erect equipment and pre-assembled modules. Engineering calculations are required for the lifting analysis where lifting capacity is analyzed to ensure the feasibility of the lifting scenarios. Such engineering calculations are often presented in static formats, e.g. two-dimensional or three-dimensional models. However, it is difficult to help practitioners (e.g. lifting engineers, site crews and operators) understand the complexity of the lifting process and thus operational decisions are often made intuitively. Therefore, this paper aims to introduce a game-based simulation system to allow for interactive analysis of the lifting process to improve lifting efficiency and safety.

The proposed method treats the mobile crane as a robot with degree-of-freedoms, and the movements are simulated in the Unity game environment. The lifting capacity is calculated dynamically based on the lifting object weight, rigging weight and lifting radius.

Compared with the four-dimensional visualization, this development has added a dimension of real-time interactive simulation; this allows the users to understand the complexity and feasibility of the lifting process.

The developed prototype has been tested and validated using a real case study from a heavy industrial project with the possibility of generalizing crane lifting configurations.

Modular construction is widely adopted and used in the construction industry to improve construction performance with respect to both efficiency and productivity. The evaluation of design options for modular construction can be iterative, and thus automation is required to develop design alternatives. This research aims to explore the potential of utilizing the generative design approach to automate modular construction for residential building structures in urban areas such as New York City.

The proposed research methodology is investigated for a systematic approach to parametrize design parameters for modular construction layout design as well as incorporate design rules/parameters into modularizing design layouts in a Building Information Modeling (BIM) environment. Based on current building codes and necessary inputs by the user, the proposed approach enables providing recommendations in a generative design method and optimizes construction processes by performing analytical calculations.

The generative design has been found to be efficient in generating layout designs for modular construction based on parametric design. The integration of BIM and generative design can allow industry practitioners to fast generate design layout with evaluations from constructability perspectives.

This paper has proposed a new approach of incorporating generative design with BIM technologies to solve module layout generations by considering design and constructability constraints. The method can be further extended for evaluating modular construction design from manufacturability and assembly perspectives.

This research aims to propose a comparative environmental analysis of conventional and prefabricated construction techniques utilizing a building information modelling (BIM) technique.

A set of indicators are selected to assess the environmental emissions throughout the construction life cycle, based on BIM platform. An existing project involving ten apartment buildings in Shanghai is selected as a case study.

The results reveal that prefabricated construction demonstrates environment-friendly performance with some exceptions of acidification and mineral resource consumption. Environmental impacts can also be further reduced by increasing the projected area ratio and percentage of project prefabrication.

Overall, the proposed method can be used to identify relevant environmental merits and for decision-making of appropriate construction techniques in building construction projects.

The purpose of this paper is to investigate firm behaviors on patent examination request under the deferred patent examination system in Korea. The authors examine firm decisions on whether and when to request patent examinations when they face both uncertainty about invention’s value and market competition.

The authors provide a simple theoretical model and test a couple of hypothesis using Korea patent data. The authors employ KIPO (Korean intellectual patent office) patent applications data during 2006–2009 and incorporate it with firm financial data retrieved from1 Korea investor service-financial analysis system (KIS-FAS) database in Korea. The authors use the variation in the probability of lapsed patent applications filed in the same year and in the same technology field (at the four-digit IPC class level) of a patent application i as a proxy for the value of uncertainty, and further use one minus a firm’s market share (at the three-digit SIC industry level) as an indicator of the market competition faced by the firm/applicant.

The authors find that the examination requests of firms in Korea have interesting bipolar distribution, and both uncertainty about an invention’s value and market competition have significant impacts on firm’s decision for examination request. Applicants tend to utilize option value of waiting when uncertainty is high, but market competition attenuates the option value: the higher the competition, the less likely applicants are to delay or forego examination.

The authors’ study makes interesting contributions to the literature on the optimal design of the patent system in general and the deferred patent examination request system in particular. By considering the roles of both uncertainty and market competition in firm decisions, it provides a more comprehensive perspective on the deferred patent examination system. The study also provides empirical evidences on the broader research topic regarding firm decision for irreversible investment when faced with both uncertainty and competition, for which a strand of theoretical literature exists but empirical literature is largely limited. This study, which explicitly takes into account uncertainty and market competition, extends this line of empirical literature and fills the gap in the literature.

Grounded in the Social Exchange theory, this study focuses on the perception of digital leadership and innovative work behaviors. It also examines the complex effects of leader-member exchange, learning orientation, and innovation capabilities.

We undertake a quantitative approach using a two-wave longitudinal field survey of 440 employees and managers from various backgrounds working in the automobile industry in France.

The findings based on Structural Equation Modeling reveal that the perception of digital leadership leads to innovative work behavior while leader-member exchange moderates between the perception of digital leadership and learning orientation. The findings also support the mediating roles of learning orientation and innovation capabilities.

The study contributes important policy suggestions, raises queries for additional investigation, and suggests theoretical and practical implications for leadership and organizational environmental factors to foster innovative work behaviors in organizations.

The purpose of this paper is to describe an application of Multi-Criteria Decision Making (MCDM) technique for the selection of waste treatment and disposal technology for municipal solid waste (MSW).

The proposed approach is based on the integration of Delphi and Analytic Hierarchy Process (AHP) techniques. A model has been proposed to evaluate the best treatment and disposal technology. Expert opinions have been incorporated in the selection of criteria. AHP has been used to determine the weights of criteria, followed by ranking of the available technologies.

Delphi method was used to derive appropriate evaluation criteria to assess the potential alternative technologies. A set of identified holistic criteria was used, representing the environmental, social, and economic aspects, as compared to the sub-criteria concept generally found in existing literature. Quantitative weightings from the AHP model were calculated to identify the priorities of alternatives. The study provides a simple framework for technology selection as compared to the complex models present in the literature, reducing the uncertainty, cost and time consumed in the decision-making process.

The model identifies the optimal technologies for the handling, treatment and disposal of MSW in a better economic and more environmentally sustainable way. The study provides a simple framework for selection as compared to the complex models present in the literature, reducing the uncertainty, cost and time taken by the decision-making process.

The paper highlights a new insight into MCDM techniques to select an optimum treatment and disposal technology suitable for MSW management in India. The study identifies a minimal relevant set of evaluation criteria, and appropriate technologies for the handling, treatment, and disposal of MSW in a more economic and environmentally sustainable way.

The purpose of this paper is to formulate frameworks for the drivers and barriers of integrated sustainable solid waste management (ISSWM) with reference to conditions prevailing in India.

A multi-phased approach was adopted in this paper to come up with the conceptual framework of the drivers and barriers of ISSWM. In the first phase, drivers and barriers of ISSWM were identified based on a systematic literature review process. In the second phase, 25 experts having 15 plus years of experience in the field of sustainable development and environmental management were consulted to get their opinion. Validation and understanding of the interrelationship among the selected drivers and barriers were done based on the insights from expert interviews. And in the final phase, structural self-interaction matrix and transitive links are defined based on the expert opinion to come up with the theoretical frameworks of drivers and barriers of ISSWM.

Findings reveal the importance to have a system view point approach by giving equal importance to social, environmental and economic pillars of sustainability along with the technology component to effectively and sustainably manage the solid waste disposal. Institutional effectiveness and the robust policy and frameworks are the two variables found to have the highest driving power. Poor social values and ethics, huge population and illiteracy are the three most critical barriers faced by developing nations in achieving the sustainability practices in the solid waste management. The proposed frameworks of drivers and barriers of ISSWM will definitely help policy makers to effectively manage the sustainable waste management practices for developing economies by focusing on the key variables listed out.

One of the limitations is in the use of very limited sample size in the study. Another limitation is that total interpretive structural modeling fails to come up with the relative weightings of drivers and barriers used in the study. These limitations can be overcome by extending the research by using a semi-structured questionnaire survey with higher sample size for the empirical validation of the model.

This research will help to clearly understand the framework of drivers and barriers of variables and their hierarchical level based on the driving power and dependence. Since such articles focusing on the conceptual frameworks of drivers and barriers of ISSWM are found to be very scant, this paper will equally help academicians and waste management professionals to understand the concepts deeply, by getting answers to the fundamental questions of “what,” “why” and “how.” Developed framework of drivers explicitly shows the need to attain financial stability through the commercialization of the waste management initiatives, which will help to reduce burden on various governmental institutions. Commercialization opportunities will also help to have more successful start-up ventures in solid waste management domain that can provide improved employment opportunities and hygiene environment in the developing nations like India.

Based on the authors’ best knowledge, there is hardly any article that explicitly explains the conceptual frameworks of the drivers and barriers of ISSWM by considering the conditions prevailing in developing countries like India. And thus, this can be considered as one of the unique research attempts to build a clear conceptual framework of ISSWM. The study contributes significantly to the existing literature body by clearly interpreting the interrelationships and the driving power and dependence of variables of ISSWM.

The purpose of this paper is to investigate the effects of surface topography, including surface roughness, circumferential waviness and radial taper, on hydrodynamic performance of liquid film seals considering cavitation.

A mathematical model of liquid film seals with surface topography was established based on the mass-conservative algorithm. Liquid film governing equation was discretized by the finite control volume method and solved by the Gauss–Seidel relaxation iterative algorithm, and the hydrodynamic performance parameters of liquid film seals were obtained considering surface roughness, circumferential waviness and radial taper separately.

The results indicate that the values of load-carrying capacity and frication torque are affected by the surface topography in varying degrees, but the effect is limited.

The results presented in the study are expected to aid in determining the optimum value of structural parameters for the optimum seal performance because of the realistic model which considers both surface topography and cavitation.

To unlock social media’s value, this study aims to integrate insights from several theoretical perspectives and the relevant literature, developing an extended social media analytics framework. It identifies the stages underlying the social media analytics process and tests the framework in three important and interconnected areas: social media (Twitter), new product adoption (iWatch and Google Glass) and social media analytic techniques (text mining and sentiment analysis).

Based upon a systematic review of different research approaches, theories and media types, this paper presents and tests an extended framework in three important and interconnected areas mentioned above.

This paper offers a theory-driven social media analytics framework. It validates the framework by providing concrete processes, examples, evidence and insights related to three chosen areas mentioned above, thereby helping managers create effective and efficient social media and new product development strategies.

This paper integrates insights from theories of the middle range (Merton, 1949), Campbell’s (1965) model of sociocultural evolution and Fan and Gordon’s (2014) social media analytics framework, developing its own extended social media analytics framework and validating it in three important and interconnected areas mentioned above. This paper demonstrates not only how the proposed framework can be applied to the context of new product development, but also how social media are transforming research approaches (qualitative, quantitative and mixed method) and the very nature of business itself (increased importance of digital business).

Machine learning is having a major impact on banking, law and other organisations. The speed with which this technology is developing to undertake tasks that are not only complex and technical but also time-consuming and that are subject to constantly changing parameters is astounding. The purpose of this paper is to explore the extent to which machine learning can be used as a solution to lighten the compliance and regulatory burden on charitable organisations in the UK; so that they can comply with their regulatory duties and develop a coherent and streamlined action plan in relation to technological investment.

The subject is approached through the analysis of data, literature and domestic and international regulation. The first part of the study summarises the extent of current regulatory obligations faced by charities, these are then, in the second part, set against the potential technological solutions provided by machine learning as of July 2021.

It is suggested that charities can use machine learning as a smart technological solution to ease the regulatory burden they face in a growing and impactful sector.

The work is original because it is the first to specifically explore how machine learning as a technological advance can assist charities in meeting the regulatory compliance challenge.