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Megaproject performance measurement (MPM) has received great attention in the project management community, but it primarily focused on the design of performance measures or frameworks. Yet, whether MPM utilization can improve megaproject performance and how project actors use MPM to improve megaproject performance is less well understood. This study aims to investigate whether and how the use of MPM can contribute to better megaproject performance.

Through the lens of the lever of control, this study conceptualizes MPM utilization as diagnostic use and interactive use. A holistic research model and related hypotheses integrating MPM use, project complexity and megaproject performance were established. The model was validated using a partial square-structural equation modeling method.

Based on 214-megaproject data collected through a questionnaire survey in China, the results show positive effects of diagnostic use and interactive use on megaproject performance. Both, however, have substitutional interaction effects. The moderating results suggest that the higher project complexity weakens the positive effects of MPM utilization on megaproject performance.

This study advances megaprojects performance measurement and management literature by validating the value of MPM utilization on performance. It also presents practical implications for project managers to improve performance by appropriate MPM utilization.

The aim of this study is to first investigate the surface integrity of cylindrical rollers under grinding process and then design a reasonable superfinishing process that improve the anti-fatigue performance of cylindrical rollers by optimization of the surface integrity.

First, the white and dark layers produced by the grinding process is analyzed by microscope. Then, the influence of oilstone pressure on the stock removal, surface precision and crowned profile are explored. Finally, an optimal superfinishing process and a novel turnaround device are designed to improve surface integrity.

The experimental results show that as the oilstone pressure increases, the stock removal first increases and then remains stable. This hints that the stock removal of a single-time superfinishing process has an upper limit. In the current conditions, the maximum stock removal is 6 µm. Double-time superfinishing process and the turnover device can effectively eliminate the white and dark layers and improve the symmetric of roller profile. In addition, the surface precision is also improved.

The surface integrity of bearing rollers is very important to the application of industry field. The findings and the methods in the study can be helpful to improve the surface integrity of the bearing rollers.

To explore substitutes for traditional Sn-Pb solder, Sn-20In-2.8Ag was considered because of its appropriate melting temperature, good reliability and high ductility at less than 100°C. However, the mechanical properties of Sn-20In-2.8Ag were not satisfactory. The reason for the poor mechanical properties of the Sn-20In-2.8Ag/Cu joint was revealed, and a way to solve the problem was found.

The microstructure evolution, characteristics of melting and solidification and joining performance with Cu were investigated using scanning electron microscopy (SEM), electron probe microanalysis, differential scanning calorimetry (DSC) and mechanical testing.

SEM results showed that the microstructure of Sn-20In-2.8Ag was composed of coarse dendritic Ag₂In and γ phases, with Ag₂In distributed at the grain boundaries. DSC measurements revealed that small amount of low temperature eutectic reaction, L → Ag₂In + β + γ, occurred at 112.9°C. This reaction was caused by the segregation of indium, which is a process that has a strong driving force. In the lap-shear testing, a crack propagated along the grain boundary of the solder, and failure showed an intergranular fracture. This failure was connected with the three-phase eutectic and coarse Ag₂In. Thus, to improve the mechanical properties, segregation of indium should be reduced and coarsening of Ag₂In should be prevented.

The reason for the unsatisfactory mechanical properties of Sn-20In-2.8Ag was revealed via microstructural observations and solidification analysis, and the way to solve this problem was found.

A linear interpolation (Lerp) approach, utilizing a common stochastic trend, is explored to impute missing values in nonstationary panel data models. The Lerp algorithm is considerably faster and easier to use than the leading methods recommended in the statistics literature. It shows through a set of simulations that the Lerp works well, whereas other existing methods fail to perform properly, when the panel data contain a high degree of missingness and/or a strong correlation across cross-sectional units. As an illustration, the method is applied to study the cost-of-living-index dataset with missing values. The test on the imputed panel data provides the supporting evidence for the U.S. economy convergence that depends on the state physical spatial proximities and the state industrial development similarities.

As a kind of NP-hard combinatorial optimization problem, pipe routing design (PRD) is applied widely in modern industries. In the offshore oil and gas industry, a semi-submersible production platform is an important equipment for oil exploitation and production. PRD is one of the most key parts of the design of semi-submersible platform. This study aims to present an improved ant colony algorithm (IACO) to address PRD for the oil and gas treatment system when designing a semi-submersible production platform.

First, to simplify PRD problem, a novel mathematical model is built according to real constraints and rules. Then, IACO, which combines modified heuristic function, mutation mechanism and dynamical parameter mechanism, is introduced.

Based on a set of specific instances, experiments are carried out, and the experimental results show that the performance of IACO is better than that of two variants of ACO, especially in terms of the convergence speed and swarm diversity. Finally, IACO is used to solve PRD for the oil and gas treatment system of semi-submersible production platform. The simulation results, which include nine pipe paths, demonstrate the practicality and high-efficiency of IACO.

The main contribution of this study is the development of method for solving PRD of a semi-submersible production platform based on the novel mathematical model and the proposed IACO.

The purpose of this paper is to describe the development of a novel mobile monitoring and control (MC) framework with active-push and plug-and-play capabilities. This proposed framework is particularly designed to addresses the shortcomings of the traditional factory MC systems in sharing information over the internet, protecting the system security, delivering warning messages, and deploying monitoring points.

By leveraging web service technology, mobile devices, and wireless communication, this paper describes the methodology and approach for designing a MC server, a wireless monitoring module (WMM), an intelligent v-Machine, two active-push mechanisms, a pocket PC application, and a smart phone application.

The designed WMM enables the monitoring points to be deployed in a mobile manner. The proposed mobile MC framework (MMCF) can timely detect abnormalities of appliances and equipment and turn off appliances in dangerous situations through WMM. It can also instantly deliver various warning contents to the mobile devices carried by the responsible persons. The v-Machine is built based on virtual metrology (VM) technology and can predict production precision of machined workpieces.

With the successful design and testing of the novel MMCF, this framework can obviously be used for many more applications and developments.

The authors' implement a factory MC system based on the proposed framework and conduct various integration tests on two electric appliances and a practical CNC machine tool in a factory. Testing results shows that the factory MC system works smoothly according the design goals and can overcome the shortcomings of traditional factory MC systems. The MC system also presents good performances, instantly delivering warning contents with a size ranging from 1K bytes to 10M bytes to the users within few seconds.

The proposed MMCF exploits various automation technologies to detect equipment's abnormalities, reduce the rate of product defects caused by human errors, reinforce security, prevent accidents, and ensure the safety of operations.

The proposed MMCF can effectively promote existing factory MC systems to achieve the merits of mobile MC, which is a unique contribution of this work, compared to previous studies. The results of this study can be applied to a variety of industrial automation applications, including factory automation and assembly automation.

The purpose of this paper is to examine the deficit–inflation nexus in the two fastest growing economies, India and China, which happen to be crucial affiliates of the global growth generator countries apart from their association in Brazil, Russia, India, China, and South Africa.

The paper uses the prism of the vector auto regression framework, for the period 1985–1986 to 2016–2017 for both India and China. For this purpose, gross fiscal deficit, money supply, exchange rate, crude oil prices and output gap are examined as the key elements in the determination of inflation. The econometric framework used chiefly comprises of cointegration analysis, vector error correction model, Granger causality and impulse response functions.

The findings of this paper support the hypothesis that fiscal deficits are inflationary only in the Indian context and that the Ricardian equivalence cannot be negated for China at least in the short run. The results presented in the paper are a little agnostic about whether New Keynesian Phillips Curve (NKPC) explains the inflation dynamics in India, given that both inflation inertia and output gap are not robust. However, for the Chinese economy, NKPC along with structural theory is instrumental in describing trends pertaining to inflation during the period of the study.

The paper warrants broader policy framework to aim at addressing structural bottlenecks to ensure non-inflationary growth keeping in mind the structural views on inflation. Furthermore, the paper fosters greater synthesis between monetary and fiscal policies, especially considering the global economic disruptions the world economy is subject to.

Considering there are only a limited number of studies on fiscal deficit of China, the present paper is of paramount significance in terms of growing concern over the sustainability of the growth process in China. Additionally, the paper is first-of-its-kind attempt to account the effectiveness of a healthy monetary–fiscal interface in achieving macroeconomic stability in India and China.

The purposes of this paper are (1) to explore the overall development of AI technologies and applications that have been demonstrated to be fundamentally important in the healthcare industry, and their related commercialized products and (2) to identify technologies with promise as the basis of useful applications and profitable products in the AI-healthcare domain.

This study adopts a technology-driven technology roadmap approach, combined with natural language processing (NLP)-based patents analysis, to identify promising and potentially profitable existing AI technologies and products in the domain of AI healthcare.

Robotics technology exhibits huge potential in surgical and diagnostics applications. Intuitive Surgical Inc., manufacturer of the Da Vinci robotic system and Ion robotic lung-biopsy system, dominates the robotics-assisted surgical and diagnostic fields. Diagnostics and medical imaging are particularly active fields for the application of AI, not only for analysis of CT and MRI scans, but also for image archiving and communications.

This study is a pioneering attempt to clarify the interrelationships of particular promising technologies for application and related products in the AI-healthcare domain. Its findings provide critical information about the patent activities of key incumbent actors, and thus offer important insights into recent and current technological and product developments in the emergent AI-healthcare sector.

Teachers, students, librarians, scholars and domain experts often spend a lot of time and effort to select good and suitable textbooks. This study aims to propose and construct a computer-aided bibliometric system to rate textbooks. Through the software system designed here, the quality of every textbook can be easily and quickly known. This system will benefit both scholars and librarians.

Four methods were used to evaluate textbooks in this study, including: questionnaire recommendation analysis, dissertation citation analysis, library circulation analysis and bibliography analysis. The system architecture includes three subsystems: the textbook indexing and searching subsystem, the statistics added-value analysis subsystem and the citation report inquiry subsystem. An example demonstrates the usability and validity of the proposed method and system. The example uses surveying textbooks. The following percentages were used in the correlation calculation: textbook citation percentage (TCP), textbook library circulation percentage (TLP) and textbook recommend percentage (TRP).

There are three textbook assessment methods applied in this study, including: dissertation citation, library circulation and questionnaire recommendation. Dissertation citations for textbooks have a high correlation value with library circulation. The frequency correlation calculation was 0.7, while the TCP, TLP and TRP correlation calculation was 0.84. Therefore, the dissertation citation method can be accepted to evaluate textbooks effectively.

To the best of the authors’ knowledge, this is the first work related to evaluating surveying textbooks using a computer-aided bibliometrics system that can deal with large amounts of data and generate results quickly. This can be applied to other fields as well.

The formation of alliances between organisations is increasingly common, allowing firms to discover and ensure competitive advantages. This research paper aims to make a critical analysis of studies to understand the role of communication between partners in the process of strategic alliances.

A systematic literature review was carried out, using the Web of Science database to obtain data, associating the terms “communication” and “strategic alliances”, which resulted in 240 scientific articles (published between 1993 and March 2021). After data treatment using VOSviewer software and reading of the contents, the final sample consisted of 179 articles on the subject in question.

The conceptual limits, exploratory descriptive analysis of the data and content analysis of research methods are presented, with five clusters being identified. The results show growing academic interest in studying communication associated with strategic alliances, and authors’ main interest lies in understanding the critical success factors and the relation between communication and knowledge.

This study corroborates understanding of the future of alliances, assuming that learning is the main objective; trust is the factor determining success or failure; technology is the aggregating tool; culture affects the relation; and communication is not an end but a means to construct consolidated, long-lasting and high-performing strategic alliances.

This study is innovative in strategic alliances area. The research confirms that the main factor in forming alliances, in both emerging and international markets, is the learning intention. This fact reinforces the relevance of the learning made possible by this transfer of know-how through communication. In addition, this study gives critical understanding of how the process of communication between partners in an alliance must be distinct; i.e. it must be flexible enough to adjust to the stage in the alliance’s life cycle.