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Integrated project delivery (IPD) project that does not use multiparty agreement is identified as IPD-ish. The use of IPD-ish arrangement by incorporating integration practices in conventional contract can be viewed as the part of the adoption process of IPD. Moreover, inappropriate integration practices invite new forms of risks and the absence of multiparty agreement adds to the challenges of risk management in IPD-ish projects. This study discusses such challenges and proposes the use of joint risk management to address the potential pitfalls in IPD-ish arrangement.

A mixed research method was applied. First, the criticality of IPD-ish general and integration-specific risks was examined through a survey. Second, a real IPD-ish project was used to exemplify the use of joint risk management (JRM) to manage IPD-ish risks.

Two types of risks, namely integration risks (IRs) and general risks (GRs), are identified in IPD-ish projects. Two major findings for the IRs: (1) the most critical IRs are related to unbalanced incentivization and inefficient multidisciplinary teams; and (2) only team formation related pre-contract JRM strategies affect IRs. As for the GRs, the most critical ones are associated with design issues and can be effectively mitigated by post-contract JRM.

Using IPD-ish arrangement is an inevitable part of implementation of full IPD. This happens as many change-averse owners would like to test the integration principles using a conventional contract that they are familiar with. In fact, success in IPD-ish would pave the path for further adoption of IPD. This study offers insight into categorization of risks in IPD-ish projects. Appropriate use of post-contract and organization related pre-contract JRM would improve the chance of teasing out the values of IPD through IPD-ish arrangements. Care should be taken to introduce some contracting integration initiatives, such as risk/reward sharing incentive.

Despite the significant interest from researchers and practitioners, the literature on project value measurement from the perspective of the customer is non-existent. This study aims to address this gap by developing and validating a scale to measure project value through a customer lens called the customer perception of project value scale.

A list of items was initially generated based on 762 sample responses through a systematic review of the literature and with the participation of specialists. Exploratory and confirmatory factorial analyses and structural equation modelling were used to develop and validate the scale.

The authors formulated a four-dimension scale. The dimensions used to measure the second-order construct are customer centrality, process, delivery and cost-benefit. This was validated using a nomological structure.

The non-consensual nature of what is value in projects restricts the results of this study to the context of a specific group of stakeholders only, that is, the consumers of the projects. The authors also see limitations in the absence of competing scales, which do not allow the comparison of the instrument with alternative measures.

This study allows project managers and other professionals to measure a project’s perceived value from the customer’s point of view and manage the improvement of this perception.

To the best of the authors’ knowledge, this is the first study to propose a scale to measure project value, which advances the literature on project management and value and contributes to academic knowledge and practice by measuring project value from the customer standpoint.

Social mediametrics is a subfield of measurement in which the emphasis is placed on social media data. This paper analyzes the trends and patterns of paper comprehensively mentions on Twitter, with a particular focus on Twitter's mention behaviors. It uncovers the dissemination patterns and impact of academic literature on social media. The research has significant theoretical and practical implications.

This paper explores the fundamental attributes of Twitter mentions by means of analyzing 9,476 pieces of scholarly literature (5,097 from Nature and 4,379 from Science), 1,474,898 tweets and 451,567 user information collected from Altmetric.com database and Twitter API. The study uncovers assorted Twitter mention characteristics, mention behavior patterns and data accumulation patterns.

The findings illustrate that the top academic journals on Twitter have a wider range of coverage and display similar distribution patterns to other academic communication platforms. A large number of mentioners remain unidentified, and the distribution of follower counts among the mention users exhibits a significant Pareto effect, indicating a small group of highly influential users who generate numerous mentions. Furthermore, the proportion of sharing and exchange mentions positively correlates with the number of user followers, while the incidence of supportive mentions has a negative correlation. In terms of country-specific mention behavior, Thai scholars tend to utilize supportive mentions more frequently, whereas Korean scholars prefer sharing mentions over communicating mentions. The cumulative pattern of Twitter mentions suggests that these occur before official publication, with a half-life of 6.02 days and a considerable reduction in the number of mentions is observed on the seventh day after publication.

Conducting a multi-dimensional and systematic analysis of Twitter mentions of scholarly articles can aid in comprehending and utilizing social media communication patterns. This analysis can uncover literature's distribution patterns, dissemination effects and social significance in social media.

This study aims to identify current practices of environmentally friendly sustainable preventive conservation in Asian libraries.

This study uses a predominantly quantitative survey for data collection with a combination of open and closed questions. From 237 survey links sent, 22 responses were received from libraries in 16 Asian countries.

This study uncovers current practices in four areas of environmentally sustainable preventive conservation in Asia: collection preservation, environmental monitoring and management, integrated pest management, and collections care and handling. Challenges to implementing sustainable preventive conservation were also revealed.

The response rate was relatively low, and responses were not received from all countries in Asia. As such, while the study provides a starting point for further research, it cannot be assumed that the findings are representative of Asian libraries in general. In addition, some aspects of preventive conservation (for example, disaster preparedness, exhibition) and library preservation management were excluded from the study, and research on these topics, together with environmental and economic factors, is encouraged, along with qualitative research methods.

This study highlights the environmentally friendly sustainable initiatives that libraries employ in their preservation programmes and increases awareness of challenges to implementing those initiatives.

To date there has been little research on environmentally sustainable preventive conservation practices within Asia's libraries. This study therefore makes a valuable contribution to understanding current practices of preventive conservation in Asia.

The conventional project delivery (CPD) approach has been reported in the literature as the most widely used project delivery method in the construction industry globally compared to other delivery methods. However, researchers and practitioners have argued that the approach, specifically during the production of design documentation under the CPD, lacks certain capabilities that ensure quality and enhance project delivery. Therefore, this study aims to use the Ghanaian construction industry to identify the capabilities required of the CPD in practice, particularly during the production of design documentation.

The study design follows a pragmatist philosophy and uses mixed methods based on a deductive approach. Data collection involved a questionnaire survey, followed by semi-structured interviews. Quantitative data analysis used descriptive and inferential statistics, whereas qualitative data analysis used content analysis with the assistance of IBM SPSS and QSR Nvivo 12 Pro.

Findings indicate that there should be incentives for producing good design documentation quality; mandatory coordination of design documentation; improving collaboration among designers; and allowing contractors to make input during the design stage.

The results indicate the need for the identified capabilities to be introduced in the CPD approach to improve design documentation quality.

This study offers a significant insight into the specific capabilities that are required of the CPD approach in practice particularly, in the production of design documentation

This study proposes a predictive neural network model reference decoupling control method for the coupling problem between the leg joints of hydraulic quadruped robots, and verifies its decoupling effect..

The machine–hydraulic cross-linking coupling is studied as the coupling behavior of the hydraulically driven quadruped robot, and the mechanical dynamics coupling force of the robot system is controlled as the disturbance force of the hydraulic system through the Jacobian matrix transformation. According to the principle of multivariable decoupling, a prediction-based neural network model reference decoupling control method is proposed; each module of the control algorithm is designed one by one, and the stability of the system is analyzed by the Lyapunov stability theorem.

The simulation and experimental research on the robot joint decoupling control method is carried out, and the prediction-based neural network model reference decoupling control method is compared with the decoupling control method without any decoupling control method. The results show that taking the coupling effect experiment between the hip joint and knee joint as an example, after using the predictive neural network model reference decoupling control method, the phase lag of the hip joint response line was reduced from 20.3° to 14.8°, the amplitude attenuation was reduced from 1.82% to 0.21%, the maximum error of the knee joint coupling line was reduced from 0.67 mm to 0.16 mm and the coupling effect between the hip joint and knee joint was reduced from 1.9% to 0.48%, achieving good decoupling.

The prediction-based neural network model reference decoupling control method proposed in this paper can use the neural network model to predict the next output of the system according to the input and output. Finally, the weights of the neural network are corrected online according to the predicted output and the given reference output, so that the optimization index of the neural network decoupling controller is extremely small, and the purpose of decoupling control is achieved.

This paper aims to identify the conditions under which encroachment is a viable strategy for a manufacturer to gain competitive advantage and achieve higher profitability in the presence of the store-brand.

This paper proposes game-theoretic models in a two-echelon supply chain consisting of a manufacturer (him) and a retailer (her), in which he distributes his national brand through the retailer, and endogenously determines whether to establish a new direct sales channel to sell the national brand when the retailer introduces her store-brand.

Analytical results show that the bar for the manufacturer to encroach the end market in the presence of the store-brand is always higher than that for him to encroach in the absence of the store-brand. Although incurring channel competition, encroaching with the national brand in the presence of the retailer's store-brand can lead to either a win-lose or win-win result for the manufacturer and the retailer. Numerical studies claim that, higher brand substitution can push down the retailer's enthusiasm to introduce her new brand. Counterintuitively, when the retailer introduces her store-brand, higher brand substitution does not necessarily push up the manufacturer's enthusiasm to respond with national-brand encroachment. When consumer preferences for the two brands are heterogeneous, a higher consumer preference for the retailer's store-brand results in the retailer's higher enthusiasm to introduce her store-brand and the manufacturer's lower enthusiasm to encroach with his national brand.

This study can help researchers to better understand the retailer's store-brand introduction, manufacturer encroachment and their interaction theoretically, and further provide decision support for enterprises to choose brand and channel strategies in practice.

Microribbon with meander type based on giant magnetoimpedance (GMI) effect has become a research hot spot due to their higher sensitivity and spatial resolution. The purpose of this paper is to further optimize the line spacing to improve the performance of meanders for sensor application.

The model of GMI effect of microribbon with meander type is established. The effect of line spacing (Ls) on GMI behavior in meanders is analyzed systematically.

Comparison of theory and experiment indicates that decreasing the line spacing increases the negative mutual inductance and a consequent increase in the GMI effect. The maximum value of the GMI ratio increases from 69% to 91.8% (simulation results) and 16.9% to 51.4% (experimental results) when the line spacing is reduced from 400 to 50 µm. The contribution of line spacing versus line width to the GMI ratio of microribbon with meander type was contrasted. This behavior of the GMI ratio is dominated by the overall negative contribution of the mutual inductance.

This paper explores the effect of line spacing on the GMI ratio of meander type by comparing the simulation results with the experimental results. The superior line spacing is found in the identical sensing area. The findings will contribute to the design of high-performance micropatterned ribbon with meander-type GMI sensors and the establishment of a ribbon-based magnetic-sensitive biosensing system.

Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials.

A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials.

The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach.

The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.

This paper aims to propose a bed and breakfast (B&B) recommendation method that takes into account review timeliness and user preferences to help consumers choose the most satisfactory B&B.

This paper proposes a B&B ranking method based on improved intuitionistic fuzzy sets. First, text mining and cluster analysis are combined to identify the concerns of consumers and construct an attribute set. Second, an attribute-level-based text sentiment analysis is established. The authors propose an improved intuitionistic fuzzy set, which is more in line with the actual situation of sentiment analysis of online reviews. Next, subjective-objective combinatorial assignments are applied, considering the consumers’ preferences. Finally, the vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) algorithm, based on the improved score function, is advised to evaluate B&Bs.

A case study is presented to illustrate the use of the proposed method. Comparative analysis with other multi-attribute decision-making (MADM) methods proves the effectiveness and superiority of the VIKOR algorithm based on the improved intuitionistic fuzzy sets proposed in this paper.

Proposing a B&B recommendation method that takes into account review timeliness and user customization is the innovation of this paper. In this approach, the authors propose improved intuitionistic fuzzy sets. Compared with the traditional intuitionistic fuzzy set, the improved intuitionistic fuzzy set increases the abstention membership, which is more in line with the actual situation of attribute-level sentiment analysis of online reviews.