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Conflicts frequently occur in construction projects. Matching appropriate contractual and relational governance with conflict features to promote cooperation and thus minimize the negative influences of conflict is an issue that deserves attention. Our study classifies conflict types into task, process and relationship conflict and defines their combinations as conflict profiles. By conceptualizing contractual governance as the complexity of contract provisions and the strictness of contract enforcement and relational governance as trust, our study aims to explore the configurational impacts of conflict profiles and these governance mechanisms on parties’ cooperative behaviors.

A questionnaire survey was conducted, and 238 valid questionnaires were received. Fuzzy set qualitative comparative analysis was performed.

Four configurations produce cooperative behaviors. The combined use of detailed contracts, rigid enforcement and high trust enhances cooperation and such a governance arrangement is not subject to any conflict profile. A relatively low level of conflict requires detailed contracts and high levels of trust. For the conflict profile characterized by high task and process conflict and low relationship conflict, parties can select contractual governance-dominant or relational governance-dominant approaches.

Theoretically, our study reveals the matching relationships between conflict profiles and governance mechanisms, enriching the research on conflict profiles in construction projects and the interrelation between contractual and relational governance. Practically, the findings provide project managers guidance for conflict management and selecting governance mechanisms.

This paper investigates the paths through which innovation community affects content providers' new service development (NSD) performance in technology-based service ecosystem and contingency factors exist in the paths.

The research model is built based on service-dominant (S-D) logic, exploring the relationship among innovation community, content providers' knowledge acquisition and content providers' NSD performance as well as the moderating role of content providers' technology readiness and content providers' complexity. Using survey data collected from 386 content providers of selected open network platforms in China, this study finds broad support for the proposed research model.

The findings of this paper reveal that content providers' tacit knowledge acquisition from users plays a mediating role between the innovation community and new service ratings. Content providers' technology readiness plays a positive moderating role in the relationship between innovation community and their explicit or tacit knowledge acquisition. Content providers' task complexity negatively moderates the effects of their explicit knowledge acquisition from users on new service volumes or ratings, but positively moderates the effects of tacit knowledge acquisition from users on new service volumes or ratings.

Though extant literature highlights the importance of knowledge acquisition in NSD performance, few studies explore the antecedents of content providers' knowledge acquisition from users and the paths through which these antecedents affect content providers' NSD performance. Moreover, boundary conditions exist in the process of improving NSD performance are generally ignored in previous literature. With the lens of S-D logic, this paper explicates how content providers of different technology readiness and different task complexity enhance their new service volumes and ratings through acquiring explicit and tacit knowledge from users in innovation community. Adopting S-D logic from marketing area to NSD area, this paper not only enriches the theoretical accumulations of antecedents and boundary conditions of content providers' NSD performance but also offers insights for content providers and users on how to synergistically advance NSD activities and co-create value in the technology-based service ecosystem.

Existing calibration methods mainly focus on the camera laser-plane calibration of a single laser-line length, which is not convenient and cannot guarantee the consistency of the results when several three-dimensional (3D) scanners are involved. Thus, this study aims to provide a unified step for different laser-line length calibration requirements for laser profile measurement (LPM) systems.

3D LPM is the process of converting physical objects into 3D digital models, wherein camera laser-plane calibration is critical for ensuring system precision. However, conventional calibration methods for 3D LPM typically use a calibration target to calibrate the system for a single laser-line length, which needs multiple calibration patterns and makes the procedure complicated. In this paper, a unified calibration method was proposed to automatically calibrate the camera laser-plane parameters for the LPM systems with different laser-line lengths. The authors designed an elaborate planar calibration target with different-sized rings that mounted on a motorized linear platform to calculate the laser-plane parameters of the LPM systems. Then, the camera coordinates of the control points are obtained using the intersection line between the laser line and the planar target. With a new proposed error correction model, the errors caused by hardware assembly can be corrected. To validate the proposed method, three LPM devices with different laser-line lengths are used to verify the proposed system. Experimental results show that the proposed method can calibrate the LPM systems with different laser-line lengths conveniently with standard steps.

The repeatability and accuracy of the proposed calibration prototypes were evaluated with high-precision workpieces. The experiments have shown that the proposed method is highly adaptive and can automatically calibrate the LPM system with different laser-line lengths with high accuracy.

In the repeatability experiments, there were errors in the measured heights of the test workpieces, and this is because the laser emitter had the best working distance and laser-line length.

By using this proposed method and device, the calibration of the 3D scanning laser device can be done in an automatic way.

The calibration efficiency of a laser camera device is increased.

The authors proposed a unified calibration method for LPM systems with different laser-line lengths that consist of a motorized linear joint and a calibration target with elaborately designed ring patterns; the authors realized the automatic parameter calibration.

Urban spatial form influences the social, economic, and ecological development modes of the city. The spatial form during the urbanization of Hanjiang River Basin in Southern Shaanxi needs to be studied. In this study, research methodologies on urban spatial form in China and abroad were summarized. The concept of ecology background was applied, and the research framework for urban spatial form, which integrated the background, framework, core, axis, cluster, and skin, was established. Valley cities in the Hanjiang River Basin in Southern Shaanxi were classified into wide valley, narrow valley, and canyon cities. The spatial form characteristics of these three types of valley cities were discussed. A case study based on a typical city-Yang County-was conducted to discuss the characteristics of the aforementioned six elements of urban spatial form. Finally, spatial form characteristics were summarized. These characteristics provide a basis for the study of the small valley urban spatial form in the Hanjiang River Basin in Southern Shaanxi.

Recent studies have documented the significant influence of investment bank relationships on the forecast accuracy of affiliated analysts. However, the literature primarily focuses on investment bank-firm relationships, such as whether the investment bank has underwriter or lending relationships with firms. Little attention has been paid to the impact of investment bank-state relationships. To fill this gap in the literature, this paper investigates whether investment bank-state relationships create an information advantage for affiliated analysts.

We empirically test the information advantage of state-affiliated analysts using a large sample of analyst forecasts from China spanning the period 2008 to 2020. Specifically, we investigate whether state-affiliated analysts issue more accurate and timely forecasts around macro events. To address endogeneity concerns, we examine instances where analysts move between state-affiliated and non-affiliated banks, as well as changes in the controlling structure of investment banks.

We find that state-affiliated analysts demonstrate greater accuracy in forecasts driven by macro events, indicating their information advantage. This effect is more pronounced under conditions of heightened economic policy uncertainty and closer ties between investment banks and the state. After transitioning to a non-state-affiliated investment bank, analysts no longer maintain the ability to make superior macro-event-driven forecasts. Conversely, when the investment bank's affiliation changes from non-state to state, financial analysts gain an information advantage following the establishment of new state affiliation. Additionally, state-affiliated analysts tend to issue more assertive forecasts in response to macro events, which are subsequently echoed by their peers. Furthermore, this information advantage is recognized by investors, enhancing stock price informativeness.

Firstly, we contribute to the literature on the economic implications of state ownership in financial intermediaries. Secondly, we enrich the existing literature on financial analysts by acknowledging the pivotal role of investment bank relationships in shaping analysts' behaviors. Lastly, unlike existing literature that treats forecasts driven by macroeconomic events and those influenced by firm-specific events as a homogeneous category, this study contributes to the literature by innovatively categorizing analyst forecasts into two distinct types.

Power amplifiers (PAs) play an important role in wireless communications because they dominate system performance. High-linearity broadband PAs are of great value for potential use in multi-band system implementation. The purpose of this paper is to present a cascode power amplifier architecture to achieve high power and high efficiency requirements for 4.2∼5.4 GHz applications.

A common emitter (CE) configuration with a stacked common base configuration of heterojunction bipolar transistor (HBT) is used to achieve high power. T-type matching network is used as input matching network. To increase the bandwidth, the output matching networks are implemented using the two L-networks.

By using the proposed method, the stacked PA demonstrates a maximum saturated output power of 26.2 dBm, a compact chip size of 1.17 × 0.59 mm² and a maximum power-added efficiency of 46.3 per cent. The PA shows a wideband small signal gain with less than 3 dB variation over working frequency. The saturated output power of the proposed PA is higher than 25 dBm between 4.2 and 5.4 GHz.

The technology adopted for the design of the 4.2-to-5.4 GHz stacked PA is the 2-µm gallium arsenide HBT process. Based on the proposed method, a better power performance of 3 dB improvement can be achieved as compared with the conventional CE or common-source amplifier because of high output stacking impedance.

Algorithmic monitoring has been widely applied to the practice of platform economy as a management means. Despite its benefits, negative effects of algorithmic monitoring are gradually emerging.

Based on moral disengagement theory, this research aims to investigate how algorithmic monitoring might affect gig workers’ attitudes and behaviors. Specifically, we explored the effect of algorithmic monitoring on gig workers’ unethical behavior. A three-wave survey was conducted online, and the sample consisted of 318 responses from Chinese gig workers.

The results revealed that algorithmic monitoring positively affected unethical behavior through displacement of responsibility, and the individualistic orientation of gig workers moderated this relationship. However, the relationship between moral justification and algorithmic monitoring was not significant.

This research contributes to the algorithmic monitoring literature and examines its impact on gig workers’ unethical behavior. By revealing the underlying mechanism and boundary conditions, this research furthers our understanding of the negative influences of algorithmic monitoring and provides practical implications.

The influence of road surface temperature (RST) on vehicles is becoming more and more obvious. Accurate predication of RST is distinctly meaningful. At present, however, the prediction accuracy of RST is not satisfied with physical methods or statistical learning methods. To find an effective prediction method, this paper selects five representative algorithms to predict the road surface temperature separately.

Multiple linear regressions, least absolute shrinkage and selection operator, random forest and gradient boosting regression tree (GBRT) and neural network are chosen to be representative predictors.

The experimental results show that for temperature data set of this experiment, the prediction effect of GBRT in the ensemble algorithm is the best compared with the other four algorithms.

This paper compares different kinds of machine learning algorithms, observes the road surface temperature data from different angles, and finds the most suitable prediction method.

This paper aims to find out how business aligns with robotic process automation (RPA) and whether the alignment has the same factors as for IT–business alignment.

Condition configurations for positive and negative impact for business alignment with RPA.

The positive and negative configurations that possibly impact business alignment with RPA.

There are some human instincts during conditions dichotomization and limited number of cases.

The findings can be used to guide practice application in real industry.

This paper adopted crisp-set qualitative comparative analysis to find condition configurations for alignment of business and RPA for more generalization.

Scholarly research on food waste is growing, but it tends to focus on households in general. The purpose of this paper is to explore the attitudes of green consumers towards food waste, reasons for wasting edible food and acceptance of policy actions that could help address the food waste challenge.

Based on a quantitative survey of 346 respondents, frequency distributions, cross tabulations and non-parametric tests were performed.

This study finds that there is inconsistency between attitudes and behaviours. Green consumers, including those who value organic food and vegetarianism, waste quite a lot of edible food. Food is thrown away mainly due to spoilage, short shelf life, being forgotten in the fridge and eating outside the home. Hence, consumers, even those with the best of intentions, face behavioural constraints when it comes to reducing food waste. A surprising finding is that some consumers lack awareness of the environmental burden posed by food waste. Several policy measures to reduce food waste are acceptable to the respondents

Reliance on self-reported data for food waste.

The research identifies actions that local governments could undertake to reduce consumer-related food waste. An environmental awareness campaign targeting green consumers could correct information deficits.

The focus on the green segment has practical implications for reducing the economic and environmental burden of food waste