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With the continuous improvement of public–private partnership (PPP) projects, the participants' value creation goals are not only limited to achieving the basic performance objectives but also to realising value added. However, the effect of traditional contract management on realising the value creation objectives of PPP projects is limited. According to the view of multifunctional contract, joint-contract functions that integrate contract control and flexibility are likely to be effective in enhancing the value creation of PPP projects. This study aims to explore the effects of joint-contract functions on PPP project value creation and relevant influencing mechanism by investigating the mediating effect of in-role behaviour and extra-role behaviour.

After collecting 258 valid questionnaires from PPP professionals in China, this study used structural equation modelling to validate the hypotheses.

Contract control and flexibility can improve PPP project value creation. Specifically, contract control improves the achievement of the basic contract objectives of PPP projects, whereas contract flexibility enhances the achievement of the value-added of PPP projects. Moreover, only in-role behaviour mediates the effect of contract control on value creation. In addition, the mediating effect of extra-role behaviour on the impact of contract flexibility on value creation is stronger than that of in-role behaviour. The mediating effect of in- and extra-role behaviour is mainly reflected in the realisation of basic and value-added performance, respectively.

The findings of this study can help realise value creation in three ways. Firstly, new perspectives for PPP project value creation should be proposed by combining the improvement of contract objectives and the realisation of the participants' implicit demands. Secondly, the effects of different contract functions on value creation should be analysed instead of a single dimension of contractual governance. Thirdly, the mediating effects of different types of cooperation behaviour that may influence the relationship between contractual governance and value creation should be evaluated.

This study verifies the impacts of different contract functions on PPP project value creation. In addition, cooperative behaviour is embedded as a mediating variable, and the mediated transmission path from contract function to cooperative behaviour and further to PPP project value creation is systematically analysed.

Online shopping has recently been evolving more toward the subject area of collaborative online shopping (COS), and customer satisfaction is one of the key determinants for the success of COS. In this study, we investigate the effect of product type and gender and their interaction with customer satisfaction through user involvement in a collaborative online shopping context.

We developed a lab experiment with a mixed two-by-two factorial design to test the proposed research model. We chose gender (male versus female) as the between-subjects factor and product type (utilitarian product versus hedonic product) as the within-subjects factor.

The obtained results indicate that collaborative shopping may require group members to be more involved for a hedonic product than a utilitarian product. When collaboratively shopping for utilitarian products, male groups tend to show a higher level of involvement than female groups. In contrast, female groups show a higher level of involvement than male groups when collaboratively shopping for hedonic products. Furthermore, our results indicate that greater involvement in COS may lead to higher satisfaction.

Websites that sell hedonic products should first adopt the design elements that support COS. Meanwhile, online sellers should be aware that the gender gap still exists as online shopping evolves toward social online shopping. In addition, COS websites should provide more design elements (e.g. co-browsing, avatar embodiment, video chat and voting tools) to stimulate user involvement.

In this paper, we employ the theory of consumption values, which decomposes COS value into the utilitarian and hedonic dimensions, as a theoretical foundation to investigate the effect of product type and gender together as well as their interactions in the COS context. The obtained findings may provide various insights and empirical evidence to improve the understanding of how to target male and female customers across different product types in the COS context.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

The present study reviews the literature on the history and evolution of investment strategies in the stock market for the period from 1900 to 2022. Conflicts and relationships arising from such diverse seminal studies have been identified to address the research gaps.

The studies for this review were identified and screened from electronic databases to compile a comprehensive list of 200 relevant studies for inclusion in this review and summarized for the cognizance of researchers.

The study finds a coherence to complex theoretical documentation of more than a century of evolution on investment strategy in stock markets, capturing the characteristics of time with a chronological study of events.

There were complications in locating unpublished studies leading to biases like publication bias, the reluctance of editors to publish studies, which do not reveal statistically significant differences, and English language bias.

Practitioners can refine investment strategies by incorporating behavioral finance insights and recognizing the influence of psychological biases. Strategies span value, growth, contrarian, or momentum indicators. Mitigating overconfidence bias supports effective risk management. Social media sentiment analysis facilitates real-time decision-making. Adapting to evolving market liquidity curbs volatility risks. Identifying biases guides investor education initiatives.

This paper is an original attempt to pictorially depict the seminal works in stock market investment strategies of more than a hundred years.

The paper examines the effect of language negativity of US financial analysts’ ancestral origins on their earnings forecast behavior.

The paper first developed a dictionary of the most emotionally negative words in 25 languages, based on the study by Dodds et al. (2015). The authors constructed firm-year analyst-level earnings forecast data and applied multivariate regression model along with a series of robustness tests to examine the research question.

The empirical results indicate that financial analysts with their ancestral countries characterized by a high level of language negativity tend to issue less optimistic earnings forecasts than other analysts. Additional evidence suggests that the effect of language negativity on analysts’ forecast is strengthened (1) during periods of financial crisis, (2) for firms with losses and a high level of earnings volatility and (3) for younger analysts and analysts working for small brokerage firms. Finally, we find evidence that higher levels of language negativity increase analysts’ forecast accuracy.

Collectively, the findings of this study support the conjecture that the level of negativity across languages can have a significant impact on capital market participants’ behavior. Thus, the study sheds light on how culturally inherited emotion can affect analysts’ earnings forecast properties.

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.

In order to extend the application of the original octagonal Goodman–Smith fatigue limit diagram, which is commonly used for the evaluation of structure fatigue stress in engineering, a modification of it is proposed for the structure made of S355 steel (commonly used in high-speed electric multiple units (EMUs) bogie frame).

The modification is made based on Deutscher Verband für Schweißen und verwandte Verfahren e. V. (DVS) 1612 standard and the γ-P-S-N curve, with consideration of the fatigue evaluation requirements of different survival rates and confidence levels. The verification of the modification is performed for three welded joints and for the comparison with the experimental data.

The results indicate that the design survival rate, the design safety margin and the fatigue stress evaluation of welded joint types are all improved by using the modified diagram.

There are relatively few studies on modifying octagonal Goodman–Smith fatigue limit diagram. In this paper, a modified diagram is proposed and applied in order to ensure the safety and durability of key welded structures of rail vehicles.

This study aims to identify the key factors that influence household pro-environmental behaviors (HPEBs) and explore the differences caused by the same influencing factors between household waste management behavior (HWM) and household energy-saving behavior (HES).

A meta-analysis was conducted on 90 articles about HPEBs published between 2009 and 2023 to find the key factors. HPEBs were further categorized into HWM and HES to investigate the difference influenced by the above factors on two behaviors. The correlation coefficient was used as the unified effect size, and the random-effect model was adopted to conduct both main effect and moderating effect tests.

The results showed that attitude, subjective norms, and perceived behavioral control all positively influenced intention and HPEBs, but their effects were stronger on intention than on HPEBs. Intention was found to be the strongest predictor of HPEBs. Subjective norms were found to have a more positive effect on HES compared to HWM, while habits had a more positive effect on HWM. Furthermore, household size was negatively correlated with HWM but positively correlated with HES.

The same variables have different influences on HWM and HES. These results can help develop targeted incentives to increase the adoption of HPEBs, ultimately reducing household energy consumption and greenhouse gas emissions and contributing to the mitigation of global warming.

This study aims to examine whether Chinese firms increase their concerns about analysts’ earnings forecasts following the split-share structure reform (SSR) in 2005, which removed trading restrictions on approximately 70% of the shares of listed firms.

Using data from 2002 to 2019, the authors empirically test the association between meeting or beating analysts’ earnings expectations and the implementation of SSR.

The authors find that firms are more inclined to meet analysts’ earnings expectations after the introduction of SSR. Further analysis shows that firms guide analysts to walk their forecasts down by manipulating third-quarter earnings, suggesting enhanced value relevance between analysts’ forecasts and third-quarter earnings management in the postreform period.

The findings reveal an undesirable side effect of SSR and suggest that policymakers and regulators should consider and carefully manage the complex relationships between firms and analysts.

In contrast to prior studies that predominantly focus on the positive effects of the reform, this study reveals the side effects of SSR and provides new evidence on the mechanisms of meeting or beating analysts’ earnings expectations.

This study aims to solve the problems of large training sample size, low data sample quality, low efficiency of the currently used classical model, high computational complexity of the existing concern mechanism, and high graphics processing unit (GPU) occupancy in the current visualization software defect prediction, proposing a method for software defect prediction termed recurrent criss-cross attention for weighted activation functions of recurrent SE-ResNet (RCCA-WRSR). First, following code visualization, the activation functions of the SE-ResNet model are replaced with a weighted combination of Relu and Elu to enhance model convergence. Additionally, an SE module is added before it to filter feature information, eliminating low-weight features to generate an improved residual network model, WRSR. To focus more on contextual information and establish connections between a pixel and those not in the same cross-path, the visualized red as integer, green as integer, blue as integer images are inputted into a model incorporating a fused RCCA module for defect prediction.

Software defect prediction based on code visualization is a new software defect prediction technology, which mainly realizes the defect prediction of code by visualizing code as image, and then applying attention mechanism to extract the features of image. However, the challenges of current visualization software defect prediction mainly include the large training sample size and low sample quality of the data, and the classical models used today are not efficient, and the existing attention mechanisms have high computational complexity and high GPU occupancy.

Experimental evaluation using ten open-source Java data sets from PROMISE and five existing methods demonstrates that the proposed approach achieves an F-measure value of 0.637 in predicting 16 cross-version projects, representing a 6.1% improvement.

RCCA-WRSR is a new visual software defect prediction based on recurrent criss-cross attention and improved residual network. This method effectively enhances the performance of software defect prediction.