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The purpose of this paper is to find a new method to reinforce high-density polyethylene (HDPE) with polyacrylonitrile fibers (PAN). Furthermore, the crystallinity, viscoelasticity and thermal properties of HDPE composites have also been investigated and compared.

For effective reinforcing, samples with different content fillers were prepared. HDPE composites were prepared by melt blending with double-screw extruder prior to cutting into particles and the samples for testing were made using an injection molding machine.

With the addition of 9 Wt.% PAN fibers, it was found that the tensile strength and flexural modulus got the maximum value in all HDPE composites and increased by 1.2 times than pure HDPE. The shore hardness, storage modulus and vicat softening point of the composites improved continuously with the increase in the proportion of the fibers. The thermal stability and processability of composites did not change rapidly with the addition of PAN fibers. The degree of crystallinity increased with the addition of PAN fibers. In general, the composites achieve the best comprehensive mechanical properties with the fiber content of 9 Wt.%.

The fibers improve the strength of the polyethylene and enhance its ability to resist deformation.

The modified HDPE by PAN fibers in this study have high tensile strength and resistance to deformation and can be used as an efficient material in engineering, packaging and automotive applications.

This study aims to propose a centralized optimal control model for automated left-turn platoon at contraflow left-turn lane (CLL) intersections.

The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness. The proposed model is cast into a mixed-integer linear programming problem and then solved by the branch-and-bound technique.

The proposed model has a promising control effect under different geometric controlled conditions. Moreover, the proposed model performs robustly under various safety time headways, lengths of the CLL and green times of the main signal.

This study proposed a centralized optimal control model for automated left-turn platoon at CLL intersections. The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness

The purpose of this paper is to address the urgent need for transformation and upgrading in the construction industry amid the accelerating industrialization process. The focus is on understanding how value-added for construction enterprises can be achieved through servitization.

Grounded in the perspective of added value of construction enterprises, this paper uses a multicase analysis method, selecting four internationally renowned construction enterprises as the research subjects. The analysis investigates how these case study enterprises transition toward servitization and explores the trends in servitization in construction.

The research results indicate that servitization manifests in two aspects: contractor transition to servitization, and the shift of the construction industry toward integrated delivery. Furthermore, servitization in construction can achieve value-adding through three pathways: increasing product value, creating market demand and providing customized services.

This study contributes by providing insights into the manifestations of servitization and pathways for value-added. It provides a reference for the overall direction and basic strategy of servitization in construction.

Corporate social responsibility (CSR) practice and research regarding construction contractors are comparatively limited. The purpose of this research is to identify a series of CSR issues that reflect the major components of CSR, and to determine the perceived importance of these factors in the context of construction contractors.

A CSR indicator framework was developed based on stakeholder theory. CSR stakeholders and their corresponding CSR performance issues in construction contractors are classified into two levels, i.e. project level and organizational level. This is followed by a questionnaire survey to investigate the perceptions on relative importance of CSR issues of four key stakeholders in typical construction projects in China, i.e. construction contractors, clients, design and engineering consultancy and supervision firms.

The study highlighted a number of factors, e.g. “quality and safety of construction”, “occupational health and safety” and “supplier/partner relationship” were highly regarded; however, their relative importance varied according to the type of responding organization.

The findings indicated the major concerns of the different parties in construction projects, thereby providing a pathway for construction contractors to improve their CSR practice.

The priorities of various stakeholders described in this paper provide a useful reference for construction contractors in the selection and adoption of criteria for CSR performance. A better understanding of perceived priorities of CSR factors from different participating parties also serves useful inputs to construction contractors in their stakeholder management process.

This paper aims to examine the relationship between executive pay disparity and the cost of debt.

The authors use a sample of syndicated bank loans granted to United States (US) listed firms from 1992 to 2014 and adopt the loan yield spread (Chief Executive Officer (CEO) pay slice) as the main proxy for the cost of debt (executive pay disparity). The authors also use the Heckman two-stage model to address the sample selection bias and the two-stage least squares and propensity score matching methods to control the potential endogeneity issues. To test different views about executive pay disparity, the authors adopt the cash-to-stock ratio to proxy for managerial risk-shifting incentives.

The authors find that the cost of debt is significantly higher for firms with larger executive pay disparity, which is robust to sample selection bias, endogeneity concerns, alternative measures and various controls. This positive relationship increases with the risk-shifting incentives of CEOs instead of other top executives, which supports the managerial power view, and is stronger for firms with higher levels of financial distress. The findings suggest that creditors view executive pay disparity are associated with higher credit risk and CEO entrenchment.

This paper reveals one “dark” side of executive pay disparity: it increases the cost of debt and identifies a significant role played by CEOs' risk-shifting incentives. The authors provide direct evidence of the relevance of pay differential to corporate credit analysis.

Servitization and research and development (R&D) innovation provide new developmental opportunities for transformation in the construction industry. This study aims to explore the transformative impact of servitization and R&D innovation on the value added of the construction industry, offering new insights into industry transformation and growth.

This study utilizes panel data from Chinese listed construction companies from 2014 to 2022 to empirically investigate the relationship among servitization, R&D innovation and value added in the construction industry. The data analysis is augmented by incorporating text mining techniques to rigorously investigate the interplay among servitization, R&D innovation and the value added within the construction industry.

The research findings indicate that the impact of servitization on value added follows a positive U-shaped relationship, while the influence of R&D innovation on value added exhibits an inverted U-shaped relationship. Additionally, innovation investment plays a negative moderating role in the relationship between servitization and value added.

This study reveals a fresh perspective on how construction companies can leverage servitization as a strategic pathway for transformation and competitive advantage. The research also lays a theoretical groundwork for future innovation investment strategies in the construction industry, emphasizing the need for a balanced approach to innovation investments to maximize value added.

This study aims to test the possible correlation between the letter height-to-width ratio and consumers’ perception of cuteness.

Through the design of three groups of experimental questionnaires, this paper carried out experiments on subjects with different professional backgrounds.

The result shows that perceived cuteness is only beneficial for consumers who adopt communal relationship (rather than exchange relationship) with the brand. Compared to consumers who adopt communal relationship with brands, letters of lower height-to-width ratio are perceived as cuter and thus more preferable than thinner ones, whereas for consumers who adopt exchange relationship with brands, thinner letters are preferred.

To rule out interference, this study focuses only on the height-to-width ratio of the letters. In the future, researchers can pay more attention to the mobility of brand relationships, consumers’ reading strategy and logos’ visual elements that influence consumers’ brand perception (besides height-to-width ratio).

The research reminds scholars that the height-to-width ratio of letters/logos is not only of aesthetic value but also imposes a great impact on consumer perception. And the result of this research explains the contradiction in consumers’ preference for wide vs thin letter shapes and provides evidence for the interaction between brand relationship norms and letter preferences.

To the best of the authors’ knowledge, this research is the first to explore the influence of letter height-to-width ratio in marketing.

This paper aims to present a new kinematics mapping method based on dynamic equivalent points. In teleoperation, this method enables a robotic (follower) arm to mimic human (leader) arm postures and avoid obstacles in a human-like manner.

The information of the human arm is extracted based on the characteristics of human arm motion, and the concept of equivalent points is introduced. Then, an equivalent point is determined to transform the robotic arm with a nonhuman-like kinematic structure into an anthropomorphic robotic arm. Based on this equivalent point, a mapping method is developed to ensure that the two arms are similar. Finally, the similarity between the human elbow angle and robot elbow angle is further improved by using this method and an augmented Jacobian matrix with a compensation coefficient.

Numerical simulations and physical prototype experiments are conducted to verify the effectiveness and feasibility of the proposed method. In environments with obstacles, this method can adjust the position of the equivalent point in real time to avoid obstacles. In environments without obstacles, the similarity between the human elbow angle and robot elbow angle is further improved at the expense of the end-effector accuracy.

This study presents a new kinematics mapping method, which can realize the complete mapping between the human arm and heterogeneous robotic arm in teleoperation. This method is versatile and can be applied to various mechanical arms with different structures.

We examine whether the social capital of the area where a firm’s headquarters is located affects that firm’s credit rating. Given that credit rating agencies only infrequently visit a firm’s headquarters, it is pertinent to investigate whether this soft information is considered.

In order to test whether social capital affects firms’ credit ratings, we estimate the following model using an ordinary least squares regression: Rating_it = β₀ + β₁ Social Capital_it + ∑ Controls_it + Industry fixed Effects_i + State−year fixed effects_it + ε_it. We follow recent accounting and finance research and measure societal-level social capital at the county level (Jha & Chen, 2015; Cheng et al., 2017; Hasan et al., 2017a, b; Jha, 2017; Hossain et al., 2023). We use four inputs to calculate social capital: (1) voter turnout in presidential elections, (2) the census response rate, (3) the number of social and civic associations and (4) the number of nongovernmental organizations in each county.

W provide evidence that social capital has a causal effect on credit ratings. Interesting is that this effect is not merely localized to firms near credit rating agencies. We also find that the effect of social capital on credit ratings is concentrated among firms with moderate levels of default risk. For firms with extremely low or extremely high default risk, social capital appears irrelevant to credit ratings, suggesting that social capital plays a larger role in more ambiguous contexts or when greater judgment is required. We demonstrate that the effect of social capital on credit ratings disappears when the rating agency has extensive experience in a particular region. This result is consistent with rating agencies stereotyping certain regions of the USA and using that information to inform their ratings when they have less experience in the region. Finally, we find that while social capital is associated with credit ratings, it has no association with future defaults.

Though we cautiously followed prior studies and were confident in our data construction process, it is possible that we are measuring social capital with error.

Our findings suggest that credit rating agencies could benefit from reevaluating how they incorporate non-financial information, such as social capital, into their assessment processes, potentially leading to more nuanced and equitable credit ratings. Additionally, firms could use these insights to bolster their engagement with local communities and stakeholders, thereby enhancing their creditworthiness and attractiveness to investors as part of a broader corporate strategy. The findings also underline the need for regulatory frameworks that foster transparency and the inclusion of social factors in credit evaluations, which could lead to more comprehensive and fair financial reporting and rating systems.

Recognizing that social capital can influence economic outcomes like credit ratings may encourage both communities and firms to invest more in building and maintaining social networks, trust and civic engagement. By demonstrating how social capital impacts credit ratings, our research highlights the potential to address inequalities faced by regions with lower social capital, guiding targeted social and economic development initiatives. Moreover, understanding that regional social capital can influence credit ratings might affect public perception and trust in the impartiality and accuracy of these ratings, which is essential for maintaining market stability and integrity.

Our research provides fresh insights into how social capital, an intangible asset, influences credit ratings – a topic not extensively explored in existing literature. This sheds light on the dynamics between social structures and financial outcomes. Methodologically, our use of the 9/11 attacks as an exogenous shock to measure changes in social capital introduces a novel approach to study similar phenomena. Additionally, our findings contrast with prior studies such as Jha and Chen (2015) and Hossain et al. (2023), by delving deeper into how proximity and familiarity impact financial assessments differently, enriching academic discourse and refining existing theories on the role of local knowledge in financial decisions.

This study attempts to discover effective strategies for mobile commerce applications (apps) to grow their consumer base by releasing app strategic updates. Drawing on the landscape search model from strategy research, this study conceptualizes mobile app update strategy as three interdependent decisions, i.e. what business elements are changed in an app strategic update, how substantial the changes are and when strategic updates are released relative to the competitive environment.

Using a field data set of 1,500 strategic updates of seven rival apps in the mobile travel market, this study integrated fuzzy set qualitative comparative analysis (fsQCA) with econometric analysis to analyze how app strategic update decisions interdependently influence app performance.

This study identified three effective and one ineffective mobile app update strategies from the mixed-method analysis, which verified the complex interdependency of app strategic update decisions. A general takeaway from these strategies is that a complex strategy problem on the mobile platform must be solved with respect to the constraints and capabilities of mobile technology.

This study moves beyond a linear view of the relationship between app update frequency and app performance and provides a holistic view of how and why app strategic update decisions mutually influence one another in their impact on app performance. This work makes contributions by identifying interdependency as a conceptual bridge between strategy and mobile app literature and developing an empirically testable version of the landscape search model.