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The paper aims to build a new objective evaluation method of fabric pilling by combining an integrated image analysis technology with a deep learning algorithm.

Series of image analysis techniques were adopted. First, a Fourier transform transformed images into the frequency domain. The optimal resolution matrix of an exponential high-pass filter was determined by combining the energy algorithm. Second, the multidimensional discrete wavelet transform determined the optimal division level. Third, the iterative threshold method was used to enhance images to obtain a complete and clear pilling ball images. Finally, the deep learning algorithm was adopted to train data from pilling ball images, and the pilling levels were classified according to the learning features.

The paper provides a new insight about how to objectively evaluate fabric pilling grades. Results of the experiment indicate that the proposed objective evaluation method can obtain clear and complete pilling information and the classification accuracy rate of the deep learning algorithm is 94.2%, whose structures are rectified linear unit (ReLU) activation function, four hidden layers, cross-entropy learning rules and the regularization method.

Because the methodology of the paper is based on woven fabric, the research study’s results may lack generalizability. Therefore, researchers are encouraged to test other kinds of fabric further, such as knitted and unwoven fabrics.

Combined with a series of image analysis technology, the integrated method can effectively extract clear and complete pilling information from pilled fabrics. Pilling grades can be classified by the deep learning algorithm with learning pilling information.

The purpose of this study is to propose extended potentials and investigate the applicability of extended Finnis–Sinclair (FS) potential to Cr with the unit cell structure of body-centered cubic (BCC Cr).

The parameters of each potential are determined by fitting the elastic constants, cohesive energy and mono-vacancy formation energy. Furthermore, the ability of the extended FS potential to describe the crystal defect properties is tested. Finally, the applicability of reproducing the thermal properties of Cr is discussed.

The internal relationship between physical properties and potential function is revealed. The mathematical relationship between physical properties and potential function is derived in detail. The extended FS potential performs well in reproducing physical properties of BCC Cr, such as elastic constants, cohesive energy, surface energy and the properties of vacancy et al. Moreover, good agreement is obtained with the experimental data for predicting the melting point, specific heat and coefficient of thermal expansion.

In this study, new extended potentials are proposed. The extended FS potential is able to reproduce the physical and thermal properties of BCC Cr. Therefore, the new extended potential can be used to describe the crystal defect properties of BCC Cr.

Based on complex network theory, a method for critical elements identification of China Railway High-speed 2 (CRH2) train system is introduced in this paper.

First, two methods, reliability theory and complex theory, are introduced, and the advantages and disadvantages for their application in identifying critical elements of high-speed train system are summarized. Second, a multi-layer multi-granularity network model including virtual and actual nodes is proposed, and the corresponding fusion rules for the same nodes in different layers are given.

Finally, taking CRH2 train system as an example, the critical elements are identified by using complex network theory, which provides a reference for train operation and maintenance.

A method of identifying key elements of CRH2 train system based on integrated importance indices is introduced, which is a meaningful extension of the application of complex network theory to identify key components.

Drawing on the conservation of resources (COR) theory, this study aims to examine the influence of abusive supervision on hospitality employees’ helping behaviors, especially, the joint moderating effects of proactive personality and ability to manage resources (i.e. RMA) in the hypothesized relationship.

Using a two-phase design, this study gathered data from 353 employees of ten hotels located in China. To test the hypotheses, the study conducted a series of hierarchical multiple regression analyses.

Findings demonstrated that abusive supervision was negatively related to hotel employees’ helping behaviors. Moreover, both proactive personality and RMA jointly moderated the abusive supervision–helping behavior relationship. Specifically, when both proactive personality and RMA had high degrees, the abusive supervision–employees’ helping behaviors linkage was weakest. Conversely, the strongest impact of abusive supervision on employees’ helping behaviors occurred when both proactive personality and RMA were low.

Hotel managers should reduce mistreatment and cultivate employees’ both proactive personality and RMA, to inhibit the decline of helping behavior resulting from abusive supervision.

First, the current study provides a novel theoretical underpinning of the COR theory to explain the abusive supervision–helping behavior association, particularly in the hospitality context. Second, this study contributes to the boundary effects of abusive supervision on helping behavior by investigating the moderating roles of individual differences (i.e. proactive personality and RMA).

Institutional work mainly focused on the purposive action of rational actors. However, the evolution of institution is not only affected by deliberate actions but also by emergent strategic patterns. Through a qualitative study of emergent aggression strategy in a Chinese leading private firm, Gome, this paper aims to explore the role of emergent strategy in institutional work. The paper finds that emergent strategy influences the normative and cognitive institution unconsciously and offers actors specialized identities. The present analysis also suggests that the emergent strategy-based institution needs a supporting and repairing system for maintenance.

This study primarily considers the micro aspect of emergent strategy and institutional work. It calls for detailed observation, interviews and archival materials which can make up a comprehensive in-depth picture. The authors remain skeptical to what people claim and try to get multiple sources of information. Also, the topic the authors deal with is relatively under-researched, and it is valuable to get explorative richness. Therefore, an interpretive qualitative approach is adopted to investigate actual events from “the native’s” perspective.

We found that an emergent strategy, which is realized but without previous plans, can also construct a “proto-type institution”, only in an unconscious way. The precondition is that the strategic resources of the focal firm are abundant enough for it to set the criteria of inter-organizational sanctions and rewards. In addition, the authors believe that supportive system and repairing system underpin the maintenance of established institutions.

First, by combining the research on emergent strategy to institutional work, the authors extend the scope of the latter by adding unconscious institutional work. Even if the agent-based view is adopted, rational actors can still influence the institution. Second, the authors explored the institutional outcome of emergent strategy, which fills the paucity of strategy process research. Third, aggression, the specific emergent strategy in this paper, can be turned into “plans for the future”. Its prevalence in the emerging market will attract more academic attention.

In this study the aim was to investigate under-deposit corrosion (UDC) behavior and the action effects of amino trimethylene phosphonic acid (ATMP) in the oxygen-contained solution.

Electrochemical methods and wire beam electrode techniques were used for the study of ATMP action effect for X65 steel under silica sand and CaCO₃ particle deposit. Electronic coupon technique was used for the study of galvanic effect caused by the deposits and the action effect of ATMP.

ATMP would cause localized corrosion for the silica sand-covered steel. However, it could inhibit the localized corrosion of the steel beneath CaCO₃ particle deposit. Galvanic effect test showed that the galvanic effect caused by the deposits was an important factor for the acceleration of UDC. ATMP had an obvious promotion effect for the galvanic current between bare coupon and silica sand covered coupon and different degrees of localized corrosion were observed beneath both deposits.

The authors believe that the paper may be of particular interest to the readers of the journal as the measurement methods for the UDC of X65 pipeline steel. The experiment they did in the laboratory found that the inhibitor ATMP has a good inhibition effect for bare steel, but it would accelerate the UDC. Different kinds of deposits would have different influences for the UDC behavior with inhibitor added.

Trust is the glue that holds cooperative relationships together and often exists in an asymmetric manner. The purpose of this study is to explore how to mitigate the issue of losses or increased transaction costs caused by opportunistic behavior in a soft environment where trust asymmetry is quite common and difficult to avoid.

This study focuses on examining asymmetric trust between the government and the private sector in public-private partnership (PPP) projects. Drawing upon both project realities and relevant literature, the primary conditional variables influencing asymmetric trust are identified. These variables encompass power perception asymmetry, information asymmetry, interaction behavior, risk perception differences and government-side control. Subsequently, through the use of a survey questionnaire, binary-matched data from both the government and the private sector are collected. The study employs fuzzy-set qualitative comparative analysis (fsQCA) to conduct a configurational analysis, aiming to investigate the causal pathways that trigger asymmetric trust.

No single conditional variable is a necessary condition for the emergence of trust asymmetry. The pathways leading to a high degree of trust asymmetry can be categorized into two types: those dominated by power perception and those involving a combination of multiple factors. Differences in power perception play a crucial role in the occurrence of high trust asymmetry, yet the influence of other conditional variables in triggering trust asymmetry should not be overlooked.

The findings can contribute to advancing the study of trust relationships in the field of Chinese PPP projects. Furthermore, they hold practical value in facilitating the enhancement of trust relationships between the government and the private sector.

Unbalanced bidding can seriously imposed the government from obtaining the best value for the taxpayers' money in public procurement since it increases the owner's cost and decreases the fairness of the competitive bidding process. How to detect an unbalanced bid is a challenging task faced by theoretical researchers and practical actors. This study aims to develop an identification method of unbalanced bidding in the construction industry.

The identification of unbalanced bidding is considered as a multi-criteria decision-making (MCDM) problem. A data-driven unit price database from the historical bidding document is built to present the reference unit prices as benchmarks. According to the proposed extended TOPSIS method, the data-driven unit price is chosen as the positive ideal solution, and the unit price that has the furthest absolute distance measure as the negative ideal solution. The concept of relative distance is introduced to measure the distances between positive and negative ideal solutions and each bidding unit price. The unbalanced bidding degree is ranked by means of relative distance.

The proposed model can be used for the quantitative evaluation of unbalanced bidding from a decision-making perspective. The identification process is developed according to the decision-making process. The finding shows that the model will support owners to efficiently and effectively identify unbalanced bidding in the bid evaluation stage.

The data-driven reference unit prices improve the accuracy of the benchmark to evaluate the unbalanced bidding. The extended TOPSIS model is applied to identify unbalanced bidding; the owners can undertake objective decision-making to identify and prevent unbalanced bidding at the stage of procurement.

This study investigates into how organizations enable the compatibility between intermediary role of conventional systems with disintermediary potentials of blockchain toward the coordination of multiple actors in operations management.

The data were collected from 31 interviewees of the case organizations. We conduct an in-depth case study of successful BC implementation in operations management, by using affordance-actualization (A-A) theory as the theoretical lens.

This study identifies the incompatibility between the affordances of conventional systems and blockchain in coordination/operations management and offers a process model in which a fusion phase enables the affordances to be compatible and then to be actualized. The fusion phase extends A-A theory by transposing and connecting in the context of operations management. The result also shows that blockchain technology has decentralized potentials to address the issues caused by centralized organizations or information systems, while not to replace the intermediary roles of centralized organizations or information systems.

This study makes important theoretical contributions to the literature on blockchain used in operations management, the roles of blockchain enablement and affordance-actualization theory. The findings can also help IT practitioners to implement BC-based applications effectively.

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.