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Customer value co-creation behavior is promising but undertheorized. To bridge this gap, this study examines the viability of a social cognitive theory positing that customers' value co-creation behavior is shaped by their co-creation experience, self-efficacy, and engagement.

Using healthcare as a case, a stratified random sample comprising 600 patients from 40 hospitals across eight metropolitan cities in an emerging economy was acquired and analyzed using co-variance-based structural equation modeling (CB-SEM).

Customers' co-creation experience has a positive impact on their co-creation self-efficacy, co-creation engagement, and value co-creation behavior. While co-creation self-efficacy and engagement have no direct influence on value co-creation behavior, they do serve as mediators between co-creation experience and value co-creation behavior, suggesting that when customers are provided with a co-creation experience, it enhances their co-creation self-efficacy and engagement, ultimately fostering value co-creation behavior.

A theory of customer value co-creation behavior is established.

By applying the American Customer Satisfaction Index (ACSI) model to virtual art exhibitions, this research aims to reveal insights into the factors impacting visitor satisfaction and electronic word-of-mouth (e-WOM). Furthermore, the investigation of exhibition promotion seeks to understand how external factors contribute to the overall visitor experience in virtual art exhibitions.

With advancements in virtual communication technology and the transformative impact of the COVID-19 pandemic in recent years, there has been a notable surge in the popularity of virtual art exhibitions based on the Internet. This study uses the ACSI model to examine visitor satisfaction and e-WOM in virtual art exhibitions. Additionally, it explores the influence of exhibition promotion on the ACSI model.

Key findings revealed that 1) both promotion efforts and e-WOM exhibited significant relationships with the ACSI model, and 2) most of the relationships within the ACSI model were consistent with previous research outcomes.

This study extends the ACSI model’s application to virtual art exhibitions, enhancing its relevance. Additionally, it addresses the knowledge gap concerning the direct impact of promotion on audience expectations and its relationship with the ACSI model in virtual art exhibitions. Furthermore, the research explores the influence of customer satisfaction on electronic word-of-mouth in exhibitions, offering valuable insights for exhibition evaluation systems. The study serves as a guide, providing data and models for researchers investigating virtual art exhibitions.

The purpose of this paper is to study the importance of image data in hotel selection-recommendation using different types of cognitive features and to explore whether there are reinforcing effects among these cognitive features.

This study represents user-generated images “cognitive” in a knowledge graph through multidimensional (shallow, middle and deep) analysis. This approach highlights the clustering of hotel destination imagery.

This study develops a novel hotel selection-recommendation model based on image sentiment and attribute representation within the construction of a knowledge graph. Furthermore, the experimental results show an enhanced effect between different types of cognitive features and hotel selection-recommendation.

This study enhances hotel recommendation accuracy and user satisfaction by incorporating cognitive and emotional image attributes into knowledge graphs using advanced machine learning and computer vision techniques.

This study advances the understanding of user-generated images’ impact on hotel selection, helping users make better decisions and enabling marketers to understand users’ preferences and trends.

This research is one of the first to propose a new method for exploring the cognitive dimensions of hotel image data. Furthermore, multi-dimensional cognitive features can effectively enhance the selection-recommendation process, and the authors have proposed a novel hotel selection-recommendation model.

This study aims to investigate the influence of network power on exploratory and exploitative innovation and examines the moderating effects of power distance and procedural justice on these untested relationships.

This study uses survey data collected from firms in China and explores the influential mechanisms of network power, power distance and procedural justice in firm innovation.

This study empirically shows that network power has an inverted U-shaped effect on exploratory and exploitative innovation. Power distance weakens the effect of network power on exploratory and exploitative innovation, and procedural justice enhances the effect of network power on exploratory and exploitative innovation.

This study extends resource dependence theory and contributes to the literature on innovation management. Future studies should use different collection channels or research methods to provide more evidence for model promotion. In addition, the dynamic power game among network members and the roles of other mediators or moderators warrant further consideration.

Managers should exercise power strategies properly and ensure that their innovation income exceeds expenditures. Managers need to pay serious attention to power distance and procedural justice in the network and formulate suitable cooperation strategies based on actual conditions.

This study applies the resource dependence theory to investigate the influence of network power on exploratory and exploitative innovation. In addition, the moderating roles of power distance and procedural justice in the above relationships, which have rarely been discussed in previous studies, were tested.

This paper aims to investigate the following issues: the mechanisms through which different types of top management team’s social capital influence the innovation quality of high-tech firms, and the moderating effect of organizational knowledge utilization on the relationship between top management team’s social capital and innovation quality in high-tech firms.

This study categorizes top management team’s social capital into political, business and academic dimensions, investigating their impact on innovation quality in high-tech firms. Furthermore, a research model is developed with organizational knowledge utilization as the moderating variable. Data from Chinese high-tech firms between 2010 and 2019 are collected as samples for analysis.

The innovation quality of high-tech firms shows an inverted U-shaped trend as the top management team’s political capital and business capital increase. The top management team’s academic capital has a significantly positive correlation with the innovation quality of high-tech firms. Moreover, organizational knowledge utilization plays a significant moderating role in the relationship between the top management team’s social capital and innovation quality in high-tech firms.

This study explores the relationship among different dimensions of top management team’s social capital, innovation quality and organizational knowledge utilization. It holds significant theoretical value in enriching and refining the interactions between top management team’s social capital, knowledge management theory and innovation management theory. In addition, it offers important practical implications for firms to rationally approach top management team’s social capital, emphasize top management team configuration management and establish a comprehensive and efficient organizational knowledge utilization mechanism.

In this study, the central objective is to foresee stock market signals with the use of a proper structure to achieve the highest accuracy possible. For this purpose, three hybrid models have been developed for the stock markets which are a combination of support vector machine (SVM) with meta-heuristic algorithms of particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).All the analyses are technical and are based on the Japanese candlestick model.

Further as per the results achieved, the most suitable algorithm is chosen to anticipate sell and buy signals. Moreover, the authors have compared the results of the designed model validations in this study with basic models in three articles conducted in the past years. Therefore, SVM is examined by PSO. It is used as a classification agent to search the problem-solving space precisely and at a faster pace. With regards to the second model, SVM and ICA are tested to stock market timing, in a way that ICA is used as an optimization agent for the SVM parameters. At last, in the third model, SVM and GA are studied, where GA acts as an optimizer and feature selection agent.

As per the results, it is observed that all new models can predict accurately for only 6 days; however, in comparison with the confusion matrix results, it is observed that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.

In this study, the data for stock market of the years 2013–2021 were analyzed; the long length of timeframe makes the input data analysis challenging as they must be moderated with respect to the conditions where they have been changed.

In this study, two methods have been developed in a candlestick model; they are raw-based and signal-based approaches in which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.

The purpose of this study is to detect the bolt loosening under conditions of impact loading with a low-cost self-powered triboelectric nanogenerator sensor.

In this work, an Al/PTFE-based triboelectric nanogenerator (AP-TENG) is used as a sensor. A pendulum impact device and a force hammer were used to apply the impact loads. The bolt status and the applied torque can be monitored under impact loading conditions by using the output voltage results of the AP-TENGs.

The output voltage results of the current AP-TENG sensor under five different bolt torques, i.e. from 0.5 to 2.5 N m, were measured. The measurements revealed that a thicker buffer layer significantly contributed to the generation of higher voltages. Besides, the AP-TENG was also used to light ten commercial green LEDs in series, and the brightness of the LEDs was high enough even for the daytime, which showed that it can be used as the alarm device. In addition, a sudden loose test was also carried out, and the obvious voltage spikes can be seen without the external impact. The force hammer impact tests have expanded the application scope of the AP-TENG in the bolt loosening detection.

The bolt loosening monitoring is important and useful for the safe operation. The application of TENG technology for detecting bolt loosening remains relatively unexplored. In addition, ten commercial green LEDs can be driven by the AP-TENG sensor, which can be used for the early warning of the bolted loosening status.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0216/

The purpose of this paper is to analyze and compare the mechanical properties of sintered nanosilver with different porosities at both the mesoscopic and macroscopic scales and to conduct a multiscale analysis of the porosity effect on the mechanical properties of sintered nanosilver.

This paper establishes a mesoscopic model for the uniaxial tension of sintered nanosilver and a macroscopic model for chips containing sintered silver layers. Using the finite element method, combined with crystal plasticity theory and unified creep plasticity theory, a multiscale analysis is conducted for the mechanical properties of sintered nanosilver. First, stress distribution characteristics under uniaxial tensile loading for different porosities in sintered nanosilver polycrystal models are analyzed at the mesoscopic scale. Second, at the macroscopic scale, the mechanical performance of sintered nanosilver layers with varying porosities in high-power chip models under cyclic loading is analyzed. Finally, the porosity influence on the damage evolution in sintered nanosilver is summarized, and simulations are conducted to explore the evolution of damage parameters in sintered nanosilver under different porosities.

In the mesoscopic model, the presence of mesoscale voids affects the stress distribution in sintered nanosilver subjected to tensile loading. Sintered nanosilver with lower porosity exhibits higher tensile strength. In the macroscopic model, sintered nanosilver layers with lower porosity correspond to a more uniform stress distribution, whereas higher porosity leads to faster accumulation of plastic strain in the sintered layer. During chip packaging processes, improving processes to reduce the porosity of sintered layers can delay the initiation of damage and the propagation of cracks in sintered nanosilver.

During chip packaging processes, improving processes to reduce the porosity of sintered layers can delay the initiation of damage and the propagation of cracks in sintered nanosilver.

This paper innovatively uses a mesoscopic crystal plasticity constitutive model and a macroscopic unified creep plasticity constitutive model to analyze the mechanical behavior of sintered nanosilver with different porosities. It comprehensively investigates and explains the influence of porosity on the mechanical performance of sintered nanosilver across multiple scales.

This paper aims to design a novel test device and study the wear properties and the thermal mechanisms of roller pairs in dual-freedom sliding contacts.

On the transition process of lubrication regimes, experiments were conducted with various values of running speed and slip ratio obtained by two motorized spindles. Temperature and surviving time would be obtained of GCr15/GCr15 and DLC/GCr15 friction pairs. Micro photography was obtained with a PGI 3D stylus profiler and a confocal microscopy OLS4000-3D. An empirical mode decomposition method was used to eliminate measure errors.

Results showed that, even with little initial lubricant, rolling/sliding pairs still rotated for a certain time. With the synthetic actions of the dual-freedom sliding, the loss of lubrication and the tilt, interesting helical grooves appeared. Sliding speeds had remarkable effects on survive time, temperatures and surface topographies. In addition, the equilibrium values of the temperature and the surface roughness were obtained in sufficient oil supply. Extreme wear-out conditions were obtained with starved lubrication. Diamond-like carbon coatings showed better heat resistance and better wear resistance.

This work would be critical for the life design and the heat treatment of rolling bearings in the full flood lubrication and the starved lubrication.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0164/

Although buying firms increasingly adopt supplier development to help suppliers enhance their ability to deal with environmental issues, little is known about the mechanisms by which buyer-led environmental supplier development (ESD) affects the environmental management capabilities (EMC) of suppliers. Focusing on the supplier perspective and specifically on the role of psychological mechanisms at the supplier level, the authors adopt the stimulus–organism–response framework from functionalist psychology to investigate the mediating role of environment-related supplier perceived relationship value in the association between ESD, in the form of environmental requirements and audits (indirect development – ID) vs. direct development projects (direct development – DD), and supplier EMC.

The authors used structural equation modeling and regression analysis to test the hypotheses using survey data from 221 supplying organizations in China.

Results reveal that each of the three considered dimensions of the environment-related supplier perceived relationship value (i.e. economic, strategic and co-creation) helps enhance EMC. However, while DD influences positively all three dimensions, ID has a positive effect on only the economic and strategic dimensions. Moreover, the mediation analysis suggests that, while DD affects EMC both directly and via the three dimensions of environment-related supplier perceived relationship value (partial mediation), ID affects EMC only through its impact on environment-related supplier perceived relationship economic and strategic value (full mediation).

The study sheds light on the psychological mechanisms that drive suppliers’ involvement in green supplier development activities. By doing so, it contributes to the understanding of ESD practices and processes and their effectiveness.