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To understand the mechanisms underlying social media discontinuance behavior, this study explores factors affecting social media discontinuance behavior from the perspective of social cognitive theory (SCT).

Based on SCT, this study puts forward a theoretical model incorporating habit, excessive use and negative emotions to predict social media discontinuance behavior. The proposed research model was empirically tested with 465 responses collected from WeChat users in China via an online survey. WeChat is one of the most popular social media in China. However, WeChat also faces the challenges of reduced or terminated usage among its users. Partial least squares structural equation modeling (PLS-SEM) technique was used to analyze the data.

The research results in this study show that habit exerts a negative effect on social media discontinuance behavior, while exhaustion and regret have positive influences. In addition, habit positively affects excessive use, which further leads to negative emotions of social media exhaustion and regret. Moreover, gender moderates the relationship between habit and social media discontinuance behavior.

This study adds to the literature of information system (IS) use lifecycle by investigating user behavioral changes regarding a transition from habituated to excessive use and further to discontinuance behavior. This study also helps elucidate the complex role of habit by explaining social media discontinuance from the social cognitive view. Furthermore, this study advances the current understanding of gender difference in social media discontinuance in the Chinese context. The study also offers insights to practitioners on how to prevent individuals from discontinuing their use of social media.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

This study aims to investigate the daily performance of the proposed microgrid (MG) that comprises photovoltaic, wind turbines and is connected to the main grid. The load demand is a residential area that includes 20 houses.

The daily operational strategy of the proposed MG allows to vend and procure utterly between the main grid and MG. The smart metre of every consumer provides the supplier with the daily consumption pattern which is amended by demand side management (DSM). The daily operational cost (DOC) CO2 emission and other measures are utilized to evaluate the system performance. A grey wolf optimizer was employed to minimize DOC including the cost of procuring energy from the main grid, the emission cost and the revenue of sold energy to the main grid.

The obtained results of winter and summer days revealed that DSM significantly improved the system performance from the economic and environmental perspectives. With DSM, DOC on winter day was −26.93 ($/kWh) and on summer day, DOC was 10.59 ($/kWh). While without considering DSM, DOC on winter day was −25.42 ($/kWh) and on summer day DOC was 14.95 ($/kWh).

As opposed to previous research that predominantly addressed the long-term operation, the value of the proposed research is to investigate the short-term operation (24-hour) of MG that copes with vital contingencies associated with selling and procuring energy with the main grid considering the environmental cost. Outstandingly, the proposed research engaged the consumers by smart meters to apply demand-sideDSM, while the previous studies largely focused on supply side management.

Based on cognitive appraisal theory of stress, this study develops an integrated model to examine the double-edged sword effect and boundary conditions of the impact of organizational crisis on employee behavior.

This study collected 672 employees’ data through three stages of longitudinal follow-up. Hierarchical regression analysis and SPSS macro process were used to test the hypotheses.

The paper finds that organizational crisis induces unethical pro-organizational behavior through enhanced job insecurity and foster taking charge by stimulating career calling. Employee resilience negatively moderates the relationship between organizational crisis and job insecurity as well as the indirect effects of organizational crisis on unethical pro-organizational behavior through job insecurity. Conversely, it positively moderates the association between organizational crisis and career calling and the indirect effects on taking charge through career calling.

This study not only expands the research on the mechanisms of organizational crisis' effects on employees' behaviors but also provides practical guidance for corporate managers on how to respond to organizational crisis.

The following insights are available to organizations and managers: first, this study confirms that organizational crisis can be perceived as threatening stressors that create job insecurity, which in turn leads to pro-organizational unethical behavior. Therefore, managers in organizational crisis should focus on stress regulation and guidance, pay timely attention to changes in the mindset of employees to reduce job insecurity, and strictly prohibit unethical pro-organizational behavior. They should promptly calm and control the atmosphere of panic and anxiety in the organization, do a good job of coordinating the division of labor, reduce personnel conflicts and contradictions, create a good organizational climate and reduce employees' sense of stress and negative perceptions of organizational crisis, thus reducing job insecurity and being able to meet the challenges in a better state. Secondly, this study confirms that employees also perceive organizational crisis as challenges and develop career calling, which in turn inspires proactive change behaviors. This suggests that managers in organizational crisis should promote the positive perception of organizational crisis as challenge, stimulate the career calling of employees in organizational crisis and call on and encourage employees to actively adopt taking charge. Therefore, managers should promptly give employees work affirmation, rewards and punishments, enhance the sense of participation and intrinsic motivation of subordinates, improve self-efficacy and self-confidence levels, effectively reduce the negative perception of organizational crisis, awaken positive psychological energy within individuals, increase their sense of belonging to the organization and thus, increase employees' awareness of the positive challenges of organizational crisis, stimulate employees' career calling through positive and optimistic beneficial pressure drive them to lead the corresponding changes in the crisis. Finally, this study confirms that employees' own resilience can change the double-edged sword effect of organizational crisis. Employees with high resilience are more likely to see organizational crisis as challenge and are thus more likely to develop career calling and are more inclined to initiate change, while employees with low resilience are more likely to see organizational crisis as threat, are more negatively affected by them, develop greater job insecurity and are, thus, more inclined to commit unethical pro-organizational behaviors. This reflects the fact that organizations should constantly cultivate employees' resilience and enhance their cognitive toughness at the same time. For instance, the organization can regularly use promotional lectures and scenarios to help leaders and employees establish corporate ethics, strengthen moral beliefs and correctly understand the nature of unethical affinity behavior. Managers should encourage and advocate positive and correct behaviors such as overcoming difficulties, positive innovation and positive suggestions to promote the sustainable and healthy development of the organization.

The results of this study can increase the organization’s understanding of the negative effects of crisis, help the organization take measures to manage and guide the employees in organizational crisis, more effective and targeted functional changes within the organization, reduce stress damage and improve the efficiency and effectiveness of crisis management. It is also beneficial to improve competitiveness and foresight in the organization’s industry and enhance organizations and employees’ resilience.

This study explores the double-edged sword effect of organizational crisis on employees’ behavior from the perspective of the cognitive appraisal theory of stress, which theoretically opens up a new research perspective, enriches the research in the fields of organizational crisis and taking charge, pro-organizational unethical behavior relationship and practically provides theoretical guidance for enterprises and managers on how to effectively respond to organizational crisis from the employees, which is of great practical significance.

The paper aims to tackle the classification of Remote Sensing Images (RSIs), which presents a significant challenge for computer algorithms due to the inherent characteristics of clustered ground objects and noisy backgrounds. Recent research typically leverages larger volume models to achieve advanced performance. However, the operating environments of remote sensing commonly cannot provide unconstrained computational and storage resources. It requires lightweight algorithms with exceptional generalization capabilities.

This study introduces an efficient knowledge distillation (KD) method to build a lightweight yet precise convolutional neural network (CNN) classifier. This method also aims to substantially decrease the training time expenses commonly linked with traditional KD techniques. This approach entails extensive alterations to both the model training framework and the distillation process, each tailored to the unique characteristics of RSIs. In particular, this study establishes a robust ensemble teacher by independently training two CNN models using a customized, efficient training algorithm. Following this, this study modifies a KD loss function to mitigate the suppression of non-target category predictions, which are essential for capturing the inter- and intra-similarity of RSIs.

This study validated the student model, termed KD-enhanced network (KDE-Net), obtained through the KD process on three benchmark RSI data sets. The KDE-Net surpasses 42 other state-of-the-art methods in the literature published from 2020 to 2023. Compared to the top-ranked method’s performance on the challenging NWPU45 data set, KDE-Net demonstrated a noticeable 0.4% increase in overall accuracy with a significant 88% reduction in parameters. Meanwhile, this study’s reformed KD framework significantly enhances the knowledge transfer speed by at least three times.

This study illustrates that the logit-based KD technique can effectively develop lightweight CNN classifiers for RSI classification without substantial sacrifices in computation and storage costs. Compared to neural architecture search or other methods aiming to provide lightweight solutions, this study’s KDE-Net, based on the inherent characteristics of RSIs, is currently more efficient in constructing accurate yet lightweight classifiers for RSI classification.

One of the organization's main goals is to maintain their customers' loyalty, as this can give them a competitive advantage. Therefore, this study is intended to look into the impact of library service quality using LibQUAL + TM dimensions (library service effect, personal control and library as a place), library image and trust on users’ loyalty with the mediating effect of perceived service value and satisfaction.

Data for hypotheses testing were gathered from Minhaj University Lahore (MUL), a private sector university's staff, administration and students, using a survey questionnaire. About 500 questionnaires were randomly distributed, and 407 were utilized as the final sample for analysis. Structural equation modelling (SEM), using SmartPLS 4 and SPSS 25, were used to analyze the empirical data.

First, research reveals that library image, users’ trust, library service effect and personal control significantly influence user satisfaction. Second, the library as a place and personal control are not a significant indicator of perceived service value. Third, perceived service value and satisfaction have a direct positive relationship with users' loyalty. Fourth, trust and library service effect is indirectly related to loyalty via perceived service value. Fifth, satisfaction does not mediate the relationship between library as a place and loyalty.

Customer satisfaction must be guaranteed by library administration if it hopes to win users’ loyalty. In light of the fact that a variety of factors can affect customer satisfaction, their perception and loyalty, library management should enhance not just the quality of library services along with other factors such as library image and users’ trust.

The study examined the independent impact of library image and users’ trust on satisfaction, perceived service value and users’ loyalty, which, within the framework of the library, has never been addressed in literature.

Microribbon with meander type based on giant magnetoimpedance (GMI) effect has become a research hot spot due to their higher sensitivity and spatial resolution. The purpose of this paper is to further optimize the line spacing to improve the performance of meanders for sensor application.

The model of GMI effect of microribbon with meander type is established. The effect of line spacing (Ls) on GMI behavior in meanders is analyzed systematically.

Comparison of theory and experiment indicates that decreasing the line spacing increases the negative mutual inductance and a consequent increase in the GMI effect. The maximum value of the GMI ratio increases from 69% to 91.8% (simulation results) and 16.9% to 51.4% (experimental results) when the line spacing is reduced from 400 to 50 µm. The contribution of line spacing versus line width to the GMI ratio of microribbon with meander type was contrasted. This behavior of the GMI ratio is dominated by the overall negative contribution of the mutual inductance.

This paper explores the effect of line spacing on the GMI ratio of meander type by comparing the simulation results with the experimental results. The superior line spacing is found in the identical sensing area. The findings will contribute to the design of high-performance micropatterned ribbon with meander-type GMI sensors and the establishment of a ribbon-based magnetic-sensitive biosensing system.

The importance of service firms cooperating with digital platforms is widely acknowledged. The authors study three contractual relationships (fixed-cost, cost-sharing, and profit-sharing) between service firms (specifically hotels) and digital platforms in a highly fragmented service supply chain to examine which of these contract types optimizes profits.

The authors extend prior models analyzing the optimal expected total profit from the travel service firm (hotel)–digital platform relationship, providing new insights into each contract type’s ability to coordinate decentralized systems and optimize profits for both parties.

This study finds that fixed cost contracts cannot coordinate the decentralized system. Cost-sharing contracts can coordinate the decentralized system but only allow one channel profit split. In contrast, profit-sharing contracts may not always perfectly coordinate the decentralized system but support alternative profit allocations. Practically, both profit-sharing and cost-sharing contracts are preferable to fixed-cost contracts.

The paper includes implications for travel service firm managers to consider when structuring contracts with digital platforms to focus on profit optimization. Profit-sharing contracts are most preferable when cost and revenue data are fully shared between parties, while cost-sharing contracts are preferable over fixed-cost contracts.

This study extends prior investigations into the utility of different contract types on the optimal profit of a travel service firm (hotel)-digital platform provider relationship. The research fills a gap in the literature concerning the contracts used in these relationship types.

We attempt to construct a grey three-way conflict analysis model with constraints to deal with correlated conflict problems with uncertain information.

In order to address these correlated conflict problems with uncertain information, considering the interactive influence and mutual restraints among agents and portraying their attitudes toward the conflict issues, we utilize grey numbers and three-way decisions to propose a grey three-way conflict analysis model with constraints. Firstly, based on the collected information, we introduced grey theory, calculated the degree of conflict between agents and then analyzed the conflict alliance based on the three-way decision theory. Finally, we designed a feedback mechanism to identify key agents and key conflict issues. A case verifies the effectiveness and practicability of the proposed model.

The results show that the proposed model can portray their attitudes toward conflict issues and effectively extract conflict-related information.

By employing this approach, we can provide the answers to Deja’s fundamental questions regarding Pawlak’s conflict analysis: “what are the underlying causes of conflict?” and “how can a viable consensus strategy be identified?”

Amid rapid technological progress, the construction industry is embracing Construction 4.0, redefining work practices through emerging technologies. However, the implications of Construction 4.0 technologies to enhancing well-being are still poorly understood. Particularly, the challenge lies in selecting technologies that critically contribute to well-being enhancement. Therefore, this study aims to evaluate the implications of Construction 4.0 technologies to enhancing well-being.

A list of Construction 4.0 technologies was identified from a national strategic plan on Construction 4.0, using Malaysia as a case study. Fourteen construction industry experts were selected to evaluate the implications of Construction 4.0 technologies on well-being using fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The expert judgment was measured using linguistic variables that were transformed into fuzzy values. Then, the collected data was analyzed using the following analyses: fuzzy TOPSIS, Pareto, normalization, sensitivity, ranking performance and correlation.

Six Construction 4.0 technologies are critical to enhancing well-being: cloud & real-time collaboration, big data & predictive analytics, Internet of Things, building information modeling, autonomous construction and augmented reality & virtualization. In addition, artificial intelligence and advanced building materials are recommended to be implemented simultaneously as a very strong correlation exists between them.

The novelty of this study lies in a comprehensive understanding of the implications of Construction 4.0 technologies to enhancing well-being. The findings can assist researchers, industry practitioners and policymakers in making well-informed decisions to select Construction 4.0 technologies when targeting the enhancement of the overall well-being of the local construction industry.