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This study aims to examine involvement and perceived usefulness (PU) as the drivers of loyalty for online booking websites, revealing findings of theoretical and practical relevance. The proposed conceptual model is drawn on elaboration likelihood model (ELM) along with the consideration of expectation confirmation model for loyalty development.

A two-stage structural equation modeling was applied to test the reliability and validity of the constructs and the strength of the hypothesized relationships.

Attitudinal loyalty (AL) is found to have a significant role, resulting in behavioral loyalty (BL) toward online booking. The results of this study supported the ELM framework, where involvement and PU resulted in BL through AL. PU and AL also served as mediating mechanisms underlying the impact of consumer involvement on BL.

This study applies the ELM to online ticketing mechanisms and nuances amid AL and BL with their drivers.

The primary objectives of this article are to systematically explore whether and how certain WeChat use motives could lead to bridging social capital, bonding social capital and civic engagement among young people.

The data was collected from a large-scale online survey of 1208 young people in mainland China. Zero-order correlation analyses and structural equation modeling were carried out to examine the corresponding hypotheses.

Obtained findings show that WeChat use for informational and social motivations are positively associated with bonding and bridging social capital. Moreover, bonding social capital could mediate the relationship between WeChat usage for informational and relational motivations and civic engagement.

Theoretically, this article underlines the unique social and technological affordances of WeChat by exploring mobile social media use and how it would contribute to the quality of democracy by fostering young people's engagement in civic life. Practically, bridging and bonding social capital play significant roles in enhancing young people's civic engagement, which could be the meaningful resource for mobile social media designers, managers and government officials.

These obtained outcomes underlined the vital role of these newly emerging communication technologies in fostering democratic involvement and production of social capital in contemporary socially networked society.

This study aims to examine the impact of manager sentiment on the firm performance (FP) of Indian-listed nonfinancial firms. Further, it endeavors to investigate the moderating role of economic policy uncertainty (EPU) and environment, social and governance (ESG) transparency in this relationship.

A noble manager sentiment is introduced using FinBERT, a bidirectional encoder representation from a transformers (BERT)-type large language model. Using this deep learning-based natural language processing approach implemented through a Python-generated algorithm, this study constructs a manager sentiment for each firm and year based on the management discussions and analysis (MD&A) report. This research uses the system GMM to examine how manager sentiment affects FP.

The empirical results suggest that managers’ optimistic outlook in MD&A corporate disclosure sections tends to present higher performance. This positive association remains consistent after several robustness checks – using propensity score matching and instrumental variable approach to address further endogeneity, using alternative proxies of manager sentiment and FP and conducting subsample analysis based on financial constraints. Furthermore, the authors observe that the relationship is more pronounced for ESG-disclosed firms and during the low EPU.

The results demonstrate that the manager sentiment strongly predicts FP. Thus, this study may provide valuable insight for academics, practitioners, investors, corporates and policymakers.

To the best of the authors’ knowledge, this is the first study to predict FP by using FinBERT-based managerial sentiment, particularly in an emerging market context.

This paper explores the association between directors’ and officers’ liability insurance (D&O insurance) and management tone manipulation.

This study uses data from A-share listed non-financial companies from 2009 to 2021 as its sample for empirical tests. In addition, the study relies on text analysis and the construction of models to investigate the relationship between D&O insurance and management tone manipulation.

The authors find that the purchase of D&O insurance will lead to management tone manipulation in the “management discussion and analysis” part of companies’ annual reports, and operating risk and agent cost are the two paths for the effect. Further analysis shows that having a male CEO and employing high-quality auditors can weaken the positive impact of D&O insurance on tone manipulation.

This paper provides a new approach for studying the literature related to D&O insurance and management behavior, and the findings enrich our understanding of the influencing factors and the mechanism of management tone manipulation, thus revealing policy implications for further standardization of the terms and system of D&O insurance in China.

This paper aims to investigate the impact of quality loss in transit on e-commerce supply chain pricing, production and financing decisions.

The authors consider a Stackelberg game model with a supplier, logistics firm and e-commerce platform. The logistics firm is capital-constrained and obtains funding from the e-commerce platform by debt financing or equity financing. Through backward induction, this paper first solves the equilibrium results under the two financing schemes and then reveals the financing preferences of all parties.

The results demonstrate that equity financing reduces financing costs and promotes production significantly. However, it may also lead to overproduction, particularly in markets with poor profitability and high cost factors. When the percentage of product quality loss is large, equity financing is preferable. With the increasing of transportation level, the benefits of debt finance are steadily growing. In addition, equity financing is the Pareto dominant scheme for all firms under certain circumstances. The extensions consider hybrid financing and another quality loss type.

The paper derives the equilibrium solutions and financing preferences, then specifies the threshold for applying financing schemes. Provide guidance for logistics firms’ finance model innovation and core enterprise involvement in the logistics industry.

The paper investigates how logistics firms’ financing strategies are impacted by product quality loss.

Experts may adjust their assessments through communication and mutual influence, and this dynamic evolution relies on the spread of internal trust relationships. Due to differences in educational backgrounds and knowledge experiences, trust relationships among experts are often incomplete. To address such issues and reduce decision biases, this paper proposes a probabilistic linguistic multi-attribute group decision consensus model based on an incomplete social trust network (InSTN).

In this paper, we first define the new trust propagation operators based on the operations of Probability Language Term Set (PLTS) with algebraic t-conorm and t-norm, which are combined with trust aggregation operators to estimate InSTN. The adjustment coefficients are then determined through trust relations to quantify their impact on expert evaluation. Finally, the particle swarm algorithm (PSO) is used to optimize the expert evaluation to meet the consensus threshold.

This study demonstrates the feasibility of the method through the selection of treatment plans for complex cases. The proposed consensus model exhibits greater robustness and effectiveness compared to traditional methods, mainly due to the effective regulation of trust relations in the decision-making process, which reduces decision bias and inconsistencies.

This paper introduces a novel probabilistic linguistic multi-attribute swarm decision consensus model based on an InSTN. It proposes a redefined trust propagation and aggregation approach to estimate the InSTN. Moreover, the computational efficiency and decision consensus accuracy of the proposed model are enhanced by using PSO optimization.

This paper investigates the relationship between managerial sentiment and corporate investment in emerging capital markets. Further, we begin with the assertion that the positive impact of managerial sentiment on corporate investment varies according to the corporate life cycle. Lastly, we investigate whether the relationship between managerial sentiment and corporate investment can be moderated by factors like (1) economic policy uncertainty/geo-political risk, (2) size of the firm, (3) financial constraint, (4) industrial competition, and (5) Environmental Social and Governance (ESG) rating.

This study has considered Indian listed companies (465 firms) for the period spanning from 2003–2004 to 2022–2023. This study constructs the managerial sentiment using a novel large language model-financial bidirectional encoder representation from the Transformers (FinBERT), as well as on management discussion and analysis reports. Then, we employ fixed effect regression to investigate the relationship between managerial sentiment and corporate investment. Additionally, we use propensity score matching, two-stage least squares instrumental variables, and a two-step system generalized method of moments approach for robustness tests.

The findings show a positive and significant relationship between managerial sentiment and corporate investment. Additionally, our results demonstrate that this relationship is evident only during the growth and maturity phase of the corporate life cycle. Moreover, uncertainty pertaining to the economy and geopolitical issues, firm size, financial health, industry dynamics, and ESG disclosure also play a crucial role in shaping the investment-sentiment relationship.

The study is unique because it determines the relationship between managerial sentiment and corporate investment by using the novel FinBERT model. In addition, we have introduced a corporate life cycle, which is an essential aspect of our study. Additionally, this research was conducted in an emerging market with more information asymmetry and weaker disclosure rules. Thus, other emerging markets can benchmark the outcomes.

This study aims to explore the synthesis and tribological performances of di-n-octyl sebacate (DOS) synthesized with spherical nano-MoS₂/sericite (SMS) and carboxylated SMS (CSMS) as catalysts.

SMS and CSMS were used as esterification catalysts to synthesize DOS from sebacic acid and n-octanol. The two catalysts were in situ dispersed in the synthesized DOS after the reaction to form suspensions. The tribological performances of the two suspensions after 20 days of storage were studied.

CSMS was more stably dispersed in DOS than SMS, and they reduced friction by 55.6% and 22.2% and wear by 51.3% and 56.5%, respectively. Such results were mainly caused by the COOH on CSMS, which was more conducive to improving the dispersion and friction reduction of CSMS than wear resistance. Another possible reason was the difference between the dispersion amounts of CSMS and SMS in DOS. The sericite of SMS was converted into SiO₂ to enhance wear resistance, while that of CSMS only partially generated SiO₂, and the rest still remained on the surface to reduce friction.

This work provides a more effective SMS catalytical way for DOS synthesis than the traditional inorganic acid catalytical method. SMS does not need to be separated after reaction and can be dispersed directly in DOS as a lubricant additive. Replacing SMS with CSMS can produce a more stable suspension and reduce friction significantly. This work combined the advantages of surface carboxylation modification and in situ catalytic dispersion and provided alternatives for the synthesis of DOS and the dispersion of MoS₂-based lubricant additives.

Technology triggers business collaboration and partnership as well as becomes an essential part for disruptive business strategies. The literature on this topic is dispersed, and the chapter addresses this gap. This chapter aims to present a systematic literature review of academic studies in disruptive collaborative innovation frameworks and provide guidance for future research by identifying current research gaps. The study uses the PRISMA framework and collects literature from 2015 to 2023 from highly ranked academic venues with the final sample of 112 papers. The section is structured around the PRISMA framework, and results are reported accordingly. The analysis was conducted using a range of methods, including bibliometric analysis, multiple correspondence analysis (MCA), and text network analysis.

The analysis of the literature is presented to identify the main areas of research as well as to gauge the emerging streams. The overall results suggest that this area is starting to develop with limited research available to date. The study identified four theoretical foundations for existing research, aligned with behavioral, network, resource-based (RBV), and knowledge-based views (KBV). The identified theoretical views and themes are discussed, and examples of the studies are provided.

This paper aims to investigate the relative translational control for multiple spacecraft formation flying. This paper proposes an engineering-friendly, structurally simple, fast and model-free control algorithm.

This paper proposes a tanh-type self-learning control (SLC) approach with variable learning intensity (VLI) to guarantee global convergence of the tracking error. This control algorithm utilizes the controller's previous control information in addition to the current system state information and avoids complicating the control structure.

The proposed approach is model-free and can obtain the control law without accurate modeling of the spacecraft formation dynamics. The tanh function can tune the magnitude of the learning intensity to reduce the control saturation behavior when the tracking error is large.

This algorithm is model-free, robust to perturbations such as disturbances and system uncertainties, and has a simple structure that is very conducive to engineering applications.

This paper verified the control performance of the proposed algorithm for spacecraft formation in the presence of disturbances by simulation and achieved high steady-state accuracy and response speed over comparisons.