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Prior research on meeting or beating earnings thresholds documents that firms with earnings momentum are awarded with valuation premiums. However, it is unclear from this strand of literature why this is the case. Therefore, this study aims to investigate the effects of time-varying earnings persistence on earnings momentum and their pricing effects.

This study exploits a firm that reports earnings momentum as research setting to examine whether earnings persistence is significantly higher for firms with consecutive earnings increases. In addition, it investigates a relation between earnings momentum and fundamentals-driven earnings persistence and estimates return associations of earnings momentum conditional on economic-based persistence of earnings.

The empirical evidence suggests that firms with earnings momentum reflect higher time-varying earnings persistence. It further reveals that longer duration of earnings momentum is associated with higher fundamentals-driven earnings persistence. More importantly, valuation premiums are exclusively assigned to earnings momentum determined by strong firm fundamentals, not momentum itself.

This study provides new empirical evidence that valuation premiums accrued to firms with earnings momentum are conditional on time-varying earnings persistence. The research implications are relevant to investors, regulators and auditors, as the results bring conclusions that earnings momentum reflects successful business models not poor accounting quality. This leads to a more complete view of earnings momentum and helps allocate resources when evaluating earnings-momentum firms.

Relationship conflict between the owners and contractors is inevitable, which could induce negative consequences. Yet, the existing literature mostly focused on its direct effects on project performance and ignored the process by which relationship conflict gradually deteriorates cooperation as well as corresponding managerial approaches. Given the fact that relationship conflict originates from interdependent tasks, the proposed theoretical model is intended to measure relational behavior as an instant outcome of relationship conflict, and explore the buffering role of contract enforcement approach.

This paper develops the conceptual model based on the literature review. Then the questionnaire survey was conducted. The dyadic data obtained from 168 Chinese construction project professionals were analyzed by the Partial Least squares Structural Equation Modeling (PLS-SEM) technique.

The results show that relational behavior partially mediates the link between relationship conflict and project performance. Besides, three types of contract enforcement approaches are found to differentially change the negative link between relationship conflict and relational behavior. Rigid contract enforcement can worsen the adverse effects of relationship conflict on relational behavior, whereas flexible contract enforcement can alleviate these negative effects. The level of mitigation hinges on whether compromising behaviors or obliging behaviors are chosen.

The study extends the knowledge of conflict theory and contract theory in the construction field. Based on the proposed conceptual model and PLS-SEM results, this study contributes to the understanding of relationship conflict’s consequences between the owners and contractors and enriches conflict management approaches in the construction field.

In recent decades, there has been a significant increase in global concern regarding the impact of economic activities on the environment and climate change. In this context, green entrepreneurship has become a growing trend in the business world. One of the most important benefits of green entrepreneurship is enhancing energy efficiency and resource utilization. By reducing the resources required to produce a product or deliver a service, green entrepreneurship can contribute to cost reduction and operational efficiency improvement. By implementing sustainable business practices, organizations can enhance their image in the eyes of consumers and attract new customers who are environmentally conscious. This chapter addresses the identified gap in the literature regarding the influence of green entrepreneurial activities on organizational financial performance from the perspective of employees in organizations engaged in such activities (waste reduction, waste recycling, energy conservation, air pollutant reduction, packaging reduction, sustainable transportation). Organizational financial performance is measured through perceived performance compared to the previous year and performance relative to expectations. Two visible financial indicators have been selected for analysis: turnover and net profit.

This study aims to answer two significant questions: What are the relative consumer and firm-level effects of marketing through metaverse compared to conventional marketing endeavours? What are the current trends in utilizing the metaverse as reported in the recent literature?

This study uses a systematic literature review methodology, using a Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart to synthesize existing research. A total of 35 articles written in English were selected and analysed from two databases, Web of Science and EBSCO Host.

The findings indicate that consumer-level effects of the metaverse include consumer loyalty and brand attachment. The firm-level benefits are decentralization and cost reductions. The paper proposes a framework indicating variables that could attenuate or enhance the association between immersive components of the metaverse and their resultant effects.

This study contributes to understanding the role of metaverse in marketing practices related to the marketing mix components. The study conceptualizes a novel framework for the metaverse and its resultant effects.

Three-way decision (3WD) and probabilistic rough sets (PRSs) are theoretical tools capable of simulating humans' multi-level and multi-perspective thinking modes in the field of decision-making. They are proposed to assist decision-makers in better managing incomplete or imprecise information under conditions of uncertainty or fuzziness. However, it is easy to cause decision losses and the personal thresholds of decision-makers cannot be taken into account. To solve this problem, this paper combines picture fuzzy (PF) multi-granularity (MG) with 3WD and establishes the notion of PF MG 3WD.

An effective incomplete model based on PF MG 3WD is designed in this paper. First, the form of PF MG incomplete information systems (IISs) is established to reasonably record the uncertain information. On this basis, the PF conditional probability is established by using PF similarity relations, and the concept of adjustable PF MG PRSs is proposed by using the PF conditional probability to fuse data. Then, a comprehensive PF multi-attribute group decision-making (MAGDM) scheme is formed by the adjustable PF MG PRSs and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. Finally, an actual breast cancer data set is used to reveal the validity of the constructed method.

The experimental results confirm the effectiveness of PF MG 3WD in predicting breast cancer. Compared with existing models, PF MG 3WD has better robustness and generalization performance. This is mainly due to the incomplete PF MG 3WD proposed in this paper, which effectively reduces the influence of unreasonable outliers and threshold settings.

The model employs the VIKOR method for optimal granularity selections, which takes into account both group utility maximization and individual regret minimization, while incorporating decision-makers' subjective preferences as well. This ensures that the experiment maintains higher exclusion stability and reliability, enhancing the robustness of the decision results.

This study aims to critically evaluate the competitiveness of Transformer-based models in financial forecasting, specifically in the context of stock realized volatility forecasting. It seeks to challenge and extend upon the assertions of Zeng et al. (2023) regarding the purported limitations of these models in handling temporal information in financial time series.

Employing a robust methodological framework, the study systematically compares a range of Transformer models, including first-generation and advanced iterations like Informer, Autoformer, and PatchTST, against benchmark models (HAR, NBEATSx, NHITS, and TimesNet). The evaluation encompasses 80 different stocks, four error metrics, four statistical tests, and three robustness tests designed to reflect diverse market conditions and data availability scenarios.

The research uncovers that while first-generation Transformer models, like TFT, underperform in financial forecasting, second-generation models like Informer, Autoformer, and PatchTST demonstrate remarkable efficacy, especially in scenarios characterized by limited historical data and market volatility. The study also highlights the nuanced performance of these models across different forecasting horizons and error metrics, showcasing their potential as robust tools in financial forecasting, which contradicts the findings of Zeng et al. (2023)

This paper contributes to the financial forecasting literature by providing a comprehensive analysis of the applicability of Transformer-based models in this domain. It offers new insights into the capabilities of these models, especially their adaptability to different market conditions and forecasting requirements, challenging the existing skepticism created by Zeng et al. (2023) about their utility in financial forecasting.

Social commerce (s-commerce) offers community-based platforms that facilitate customer-to-customer interactions and the development of customers' social shopping-based experience. While prior research has addressed the role of customer engagement (CE) in boosting s-commerce-based sales and performance, insight into the effect of s-commerce attributes on CE remains tenuous. Addressing this gap, this study examines the role of specific s-commerce attributes (i.e. community, collaboration, interactivity and social dynamics) on CE, which is, in turn, proposed to impact customers' repurchase- and electronic word of mouth (eWOM) intention.

A web-based survey was deployed to target users of a popular s-commerce platform, Etsy.com. Partial least squares structural equation modeling (PLS-SEM) was, then, used to analyze the survey data collected from 390 users.

The results reveal that the four examined attributes positively affect CE. The findings also demonstrate CE's positive effect on customers' repurchase- and eWOM intention.

Though CE has been identified as a key s-commerce performance indicator, little remains known about the role of specific s-commerce attributes in driving CE, as, therefore, explored in this research. Specifically, the authors examine the role of s-commerce-based community, collaboration, interactivity and social dynamics on CE. Their analyses also corroborate that CE, in turn, drives customers' post-purchase (i.e. repurchase/eWOM) intention. Managerially, our findings can be used to develop more engaging s-commerce platforms.

The adoption of mobile payment remains low in certain regions, highlighting the need to identify the factors that enable and inhibit its adoption. This study aims to address this gap by investigating the role of information security, loss aversion and the moderating influence of the herd effect on Inertia and behavioral intentions in the adoption of mobile payment systems.

A structural equation model was developed and tested with 332 valid questionnaires to examine the proposed hypotheses.

The empirical results reveal that information security plays a significant role as an enabler, while loss aversion acts as an inhibitor of mobile payment adoption. Furthermore, the study uncovers the moderating influence of the herd effect on the relationship between Inertia and behavioral intentions.

This study was conducted in a specific region and may not be generalizable to other regions. Future studies could expand the sample size and scope to enhance the external validity of the findings.

This study offers practical implications for mobile payment service providers. Understanding the key enabling and inhibiting factors identified in this study can guide providers in designing and improving their services. Strengthening information security measures can help build trust among potential adopters, while offering incentives can mitigate the impact of loss aversion and encourage early adoption.

The findings of this study have social implications as they contribute to promoting the adoption of mobile payment systems. Increased adoption can enhance financial inclusion and stimulate economic development.

This study provides novel insights into the enabling and inhibiting factors of mobile payment adoption and highlights the moderating role of the herd effect. By shedding light on the influence of social norms on individual behavior in the context of mobile payment adoption, this study contributes to the existing literature and advances our understanding of this phenomenon.

Gossip spreads like wildfire, damaging relationships, decaying trust and creating a negative work environment. This study aims to investigate the relationship between negative workplace gossip (NWG) and quiet quitting (QQ), while considering the mediating effects of workplace stress and emotional exhaustion (EE).

Drawing upon the conservation of resource theory, the study aimed to comprehend this association in the context of 267 employees from diverse sectors in India, including health care, IT, banking and education. Through a three-wave time lagged survey design, using partial least squares structural equation modeling, significant findings were uncovered.

The results revealed a positive link between NWG and QQ. There was also a positive correlation between NWG and workplace stress. In addition, workplace stress and EE were found to mediate the relationship between NWG and QQ.

The findings have implications for both theory and practice. Organizations should consider implementing strategies to mitigate the prevalence of negative gossip and foster a healthier work environment, promoting employee well-being and retention.

The study reveals the “black box” between NWG and QQ, adding to the body of knowledge on the novel concept of QQ. Second, the study expands the literature on NWG, by examining impact path of how it leads to stress and EE, leading to QQ.

The purpose of this study is to examine how construction project managers’ conflict management styles (CMSs) affect project team resilience from the perspective of social identity theory.

This study adopted a cross-sectional survey design and collected paired data from 110 construction project managers and 474 employees in China. Based on the data collected, the authors tested the proposed hypotheses using hierarchical regression analysis.

The results show that a project manager’s cooperative CMS positively affects team resilience, and a project manager’s competitive and avoidant CMS negatively affects team resilience. Team followership plays a mediating role in this relationship. The team power distance moderates the effects of a project manager’s cooperative and avoidant CMSs on team followership.

This paper enriches the existing literature on conflict management in construction projects and have potential guiding significance and application value for team resilience management practices.