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The purpose of this paper is to build on Dumay and Cai’s (2014) prior research to provide a deeper analysis of the problems associated with using content analysis (CA) as a research methodology for investigating intellectual capital disclosure (ICD).

Totally, 110 articles utilising CA as a research methodology for inquiring into ICD are analysed based on Krippendorff’s (2013) conceptual CA research framework and design logic, and tied into issues relating to CA as a research methodology for investigating ICD.

The authors advocate that ICD CA researchers need to go back to the drawing board and ensure that future studies rigorously apply the basic logic of CA design. In its current state, ICD CA research needs to take a few steps back, before it can move forward. If ICD CA researchers can accomplish this, then there is an opportunity to undertake rigorous research to develop reliable and valid outputs that add to new knowledge about IC.

The main limitations of the research are the chosen sample of CA-based ICD articles and the adoption of the Krippendorff’s framework. However, the authors have identified the main corpus of CA-based ICD studies and since Krippendorff is the only recognised comprehensive text on CA as a methodology, the authors use the most appropriate data and framework possible for the analysis.

Prior CA studies have laid the foundation for what is a popular research methodology. However, the authors argue that the popularity of CA as a research method for investigating ICD has become so great that at times the research methodology “drives the research questions” as opposed to the “research questions driving the methodology” Hence, this research examines reasons for CA limited contemporary contribution and recommends how this may be overcome rather than prescribing how to conduct ICD CA research.

The purpose of this paper is to review and critique the current status of content analysis (CA) as a research method for inquiring into intellectual capital disclosure (ICD) to determine if CA has a continued role to play in developing new intellectual capital (IC) knowledge.

In all, 110 articles utilising CA as a research methodology for inquiring into ICD are analysed. The research is developed in line with other articles critically investigating IC research conducted by Guthrie et al. (2012), Dumay and Garanina (2013) and Dumay (2014). To help understand the impact of CA research articles, the data set is supplemented by including citation data from Google Scholar. The authors also differentiate the paper from other IC research reviews by critically examining the findings and implications of the articles analysed.

The authors do not hold a very positive view on future research which does not substantially depart from the plethora of articles examining ICD using annual reports as a data source or who do not in some way radically change the approach. The authors are of the view that early research into ICD using CA as a methodology was warranted because there was little knowledge about the pattern of IC disclosure in annual reports and other possible ICD forms. However, the research into ICD using annual reports and other data sources has added little more than prove that companies are unwilling to publicly disclose IC to their stakeholders. While the authors do not hold a positive view on future CA research based on annual reports, the authors do hold out hope that researchers will transform their understanding and application of CA as a research methodology and offer one example of how this might be achieved.

The paper presents a comprehensive critical review of published articles utilising CA as a research methodology for inquiring into ICD along with measuring the impact of the articles using citation data from Google Scholar. Hence, the research and its impacts are simultaneously assessed offering insights into the future role that CA as a research methodology has to play in developing new IC knowledge.

Empirical data on the impacts of entrepreneurial effectuation on firm performance are scattered and controversial. This study conducts a meta-analysis to obtain evidence on whether and under what conditions effectuation is valuable. A contextual framework is proposed that highlights the boundary condition of the performance impact of effectuation.

Both the traditional approach of meta-analysis and advanced techniques of Bayesian meta-analytic tests are used to combine numerous studies from varied research contexts.

Meta-analytic results show that effectuation generally has a positive impact on firm performance, and is context-dependent, leading to stronger performance for older firms and firms in high-tech industries and emerging countries.

The findings provide important implications for entrepreneurs who are considering applying effectuation. This study highlights that effectuation is context-dependent and the performance implications of effectuation are contingent on contextual factors at organizational, industrial and institutional levels. This study extends the contextual understanding of the effectuation–performance relationship.

Using a discrete-time version of the arbitrage-free Nelson–Siegel (AFNS) term structure model, the authors examine how yield curves in the US and China react to exchange rate policy shocks as China introduces gradual reforms to make its exchange rate regime more flexible. The paper aims to discuss this issue.

The authors characterize the specification of the discrete-time AFNS model, prove the uniqueness of the solution for model identification, perform specification analysis on its canonical form and detail the MCMC estimation method with a fast and reliable prior extraction step.

Model decomposition reveals that in the US yield responses, changes in risk premia for medium- to long-term yields dominate changes in yield expectation for short- to medium-term yields, indicating that the portfolio rebalancing effect due to varying risk perception is stronger than the signaling effect due to policy rate expectation.

The results are helpful in diagnosing market sentiment and exchange rate risk pricing as China further internationalizes its currency.

The methodology can be easily extended to study yield curve responses to other scenarios of policy shocks or regime changes.

As information technology advances, the prevalence of AI chatbot products is on the rise. Despite optimistic market projections, consumer skepticism towards these agents persists. This paper aims to expand the scope of the technology acceptance model by integrating the aspect of appearance. It examines the influence of different attributes of AI chatbot, such as usefulness, ease of use and appearance, individually and in combination, on consumers' intentions to share and purchase.

Using an exploratory study of Web Texts, a 2 (usefulness: high vs low) × 2 (ease of use: high vs low) mixed design and a 2 (usefulness: high vs low) × 2 (ease of use: high vs low) × 2 (anthropomorphism appearance: humanoid vs cartoon) for between-subjects designs and the price level (high vs low) for within-subjects designs. The hypotheses were tested by Octoparse and SPSS 22.0.

The research highlights the significant role of usefulness, ease of use and anthropomorphic appearance in shaping consumer attitudes towards AI chatbots, thus influencing their intentions to share information and make purchases. Grouped regression analysis reveals that lower prices exert a more pronounced positive influence on consumers' inclinations to both share and purchase, compared to higher prices. Moreover, novelty-seeking behavior moderates the effect of perceived usefulness or ease of use on attitude. Specifically, heightened novelty-seeking tendencies mitigate the impact of low perceived usefulness or ease of use, leading to sustained positive attitudes towards AI chatbots among consumers.

This study innovatively incorporates product appearance into the Technology Acceptance Model (TAM), considering both the functional attributes and appearance of AI chatbot and their impact on consumers. It offers valuable insights for marketing strategies, extends the scope of TAM application and holds significant practical implications for enhancing enterprise product planning.

随着信息技术的进步, AI聊天机器人产品的普及正在增长。尽管市场对这些代理人持乐观态度, 但消费者对这些代理人的怀疑仍然存在。本文旨在通过整合外观方面来扩展技术接受模型的范围。它考察了AI聊天机器人的不同属性（如有用性、易用性和外观）对消费者分享和购买意图的影响, 单独以及组合。

使用Web文本的探索性研究, 一个2（有用性：高vs低）× 2（易用性：高vs低）的混合设计和一个2（有用性：高vs低）× 2（易用性：高vs低）× 2（人格化外观：类人形vs卡通）用于受试者间设计和价格水平（高vs低）用于受试者内设计。通过 Octoparse 和 SPSS 22.0 测试假设。

研究突出了有用性、易用性和拟人化外观在塑造消费者对AI聊天机器人态度方面的重要作用, 从而影响了他们分享信息和购买的意图。分组回归分析显示, 相对于高价格, 低价格对消费者分享和购买的倾向产生了更为显著的正面影响。此外, 新奇寻求行为调节了感知有用性或易用性对态度的影响。具体来说, 增强的新奇寻求倾向减轻了对低感知有用性或易用性的影响, 导致消费者对AI 聊天机器人持续保持积极态度。

本研究将产品外观创新地纳入技术接受模型（TAM）中, 考虑了AI 聊天机器人的功能属性和外观以及它们对消费者的影响。它为营销策略提供了有价值的见解, 拓展了TAM的应用范围, 并对增强企业产品规划产生了重要的实际影响。

Although the facilitating role of green customer integration in business-to-business (B2B) markets has been highlighted in some green product innovation literature, analysis of the difficulties it can pose is still an underdeveloped field. This paper extends the conflict-based view and examines the effect of green customer integration on customer–firm conflicts and thereby investigates the influence of conflict on green product innovation.

This study conducts a questionnaire survey. Ordinary Least Square regression and structural equation model with Maximum Likelihood Estimation are applied to test the hypotheses.

The results show that green customer information integration is positively related to cognitive conflict, whereas green customer process integration has an inverted U-shaped relationship with cognitive conflict and a positive relationship with affective conflict. Moreover, green product innovation is promoted by cognitive conflict and is damaged by affective conflict.

This study highlights the conflict-related factors that play a role in firm–customer collaboration for green product innovation in B2B markets. It also reveals the potential dark side of green customer integration by explicitly delineating its effects on conflicts.

Aiming at the lack of explanatory power of traditional industrial organization theory in cross-border competition, by introducing the idea of ecological niche, the authors aim to explore the competitive situation of platform-based enterprises when they operate in multiple fields.

With the help of ecological niche theory, construct the niche width and niche overlap index of typical enterprises in the platform economy, and find out the advantages and the intensity of competition through comparative analysis.

In an environment of cross-border competition, large enterprises have significant competitive advantages, and the fierce competition is concentrated among medium-sized enterprises.

The conclusions of this paper not only provide new insights for explaining the phenomenon of cross-border competition in the platform economy, but also provide theoretical reference for the anti-trust enforcement practice in the platform economy.

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.

This paper intends to address the decision-making and coordination of green supply chain (GSC) considering risk-averse manufacturers under mixed carbon policy.

This paper focuses on a GSC consisting of a manufacturer and a retailer, in which the manufacturer is risk-averse (R-A). This paper employs Stackelberg game theory and mean variance analysis to assess the pricing decision-making process under various scenarios. Furthermore, cost-sharing contracts are introduced to coordinate the GSC.

The research results suggest that the green level of the product and the profit of the GSC under a centralized scenario are higher than those under a decentralized scenario, while the retail price is lower. Under the decentralized scenario, the green level of product, wholesale price and manufacturer’s profit in the R-A scenario are lower than the values in the risk-neutrality scenario, while retailer's profit is higher. In addition, when a cost-sharing contract is utilized for coordination in the GSC, it can lead to Pareto improvement, regardless of whether the manufacturer makes risk-neutrality or R-A decisions.

This research provides a deeper understanding of GSC decision-making and coordination strategy under mixed carbon policy with consideration of R-A from a theoretical perspective and provides decision support for enterprises to choose strategies in practice.