Due to consumer shifts, experiential marketing has become one of the marketing strategies of many companies. In order to understand consumers’ brand identification and brand loyalty from the perspective of customers, this research established a new conceptual model based on the SEMs model. Among them, brand loyalty is the dependent variable, brand identification is the intermediating variable, and the five dimensions of customer experience (Sense, Act, Feel, Think, Relate) are the independent variables. Then, there is only quantitative research method used by this study, and the target population is young users of Samsung high-end mobile phone in China. After distributed the questionnaire online, this study finally got 225 responses from target respondents. Among them, there 56. 4%females and 43. 6%males. Then, the data of them were analyzed by PLS-Smart. According to the data analysis, this study found that Sense, Act, Feel, Think and Relate can explain the brand identification of consumers for 54. 8%, and brand identification can further explain the brand loyalty of consumers for 65%. Then, it found that Sense, Acy and Relate has positive impact on consumer’s brand identification, so the H1, H4 and H5 are supported. At the same time, it also found that brand identification has positive impact on consumer’s brand loyalty, so the H6 is supported. However, this study did not find the correlation between Feel, Think and brand identification, so the H2 and H3 are rejected.

Since the beginning of the new century, the process of globalization has deepened, prompting local governments to implement talent introduction policies to maintain sustainable urban development. Focusing on 27 cities in the Yangtze River Delta region, this study collects talent introduction policy texts and panel data from 2000 to 2010. Using Latent Dirichlet Allocation (LDA) for topic mining on text data, five main topics are identified: talent structure, industrial development, scientific and technological expenditures, financial development level, and innovation and entrepreneurship. To investigate the impact of talent introduction policies on these five topics and the overall level of urban economic development, this study uses the “talent introduction policy” as a quasi-natural experiment. Empirical analysis is conducted with a multi-period difference-in-differences (DID) model and double machine learning to explore the intrinsic mechanisms by which these policies empower urban economic development. The results reveal that: (1) Talent introduction policies have significantly promoted urban economic development, and this conclusion remains robust after a series of tests; (2) These policies indirectly boost urban economic development by enhancing financial development efficiency and increasing educational expenditure; (3) The economic growth-promoting effects of talent introduction policies are more evident in provincial capitals or municipalities, eastern cities, and cities with "211 Project" universities; (4) Talent introduction policies positively impact scientific and technological expenditures and innovation and entrepreneurship, negatively impact industrial structure, and have no significant effect on talent structure and financial development level. This study confirms the necessity of talent introduction policies since the beginning of the new century and provides recommendations for their continued implementation.

Employees must adapt to new digital tools and workflows as part of this digital transformation, but this process often faces significant barriers, including resistances to change, inadequate training and the complexity of technological tools themselves. This paper will focus on these challenges, including how misaligned leadership goals and rigid organisational cultures can further impede successful adaptation. It will examine case studies from retail and healthcare, and how tiered training programs, leadership involvement and culture play a role in this process. The findings reveal that addressing technological and human factors are important in allowing employees to not only adopt digital tools, but to actually applicable. Some practical recommendations to overcome these barriers include training employees on a case-by-case basis, and having leadership advocate for this digital transformation. Leaders should create an environment where employees feel empowered and supported.

The long-term and excessive utilization of plastic significantly contribute to environmental degradation and potential contamination. Notably, plastic undergoes various degradation processes, including photodegradation, thermo-oxidative degradation, and mechanical fragmentation, ultimately resulting in the generation of microplastics (MPs). Recent studies pointed out that MPs could accumulate in multiple human organs, such as the lungs, liver, and pancreas, leading to oxidative stress and cellular toxicity. Our investigation with indicators such as GDP, education, pricing, and cultural attitudes revealed that price as the predominant factor influencing the recycling of plastic bags. We analyzed the relationship between price and recycling rates through a linear regression model with the R packages broom and dplyr, which aims to inform the formulation of new regulatory measures designed to enhance plastic reuse and plastic waste mitigation.

The literature identifies a range of factors influencing M&A motivations, including financial and legal constraints, as well as political uncertainty. The significance of M&A in the market is substantial, as it fosters market consolidation, resource optimization, and industry innovation. This study examines the effects of corporate mergers and acquisitions (M&A) on firm performance and innovation, with a focus on relevant data and trends within the U.S. market. An analysis of over 50,000 firms in the United States reveals that since 1975, more than 75% of companies have participated in M&A activities, with this proportion rising over time. Key sectors include healthcare services and semiconductors. The research demonstrates that successful M&A not only enhances firm size and profitability but also stimulates economic growth in associated industries and regions. These findings offer valuable insights into corporate development strategies and market dynamics, providing important information for both companies and policymakers.

Amid the rapid construction of a new development paradigm, digital transformation has emerged as a critical driver of social progress and economic development. This paper examines the impact of digital transformation on corporate total factor productivity (TFP) based on annual data from A-share listed companies from 2010 to 2023. The study reveals that digital transformation significantly enhances TFP, a conclusion supported by various robustness tests. Furthermore, digital transformation empowers TFP growth by reducing information asymmetry and alleviating financing constraints. Heterogeneity analysis indicates that large enterprises and highly profitable firms tend to exhibit stronger digital transformation capabilities, resulting in more pronounced TFP improvements. This study provides valuable insights for fostering new productivity dynamics and promoting high-quality corporate development.

With the increasing prominence of environmental, social, and governance (ESG) issues, countries around the world are encouraging businesses to incorporate ESG information disclosure into their daily operations and strategic planning as an important evaluation criterion. The electronic information manufacturing industry is a key component of China’s national economy, one of the most dynamic and innovative sectors, and plays a crucial role in industrial transformation and the modernization of social information systems. This article aims to highlight the positive correlation between corporate ESG disclosure levels and innovation capabilities, with a focus on the electronic equipment manufacturing industry, where "innovation" serves as the main competitive advantage. It advocates for companies to actively implement ESG principles and related policy requirements, which can help enhance their innovation capacity. By employing methods such as literature review, data analysis, and case studies, this paper progressively substantiates, explains, and expands the arguments. This research enriches the theoretical understanding of the relationship between ESG disclosure levels and corporate innovation capabilities, and, from the perspective of the new era, offers insights into long-term corporate development strategies.

Based on the AMO theoretical framework, this study examines whether and how corporate social responsibility-oriented human resource management (CSR-HRM) influences employees’ CSR-specific performance. Drawing on 331 employee questionnaires collected at two time points, the findings reveal that CSR-HRM positively impacts employees’ CSR-specific performance. Furthermore, CSR-HRM enhances employees’ CSR-specific performance through three mechanisms: increasing moral efficacy, fostering prosocial motivation, and promoting an organizational CSR climate.

The use of artificial intelligence (AI) in operations management holds the key to efficiency, precision and agility in business decision-making, yet it also involves ethical challenges such as fairness, accountability, transparency and privacy that can undermine trust in AI. This paper examines the ethical considerations of AI use in operations, paying particular attention to data bias, privacy risks and governance. Drawing on major governance frameworks such as the OECD AI Principles and the EU’s Ethics Guidelines for Trustworthy AI, this paper proposes a hybrid governance model to address the unique challenges of operational contexts. A case study in the financial sector is used to further explain how privacy-preserving techniques can safeguard the sensitive customer data needed for AI-driven customer service. Extensive experimentation conducted in that case has shown that privacy-preserving methods such as differential privacy and federated learning can reduce the incidence of unauthorised data-access events by as much as 30 per cent and can improve customer satisfaction by more than 20 per cent. This paper contributes to the dynamic discourse on ethical AI by offering practical recommendations to organisations on how to conduct AI operations in a way that is responsible and compliant.