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This study explored communication regarding corporate social responsibility (CSR), with a focus on how message specificity influences the images of corporations as well as the attitudes and behavioral intentions of sport consumers. A research model was developed based on the elaboration likelihood model and construal level theory to examine the moderating effect of perceived CSR fit on the relationship between a company’s image and its chosen social cause.

Data were collected through an online survey (N = 338) and analyzed using partial least squares structural equation modeling.

The findings revealed that CSR message specificity positively impacts corporate image, which in turn enhances consumer attitudes and behavioral intentions. Perceived CSR fit negatively moderates the relationship between CSR message specificity and corporate image, indicating that detailed CSR messaging more effectively improves corporate image when consumers perceive a low fit between a company’s core business activities and the social causes that they advocate.

The findings deepen the understanding of CSR communication and offer valuable insights for companies on crafting messages that maximize favorable consumer responses.

This study aims to provide a comprehensive overview of thin-film temperature sensors (TTS), focusing on the interplay between material properties and fabrication techniques. It evaluates the current state of the art, addressing both low- and high-temperature sensors, and explores the potential applications across various fields. The study also identifies challenges and highlights emerging trends that may shape the future of this technology.

This study systematically examines existing literature on TTS, categorizing the materials and fabrication methods used. The study compares the performance metrics of different materials, addresses the challenges encountered in thin-film sensors and reviews the case studies to identify successful applications. Emerging trends and future directions are also analyzed.

This study finds that TTS are integral to various advanced technologies, particularly in high-performance and specialized applications. However, their development is constrained by challenges such as limited operational range, material degradation, fabrication complexities and long-term stability. The integration of nanostructured materials and the advancement of wireless, self-powered and multifunctional sensors are poised to drive significant advancements in this field.

This study offers a unique perspective by bridging the gap between material science and application engineering in TTS. By critically analyzing both established and emerging technologies, the study provides valuable insights into the current state of the field and proposes pathways for future innovation in terms of interdisciplinary approaches. The focus on emerging trends and multifunctional applications sets this review apart from existing literature.

This study integrated the service gap of the PZB model, hidden importance and Taguchi’s quality engineering to develop a new two-dimensional strategic matrix, the Hidden Importance and Relative Quality Performance (HI-RQP) model. The HI-RQP model was then used to determine the managerial implications and improvement direction of memorable dining experience (MDE) attributes of Michelin-starred restaurants (MSRs).

This study collected 619 MDE questionnaires from customers of seven MSRs.

The results reveal that the HI-RQP model comprises four quadrants. Professional and high-quality service, carefully prepared dishes, restaurant style and customer-oriented service attitude are competitive advantages that should be maintained. Conversely, taste and freshness that exceed customers’ expectations and provide extra services to customers are MDE attributes that require urgent improvement.

Besides contributing practically to the enhancement of MDE in MSRs, the findings facilitate a more plausible identification of MDE attributes by integrating various theories into the HI-RQP model.

The purpose of this study was to examine the impact of ChatGPT adoption on consumers’ soccer betting behavior, with a particular focus on behavioral intention and word of mouth, by applying the technology acceptance model (TAM) and the theory of reasoned action (TRA).

A cross-sectional survey design was employed to collect data from 418 soccer bettors in Eskisehir, Türkiye. The study utilized a structured questionnaire with validated measures adapted to the context of ChatGPT adoption in soccer betting. Structural equation modeling was conducted to test the hypothesized relationships among the constructs.

The findings revealed that perceived ease of use significantly influenced both perceived usefulness and attitude, while perceived usefulness also positively affected attitude. Attitude and subjective norms emerged as strong predictors of behavioral intention. Interestingly, perceived usefulness did not directly affect behavioral intention but instead exerted an indirect effect through attitude as the mediator. Additionally, word of mouth was significantly influenced by subjective norms and behavioral intention, highlighting the importance of social influence in promoting ChatGPT adoption within the soccer betting community.

Theoretically, this study extends the application of TAM and TRA by examining behavioral intention and word of mouth in the context of AI adoption, specifically ChatGPT, among soccer bettors. Practically, the findings provide valuable insights for AI developers, offering actionable strategies to enhance user adoption and effectively promote AI innovations within the rapidly evolving soccer betting market.

This study investigates the impact of human capital (managers' capital, employees' capital) and orientation (market orientation, entrepreneurial orientation) for accelerating the digitalization process and improving the firm performance. It also studies the role of supply chains as both direct and indirect mediators of the correlation between digitalization and business performance.

This article aims to develop an empirical study using a random sampling technique and survey data collected from 368 managers and owners of different food enterprises in Vietnam. The study adopted a methodological approach quantitatively. Analysis of the relationships and confirmatory factors was performed using structural equation modeling (SEM), a technique to evaluate the proposed relationships.

In line with expectations, the findings emphasize the impact of human capital (managers' capital, employees' capital) and orientation (market orientation, entrepreneurial orientation) for accelerating the digitalization process and the role of supply chains as both direct and indirect mediators of the correlation between digitalization and improving the firm performance, in the context of emerging markets.

This is an important investigation, according to the authors' knowledge, regarding the role of developing human capital (managers' capital, employees' capital) and orientation (market orientation, entrepreneurial orientation) as a key strategy for accelerating the digitalization process and improving the firm performance. Further, the study's novelty reinforces the role of supply chains as both direct and indirect mediators of the correlation between digitalization and business performance in the Vietnamese food companies, where a market economy is emerging.

Recently, due to the practicability in several domains, generative adversarial network (GAN) has successfully been adopted in the field of natural language generation (NLG). The purpose of this paper focuses on improving the quality of text and generating sequences similar to human writing for several real applications.

A novel model, GAN², is developed based on a GAN with dual adversarial architecture. We train the generator by an internal discriminator with a beam search technique to improve the quality of generated sequences. Then, we enhance the generator with an external discriminator to optimize and strengthen the learning process of sequence generation.

The proposed GAN² model could be utilized in widespread applications, such as chatbots, machine translation and image description. By the proposed dual adversarial structure, we significantly improve the quality of the generated text. The average and top-1 metrics, such as NLL, BLEU and ROUGE, are used to measure the generated sentences from the GAN² model over all baselines. Several experiments are conducted to demonstrate the performance and superiority of the proposed model compared with the state-of-the-art methods on numerous evaluation metrics.

Generally, reward sparsity and mode collapse are two main challenging issues when adopt GAN to real NLG applications. In this study, GAN² exploits a dual adversarial architecture which facilitates the learning process in the early training stage for solving the problem of reward sparsity. The occurrence of mode collapse also could be reduced in the later training stage with the introduced comparative discriminator by avoiding high rewards for training in a specific mode. Furthermore, the proposed model is applied to several synthetic and real datasets to show the practicability and exhibit great generalization with all discussed metrics.

Scholars and practitioners alike are paying attention to entrepreneurial orientation (EO) as an antecedent of the financial performance of SMEs. Other factors foster and improve SMEs' financial performance. This paper aims to shed the light on other two different strategic orientations that may help enhance SMEs' financial performance in addition to EO, namely; market orientation (MO) and brand orientation (BO).

The three different important strategic orientations are explored through two different studies. The first study was conducted to determine the different effects of the three orientations on SMEs' financial performance. Data were collected using a questionnaire among a convenient sample (131) of business owners/managers, and next PLS-SEM was used for data analysis. The financial performance of firms in the second study is hypothesized to be an outcome of a combination of different strategic orientations; therefore, the fsQCA method is applied to explore the causal recipes of those orientations.

The paper concluded that the three different strategic orientations are collectively, of paramount importance to strategic managers of SMEs.

The brand, market and EOs have been discussed discretely in previous studies and this study attempted to provide managers/owners of SMEs with a holistic view of the three different orientations and the amalgamation among them to be beneficial for better financial performance.

This study aims to investigate the role of emoji and the moderating effects of recycling messages in encouraging customers’ attitudes toward recycling and their recycling intentions via processing fluency.

Two 2 × 2 between-subject experiments are conducted to investigate the role of emojis, the moderating role of recycling messages and the mediating role of processing fluency on customers’ recycling experiences.

Study 1 identifies that customers’ attitudes toward recycling are enhanced when a positive emoji is used with a promotion-focused message, compared to a prevention-focused message. Study 2 finds that customers’ attitudes and recycling intentions are enhanced when a positive emoji is used with an upcycling message, compared to a recycling message. Both Study 1 and Study 2 identify the mediating role of processing fluency.

Results suggest strategically using emojis and various recycling messages to enhance customers’ recycling experience.

This study investigates the role of emojis as an effective recycling communication strategy.

The purpose of this study to improve the efficiency of customer acquisition and retention through the design of salary information disclosure mechanism.

This study develops a stylized game-theoretic model of delegating customer acquisition and retention, focusing on how firms choose delegation and wage information disclosure strategy.

The results confirm the necessity for enterprises to disclose salary information. When sales agents are risk neutral, firms should choose multi-agent (MA) delegation and disclose their wages. However, when agents are risk averse, firms may disclose the wages of acquisition agents or both agents in MA delegation, depending on the uncertainty of the retention market.

This paper contributes to the literature on delegation of customer acquisition and retention and demonstrates that salary disclosure can be used as a supplement to the incentive mechanism.

In recent years, the development of metaheuristic algorithms for solving optimization problems within a reasonable timeframe has garnered significant attention from the global scientific community. In this work, a new metaheuristic algorithm inspired by the inflection mechanism of the avian influenza virus H5N1 in poultry and humans, taking into account its mutation mechanism, called H5N1.

This algorithm aims to explore optimal solutions for optimization problems by simulating the adaptive behavior and evolutionary process of the H5N1 virus, thereby enhancing the algorithm’s performance for all types of optimization problems. Additionally, a balanced stochastic probability mechanism derived from the infection probability is presented. Using this mechanism, the H5N1 algorithm can change its phrase, including exploitation and exploration phases. Two versions of H5N1, SH5N1 and MH5N1, are presented to solve single-objective optimization problems (SOPs) and multi-objective optimization problems (MOPs).

The performance of the algorithm is evaluated using a set of benchmark functions, including seven unimodal, six multimodal, ten fixed-dimension multimodal to solve SOPs, ZDT functions and CEC2009 has been used to demonstrate its superiority over other recent algorithms. Finally, six optimization engineering problems have been tested. The results obtained indicate that the proposed algorithm outperformed ten algorithms in SOPs and seven algorithms in MOPs.

The experimental findings demonstrate the outstanding convergence of the H5N1 algorithm and its ability to generate solutions of superior quality.