Search results

The study employs two independent experimental studies to collect data. It focuses on the matching effect between advertising appeals and product types. The Elaboration Likelihood Model serves as the theoretical framework for understanding the cognitive processing involved in consumers' responses to these advertising appeals and product combinations.

This paper aims to investigate the impact of advertising appeals on consumers' intentions to purchase organic food. We explored the interaction between advertising appeals (egoistic vs altruistic) and product types (virtue vs vice) and purchase intention. The goal is to provide insights that can enhance the advertising effectiveness of organic food manufacturers and retailers.

The analysis reveals significant effects on consumers' purchase intentions based on the matching of advertising appeals with product types. Specifically, when egoistic appeals align with virtuous products, there is an improvement in consumers' purchase intentions. When altruistic appeals match vice products, a positive impact on purchase intention is observed. The results suggest that the matching of advertising appeals with product types enhances processing fluency, contributing to increased purchase intention.

This research contributes to the field by providing nuanced insights into the interplay between advertising appeals and product types within the context of organic food. The findings highlight the importance of considering the synergy between egoistic appeals and virtuous products, as well as altruistic appeals and vice products. This understanding can be strategically employed by organic food manufacturers and retailers to optimize their advertising strategies, thereby improving their overall effectiveness in influencing consumers' purchase intentions.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

The purpose of this study is to explore the moderating effect of Confucian values and the mediating effect of relationship quality on the relationship between organizational justice and employee service orientation in the tourism and hospitality industry.

Structural equation modeling was applied to a sample of 421 responses in a questionnaire survey from employees of tourism and hospitality firms in mainland China.

Employee relationship quality fully mediated the relationship between organizational justice and service orientation. Confucian values negatively moderated the direct effect of organizational justice on employee relationship quality and the indirect effect of organizational justice on service orientation.

This study offers insights for hospitality managers how to improve employee service orientation and establish Confucian values in the practice of organizational justice. Tourism and hospitality organizations should equally treat all employees as internal customers and use distinct strategies to manage employees with high and low Confucian values in employee selection and management of training and development.

This study highlights the contributions of organizational justice and relationship quality to employee service orientation. It also demonstrates that Confucian values explain why many Chinese employees are less sensitive to low fairness: these values negatively moderate the organizational justice–relationship quality–service orientation relations. By linking organizational justice to relationship quality and employee service orientation, the findings enrich our understanding of the applications of internal marketing and social exchange theories under Confucian values.

This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the equity market.

The present study employs the Liquidity Adjusted Capital Asset Pricing Model (LCAPM) for pricing systematic liquidity risk using the Fama & MacBeth cross-sectional regression model in the Indian stock market from January 1, 2012, to March 31, 2021. Further, the study employed an exponential generalized autoregressive conditional heteroscedastic (1,1) model to observe the impact of decomposed illiquidity on the equity market’s conditional volatility. The study also uses the Ordinary Least Square (OLS) model to illuminate the return-volatility-liquidity relationship.

The study’s findings indicate that the commonality between individual security liquidity and aggregate liquidity is positive, and the covariance of individual security liquidity and the market return negatively affects the expected return. The study’s outcome specifies that illiquidity time series analysis exhibits the asymmetric effect of directional change in return on illiquidity. Further, the study indicates a significant impact of illiquidity and decomposed illiquidity on conditional volatility. This suggests an asymmetric effect of illiquidity shocks on conditional volatility in the Indian stock market.

This study is one of the few studies that used the World Uncertainty Index (WUI) to measure liquidity and market risks as specified in the LCAPM. Further, the findings of the reverse impact of illiquidity and decomposed higher and lower illiquidity on conditional volatility confirm the presence of price informativeness and its immediate effects on illiquidity in the Indian stock market. The study strengthens earlier studies and offers new insights into stock market liquidity to clarify the association between liquidity and stock return for effective policy and strategy formulation that can benefit investors.

Artificial intelligence (AI) is a powerful and promising technology that can foster the performance, and competitiveness of micro, small and medium enterprises (MSMEs). However, the adoption of AI among MSMEs is still low and slow, especially in developing countries like Jordan. This study aims to explore the elements that influence the intention to adopt AI among MSMEs in Jordan and examines the roles of firm innovativeness and government support within the context.

The study develops a conceptual framework based on the integration of the technology acceptance model, the resource-based view, the uncertainty reduction theory and the communication privacy management. Using partial least squares structural equation modeling – through AMOS and R studio – and the importance–performance map analysis techniques, the responses of 471 MSME founders were analyzed.

The findings reveal that perceived usefulness, perceived ease of use and facilitating conditions are significant drivers of AI adoption, while perceived risks act as a barrier. AI autonomy positively influences both firm innovativeness and AI adoption intention. Firm innovativeness mediates the relationship between AI autonomy and AI adoption intention, and government support moderates the relationship between facilitating conditions and AI adoption intention.

The findings provide valuable insights for policy formulation and strategy development aimed at promoting AI adoption among MSMEs. They highlight the need to address perceived risks and enhance facilitating conditions and underscore the potential of AI autonomy and firm innovativeness as drivers of AI adoption. The study also emphasizes the role of government support in fostering a conducive environment for AI adoption.

As in many emerging nations, the AI adoption research for MSMEs in Jordan (which constitute 99.5% of businesses), is under-researched. In addition, the study adds value to the entrepreneurship literature and integrates four theories to explore other significant factors such as firm innovativeness and AI autonomy.

In the absence of previous work, this study investigates how the psychological contract (PC) influences the safety performance of construction workers in China.

The literature is first consulted to obtain a set of PC and safety performance measures that fits the specific situation of construction workers, which is then moderated by five construction experts. A questionnaire survey of 206 workers from 4 different construction sites is followed by a descriptive statistical analysis of the nature of the PC and level of the safety performance of the respondents. Finally, a regression analysis is used to ascertain the level of influence of the PS, and an analysis is made of the influence of PC on safety performance.

A set of PC and safety performance measures is identified that fits in the construction workers' specific situation. The PC of the respondents is found to be intact and well-performed, and their safety performance is maintained at a high level. Safety performance is highly influenced by the state of the PC, with the three dimensions of safety performance (safety result, safety compliance and safety participation) positively correlated with the three dimensions of the PC (normative, interpersonal and developmental).

Suggestions are made to improve safety production management and safety performance by providing adequate material and economic conditions, helping the workers establish good interpersonal relationships and realize their personal values.

This study aims to examine the mechanisms underlying social media commerce by investigating the interplay between platforms, people and information. Drawing upon trust transfer theory, the research model proposes that the platform’s information provision enhances the credibility of the information source, leading to increased information usefulness, adoption and sharing, ultimately influencing purchase intention.

The research design used in this study was a quantitative approach using a cross-sectional survey method. The study developed a research model based on trust transfer theory and hypothesized relationships between the platform’s information provision, information source credibility, information-related responses and purchase intention. Structural equation modeling was used to analyze the collected data and test the research hypotheses.

The findings supported most of the hypotheses and provided valuable insights into the role of information credibility in shaping consumers’ purchase intentions. Specifically, the study revealed that the platform’s information provision enhances the credibility of the information source, leading to increased information usefulness, adoption and sharing. Furthermore, information usefulness and adoption mediate the relationship between information source credibility and purchase intention.

The limitations of this research include the use of convenience sampling, which may not represent the broader population, and the cross-sectional design, which does not provide an in-depth understanding of the adoption process. The reliance on self-reported data and the limited scope of investigation with only six constructs are additional limitations. Future studies should consider national random sampling, longitudinal designs, multiple data sources and explore negative effects and other potential mediating variables. Despite these limitations, this research contributes to the understanding of social media commerce mechanisms and provides valuable insights for practitioners in the field.

The findings of this study provide valuable insights for platform providers and marketers in the social media commerce environment. First, the study emphasizes the importance of effective messaging in improving information credibility. Platform providers should focus on delivering accurate and trustworthy information to enhance consumers’ perceptions of product quality and increase purchase intentions. Second, marketers can leverage the information-related factors identified in this study, such as information usefulness and adoption, to optimize their marketing efforts. By understanding how consumers perceive and interact with information on social media platforms, marketers can tailor their strategies to effectively engage and influence potential customers. Overall, these practical implications can enhance success in the competitive social media commerce landscape.

The social implications of this study are significant for social media commerce practitioners. The findings highlight the importance of effective messaging and information provision on social media platforms in improving information credibility, thereby enhancing purchase intention. By understanding the mechanisms that drive consumer behavior in the context of social media commerce, platform providers and marketers can optimize their marketing efforts. This includes focusing on delivering trustworthy and useful information, fostering information adoption and sharing among users and ultimately increasing the likelihood of successful transactions. These insights provide valuable guidance for practitioners to navigate the competitive landscape of social media commerce and enhance their chances of success.

The originality of this research lies in its application of trust transfer theory to investigate the mechanisms driving social media commerce. By examining the interplay between platform, people and information, the study specifically focuses on the role of the platform’s information provision in enhancing information credibility and its impact on information-related responses and purchase intentions. This study extends the understanding of the trust transfer mechanism between customers and sellers/brands in customer-to-customer social commerce by emphasizing the importance of effective messaging and information credibility in shaping consumer behavior. The empirical findings contribute to the understanding of information trust transfer and provide a unique perspective on the underlying mechanisms that drive social media commerce.

The purpose of this study is to test the hypotheses proposed by Konadu et al. (2023) for the first time and provide empirical insight on the subject. Corruption concerns affect all economies, but those attempting to avoid foreign grants are especially vulnerable. Stakeholders in these economies have pushed for more honest public sector (PS) workers and better oversight of public funds in an effort to build a more trustworthy and efficient government to improve PS performance. Just as the mechanisms through which employee integrity (EI) influences work performance (WP) have not been proven empirically, neither has the effect of EI on WP in African economies. Also, how purposeful leadership (PL) interacts with EI to boost WP is yet to be empirically examined in the integrity literature.

This paper surveyed and analysed the responses of 875 workers across the three most corrupt large PS organisations in Ghana using Smart PLS 4. Perceived organisational support and contract fulfilment functioned as control factors influencing job satisfaction (JS, a mediator). Psychological need satisfaction and perceived procedural justice serve as control factors for organisational identification (OI, an additional mediator). Education, tenure, job position, sex and age were used as control variables in WP. Product indicator and variance accounted for (VAF) methods were used to estimate the impacts of moderation and mediation, respectively. A 5% level of significance was determined.

As hypothesised, this study found that EI and WP had a significantly positive connection (ß = 0.119, p = 0.026), and both JS (VAF = 25.16%) and OI (VAF = 39.59%) partially mediated this connection. Moreover, PL positively moderated the EI–JS (ß = 0.155, p = 0.000) and EI–OI (ß = 0.095, p = 0.000) connections.

This paper affords empirical insight on the EI–WP relationship, how this relationship is mediated and how the EI–JS and EI–OI relationships are amplified. In this context, it sheds light on new ways in which EI and WP in the PS are improved. In addition, this paper provides a roadmap for forthcoming academics to test the hypotheses in diverse PS contexts globally to triangulate the results.

Leadership in PS organisations must maintain a “values-grounded approach” to all parts of human resource (HR) practices, including hiring, performance reviews, leadership enhancement programmes, training and promotions, if they are to attract, develop and retain employees who stand for the sector’s ethics and beliefs.

This research gives African nations proof that enhancing EI in the PS is important, and it lays out the many ways in which EI transforms into WP. It also draws attention to the challenges that purposeful leaders may help alleviate and the opportunities that they may present.

To the best of the authors’ knowledge, the hypotheses put forward in the conceptual research by Konadu et al. (2023) are tested empirically for the first time in this study. It also adds to the empirical literature that already exists on EI, JS, OI, WP and PL in the PS. This contributes to the disciplines of integrity, performance and leadership by enhancing theoretical frameworks and expanding upon existing knowledge.

Most previous studies predicting review helpfulness ignored the significance of deep features embedded in review text and instead relied on hand-crafted features. Hand-crafted and deep features have the advantages of high interpretability and predictive accuracy. This study aims to propose a novel review helpfulness prediction model that uses deep learning (DL) techniques to consider the complementarity between hand-crafted and deep features.

First, an advanced convolutional neural network was applied to extract deep features from unstructured review text. Second, this study used previous studies to extract hand-crafted features that impact the helpfulness of reviews and enhance their interpretability. Third, this study incorporated deep and hand-crafted features into a review helpfulness prediction model and evaluated its performance using the Yelp.com data set. To measure the performance of the proposed model, this study used 2,417,796 restaurant reviews.

Extensive experiments confirmed that the proposed methodology performs better than traditional machine learning methods. Moreover, this study confirms through an empirical analysis that combining hand-crafted and deep features demonstrates better prediction performance.

To the best of the authors’ knowledge, this is one of the first studies to apply DL techniques and use structured and unstructured data to predict review helpfulness in the restaurant context. In addition, an advanced feature-fusion method was adopted to better use the extracted feature information and identify the complementarity between features.

大多数先前预测评论有用性的研究忽视了嵌入在评论文本中的深层特征的重要性, 而主要依赖手工制作的特征。手工制作和深层特征具有高解释性和预测准确性的优势。本研究提出了一种新颖的评论有用性预测模型, 利用深度学习技术来考虑手工制作特征和深层特征之间的互补性。

首先, 采用先进的卷积神经网络从非结构化的评论文本中提取深层特征。其次, 本研究利用先前研究中提取的手工制作特征, 这些特征影响了评论的有用性并增强了其解释性。第三, 本研究将深层特征和手工制作特征结合到一个评论有用性预测模型中, 并使用Yelp.com数据集对其性能进行评估。为了衡量所提出模型的性能, 本研究使用了2,417,796条餐厅评论。

广泛的实验验证了所提出的方法优于传统的机器学习方法。此外, 通过实证分析, 本研究证实了结合手工制作和深层特征可以展现出更好的预测性能。

据我们所知, 这是首个在餐厅评论预测中应用深度学习技术, 并结合了结构化和非结构化数据来预测评论有用性的研究之一。此外, 本研究采用了先进的特征融合方法, 更好地利用了提取的特征信息, 并识别了特征之间的互补性。

In this study, the authors sought to investigate how the implicit social ties of both project owners and potential backers are associated with crowdfunding project success.

Drawing on social ties theory and factors that affect crowdfunding success, in this research, the authors developed a model to study how project owners' and potential backers' implicit social ties are associated with crowdfunding projects' degrees of success. The proposed model was empirically tested with crowdfunding data collected from Kickstarter and social media data collected from Twitter. The authors performed the test using an ordinary least squares (OLS) regression model with fixed effects.

The authors found that project owners' implicit social ties (specifically, their social media activities, degree centrality and betweenness centrality) are significantly and positively associated with crowdfunding projects' degrees of success. Meanwhile, potential project backers' implicit social ties (their social media activities and degree centrality) are negatively associated with crowdfunding projects' degrees of success. The authors also found that project size moderates the effects of project owners' social media activities on projects' degrees of success.

This work contributes to the literature on crowdfunding by investigating how the implicit social ties of both potential backers and project owners on social media are associated with crowdfunding project success. This study extends the previous research on social ties' roles in explaining crowdfunding project success by including implicit social ties, while the literature explored only explicit social ties.