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This work proposes a research model that explains investment intention in online peer-to-peer (P2P) lending based on the persuasion theory of elaboration likelihood model (ELM). In the proposed model, investment intention indirectly relates to source credibility and argument quality through the mediation of trust. At the same time, the study hypothetically moderates the relationships between source credibility and trust and between argument quality and trust by financial self-efficacy and risk preference.

This research presents an experiment to empirically validate its theoretical rationales. The hypotheses herein were tested using data from working professionals at a large science park in Taiwan. A total of 500 participants took part in the experiment in which the scenario of a pseudo-online P2P lending intermediary was first presented for their perusal, and then questionnaires based on the scenario were provided for the participants to fill out.

Trust cannot be improved over night without making great efforts on source credibility and argument quality in the long run. Online marketers should study market segmentations to decide what appropriate elements and promises should be provided in advertisements in order to improve their source credibility. Moreover, how online intermediaries formulate convincing messages and Polish their delivery communication skills should be improved so as to increase argument quality.

First, the theoretical conceptualization of source credibility and argument quality built upon the ELM not only broadens the boundary of virtual communities beyond the literature that considers source credibility and argument quality as important determinants, but also shows the practical status quo of trust as a critical mediator. Second, this research incorporates financial self-efficacy (based on social cognitive theory) and risk preference (based on economic theory) as important moderators in the development of trust. For that reason, customer education initiatives that influence financial self-efficacy and risk preference are discussed in greater detail.

Aiming at the problems of geometric precision misalignment and unconsidered physical constraints between large components during the measurement-assisted assembly, a self-adaptive alignment strategy based on the dynamic compliance center (DCC) is proposed in this paper, using force information to guide alignment compliantly.

First, the self-adaptive alignment process of large components is described, and its geometrical and mechanical characteristics are analyzed based on six-dimensional force/torque (F/T). The setting method of DCC is studied and the areas of DCC are given. Second, the self-adaptive alignment platform of large components driven by the measured six-dimensional F/T is constructed. Based on this platform, the key supporting technologies, including principle of self-adaptive alignment, coordinate transfer, calculation of six-dimensional F/T and alignment process control, are illustrated.

Using the presented strategy, the position and orientation of large component is adjusted adaptively responding to measured six-dimensional F/T and the changes of contact states are consistent with the strategy. Through the setting of DCC, alignment process runs smoothly without jamming.

This strategy is applied to the alignment experiment of large components muff coupling. The experimental results show that the proposed alignment strategy is correct and effective and meets the real-time requirement.

This paper proposed a novel way to apply force information in large component self-adaptive alignment, and the setting method of DCC was presented to make the alignment process more feasible.

The purpose of this study is to understand how perceived micro-celebrity-product image congruency and product type affect native advertising effectiveness on Instagram. Additionally, the study aims to understand how advertising skepticism and persuasion knowledge affect the effectiveness of native advertising featuring micro-celebrity.

This study was administered online using a 2 (product type: high self-expressive vs low self-expressive) × 2 (micro-celebrity and product congruity: congruent vs incongruent) between-subjects factorial design to test the hypotheses. A total of 186 participants, all Instagram users living in the USA, were recruited using an Amazon Mechanical Turk (MTurk). After screening out 14 respondents who were not Instagram users or did not fully answer the questions, a total sample of 172 valid and complete responses were included for hypotheses testing.

The results revealed that when native advertising featured highly self-expressive products and micro-celebrities with good product image fit, consumers had a more positive attitude toward the ad and the brand, higher source credibility and higher electronic word-of-mouth intention. In addition, advertising skepticism was found to moderate the effect of micro-celebrity-product fit on source credibility.

This study is the first to examine the effect of micro-celebrity and product congruence on native advertising effectiveness. Moreover, the study provides a better understanding of the advertising skepticism and its influence on source credibility. It discusses why a micro-celebrity’s image is a critical factor in shaping attitudes toward native advertising. This study contributes to both the native adverting and influencer marketing literature.

This study aims to investigate the rising trend of virtual influencers – digitally created characters with human-like attributes. It aims to evaluate and compare their effectiveness with human influencers in terms of brand attitudes and purchase intentions. It uncovers the mechanisms underlying the differences in effectiveness observed between virtual influencers and their human counterparts.

The research uses a 2 (influencer type: human vs virtual) × 3 (product type: functional vs symbolic vs experiential) between-subjects design. Through a pilot study (n = 334) and a main study (n = 352), the research examines the interactive effects of influencer and product type on brand attitude and purchase intentions. Hypotheses were developed and tested using moderating mediation models centered on authenticity and product–endorser fit.

Virtual influencers are perceived as less authentic than human influencers across all product types, negatively influencing brand attitude and purchase intention. However, the extent to which influencer type affects brand attitudes and purchase intentions, mediated by product–endorser fit, varies based on the product type.

This research emphasizes two key mechanisms – authenticity and product–endorser fit – influencing the effectiveness of virtual influencers. It suggests that aligning virtual influencers with suitable product types can offset their perceived authenticity deficit, significantly affecting their endorsement effectiveness.

Coronavirus disease 2019 (COVID-19) has resulted in traveling restrictions and decreased the demand among travelers since the end of 2019. Policies and people’s behaviors are gradually changing with the increase in the number of new diagnoses of COVID-19. Tourism increases tourists’ risk of contracting COVID-19 and will undoubtedly be affected by this disease. Based on this assumption and social cognitive theory, this paper aims to explore the impact of COVID-19 on tourism in terms of people’s willingness to travel.

Based on social cognitive theory, this study has designed the model and variables. The data of the paper came from a survey conducted in 29 provinces of China and a total of 618 responses were used for data analysis after deleting invalid questionnaires. Drawing on the structural equation modeling method, this paper processes the data collected from questionnaires to test the hypotheses and come to the results.

The results indicate that the negative impact of COVID-19 will affect the severity perceptions, personal negative effects and positive effects of tourism during the outbreak, which will ultimately influence people’s willingness to travel. During the outbreak of COVID-19, impacted by environmental factors and personal factors, Chinese people’s willingness to travel has been significantly reduced.

This study mainly focuses on people’s willingness to travel and the demand side of tourism to analyze the effects of COVID-19 on tourism, which neglects the supply side of tourism for analysis. Subsequent research should take account of the supply side of tourism and expanding the sample size worldwide to determine the impact of COVID-19 on the tourism industry from a broader perspective.

This study quantitatively analyzes how COVID-19 influenced the tourism industry and precisely determines the possible mechanism of the effect of COVID-19 on tourism by using social cognitive theory to build a model. The insights from the work help to understand how COVID-19 affects people’s willingness to travel during the pandemic and how to address this issue.

新型冠状病毒（COVID-19）自2019年底以来开始被发现, 随后逐渐蔓延至全球, 给人们的生活带来不小的影响。该病毒的发展使得人们的出行受到了较大的限制, 因而减少了人们对于旅游的需求。随着新冠疫情确诊人数的增加, 政府政策和人们的行为也处在变化之中。基于这一假设和社会认知理论, 本文旨在从人们的旅游意愿角度探究新冠疫情对旅游业的影响。

本文所设计的变量和模型是在社会认知理论的基础之上提出的。本研究的数据来源于面向中国29个省市自治区的问卷调查。在剔除无效问卷后, 总共搜集618份有效问卷进行数据分析。本研究采用了结构方程模型, 对假设进行检验、并得出最终结论。

研究结果表明, 新冠疫情带来的负面影响会增加人们对疫情严重性的认知程度、疫情期间旅游给人带来的负面影响增大、正面影响减少, 从而最终影响人们的旅游意愿。在新冠疫情之下, 受到环境、个人因素的影响, 人们的旅游意愿显著降低。

本研究的数据均来源于中国, 所以将本文的结论应用于其他地区时, 由于不同地区的自然和社会环境差异, 结论可能会产生差异。本研究主要聚焦于人们旅游意愿的变化, 即旅游业的需求端, 来分析新冠疫情对旅游业的影响, 忽视了旅游业的供给端在新冠疫情期间对旅游业的影响分析。后续的研究可以考虑从旅游业供给端的变化进行分析、以及将样本数量扩大到全球范围, 从而可以从更广阔的视角来探究新冠疫情对旅游业的影响。

本研究定量分析了新冠疫情如何影响旅游业, 并利用社会认知理论建立模型来精确判断这一影响的可能机理。本文的发现有助于了解新冠疫情如何影响人们在疫情行期间旅行的意愿, 以及制定相关的应对措施。

El coronavirus (COVID-19) se descubrió desde finales de 2019 y luego se extendió gradualmente a todo el mundo, lo que tuvo un gran impacto en la vida de las personas. La propaganda del coronavirus ha provocado muchas restricciones en los viajes de las personas, por lo tanto, reducía la demanda de viaje de las personas. Con el aumento en el número de casos confirmados de COVID-19, las políticas gubernamentales y el comportamiento de las personas también se están cambiando. Basado en esta hipótesis y teoría cognitiva social, este artículo tiene como objetivo explorar el impacto del COVID-19 en el turismo desde la perspectiva de la disposición de las personas a viajar.

Las variables y modelos diseñados en este artículo se proponen sobre la base de la teoría cognitiva social. Los datos para este estudio provienen de las encuestas por cuestionario de 29 provincias, municipios y regiones autónomas de China. Después de excluir los cuestionarios no válidos, se recopilaron un total de 618 cuestionarios válidos para el análisis de datos. En este estudio, se utiliza el modelo de ecuación estructural y la prueba de la hipótesis, al final llegar a la conclusión.

El resultado de la investigación muestra que el impacto negativo del COVID-19 aumenta la conciencia de las personas sobre la gravedad de la epidemia, y el impacto negativo del turismo durante la epidemia se aumenta y el impacto positivo se disminuye, lo que al fianl afecta la disposición de las personas a viajar. Bajo el COVID-19, afectada por factores ambientales y personales, la disposición de las personas a viajar se ha reducido significativamente.

Los datos de este estudio son todos de China, por lo que cuando las conclusiones de este artículo se aplican a otras regiones, las conclusiones pueden diferir debido a las diferencias en los entornos naturales y sociales de diferentes regiones. Esta investigación se centra principalmente en el cambio del deseo de viajar de las personas, es decir, el lado de la demanda del turismo, para analizar el impacto del COVID-19, por eso ignora el análisis del impacto de la oferta turística en el turismo durante el COVID-19. Los estudios posteriores se pueden considerar desde el aspecto de analizar los cambios en el lado de la oferta del turismo y expandir el número de muestras a una escala global, por lo tanto, se puede explorar el impacto del COVID-19 desde una perspectiva más amplia.

El encuentro de este artículo ayuda a comprender cómo el COVID-19 afecta la disposición de las personas a viajar durante la epidemia y a formular medidas de respuesta relevantes.

The nuclear purpose of this research paper is to analyse representative bridges around the world as a tourist attraction and iconic element through destination marketing organisations’ (DMOs’) tourism official websites where these are localised and three online travel agencies’ (OTAs’) websites.

This research used a mixed method. The author carried out Google research (13 March 2023) that included the following search word string “iconic bridges around the world” and “the most famous bridges worldwide” to select the most relevant bridges around the globe. Moreover, this research used a content analysis to examine how Expedia, Booking and Orbitz OTAs promote the bridges through their websites in terms of a tourist attraction, iconic element, tourist package, images and information.

Findings suggest that the most representative bridges analysed in this study are promoted as iconic element and tourist attraction through DMOs’ websites. Nevertheless, Booking, Expedia and Orbitz OTAs promote and sell products and services related to bridges selected, except in the case of the Millau Viaduct in France, the Si-O-Se-Pol bridge in Iran, the Danyang Kunshan Grand bridge in China and the Royal Gorge in the USA. Furthermore, results support that OTAs need to enhance the quality and variety of products and services that are linked to iconic bridges sightseeing tours because at the moment, there is a great uniformity in the promotion of products and services provided.

This paper contributes to broader debates in the importance of bridges as a tourist attraction and iconic element to attract tourists through tourism promotion websites.

Insurance companies exist to manage the risk of others, which is why they are perceived to be competitive in risk management (RM). Considering this, we investigate how different RM capabilities make insurers effective in RM. These capabilities include understanding risk and risk management (URRM), risk identification (RI), risk assessment and analysis (RAA) and risk monitoring (RMON) activities in insurance companies. In addition, the authors probe how these capabilities can jointly yield a competitive advantage for the insurance industry under the resource-based view (RBV) and dynamic capabilities perspective (DCP).

The authors present a latent variable RM model for the insurance industry and employ structural equation modeling (SEM) to test the hypotheses. Furthermore, the authors also conduct confirmatory factor analysis (CFA) and convergent and discriminant validity analysis for model fit and invariance testing, respectively.

The results show that insurers who investigated RM-related capabilities directly influence their risk management practices (RMPs). Moreover, improving these capabilities will make insurers more effective in managing the risks of others. Thus, RM as a business process will yield a competitive advantage for the insurance sector. The findings are supported by the theoretical insights presented by the RBV and DCP. Furthermore, the model also adheres to the convergent and discriminant validity cut-off values.

To the best of the authors’ knowledge, this is the first study examining insurers' RM practices as a source of a competitive advantage.

保險公司存在的目的是為其它公司或個人管理其風險；因此，保險公司在風險管理方面、被認為具有競爭能力。故此、我們擬研究不同的風險管理能力是如何能使保險公司有效地管理風險的呢？這些風險管理能力包括對風險及風險管理之了解、風險辨識、風險評估和分析，以及在保險公司內的風險監控活動。再者，我們探究這些風險管理能力如何根據資源基礎觀點及動態能力理論共同為保險業創造競爭優勢。

我們為保險業展示一個潛在變項風險管理模型，並使用結構方程模型，來測試我們的假設；而且，我們為模型適配度而進行了驗證性因素分析，又為不變性檢定而進行了驗證輻合及驗證區別效度分析。

研究結果顯示、若保險公司審査與風險管理相關之能力，這會直接影響其對風險管理之措施；而且，若保險公司能改善其風險管理之能力，這會使它們更有效地管理其它公司或個人的風險。因此，作為業務過程的一環、風險管理會為保險業創造競爭優勢。我們的研究結果，得到資源基礎理論及動態能力理論提供之理論見解所支持；而且，我們的模型從附驗證輻合及驗證區別效度的截止值。

據我們所知，本研究為首個研究、去探討保險公司的風險管理措施如何為它們創造競爭優勢。

This paper aims to figure out the relationship between energy consumption flow from a new perspective of embodied energy inventory index (EEII) and regional economic growth.

The input-output approach has been applied to calculate embodied energy inventory (EEI) and EEII using the data of 25 economies. Meanwhile, cluster analysis and panel data modeling were applied to carry out detailed research.

The results of cluster analysis show that there is a roughly negative relationship between EEII and gross domestic product (GDP) per capita, although there are some exceptions, such as Russia and Taiwan (Province of China). Panel data model results provide further evidence that there is a negative relationship between EEII and GDP per capita. Population is an important productive factor in the regional economic development. The study showed a positive relationship between EEII and population. Therefore, energy consumption flow is closely related to regional economic development.

The value of this paper is to use EEI and EEII to comprehensively clarify the energy consumption flow. The advantage of EEII is that it can reflect the energy embodied in fixed assets and infrastructure.

The role of energy or emission intensive firms face contradictory demands from advancing economic development and environmental improvement and protection and thus require appropriate policy interventions to balance the two needs. China's “Green Credit” policy that restricts loans to energy or emission intensive firms provides an example to study the impact of these kinds of policy intervention.

Using the data of all A-share listed companies in Shanghai and Shenzhen stock exchanges, our paper empirically analyzes the impact of the Green Credit Policy on performance of these energy or emission intensive firms.

(1) Using difference-in-difference (DID) and propensity score matching (PSM)-DID method and the dynamic effect method, we found that from 2012 to 2015, the Green Credit Policy had an inhibiting effect on the performance of energy or emission intensive firms. This inhibiting effect was gradually weakened in 2016, and it turned into a positive promoting effect in 2017; (2) The performance's change of these firms around 2015 showed that Green Credit promoted the green transformation and upgrading of these firms; (3) Loans were helpful to the performance of energy or emission intensive firms to some extent, but government subsidies were not significant.

The results suggest that the government, banks and other institutions should dynamically assess the implementation results of the Green Credit Policy on energy or emission intensive firms.