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This study aims to conduct an empirical investigation of differing perceptions of nine types of urban space and nine visual elements among tourists in destination using a computer vision (CV) approach.

The data for this study was extracted from YFCC 100 M dataset. Nine types of urban space in Beijing were initially identified using a scene recognition model. Subsequently, a semantic segmentation model was applied, which yielded substantial evidence relating to nine visual elements that were used to elicit differing perceptions among tourists from different continents.

Tourists from three continents had different perceptions about corridors, old buildings, overlooks and traffic spaces, reflecting their cultural convention. Asians, Europeans and North Americans diversely gazed at the landscape element of buildings, foliage, sky and people in urban space. All those provided evidence to contribute to the tourist gaze theory's construction.

This study firstly depicted how tourists perceive the tourism symbol of urban space. The novel approach of employing two CV models offer methodological insights to tourism research relevant to visual perception.

游客对城市空间的感知:计算机视觉途径

本研究采用计算机视觉方法, 探究游客对旅游目的地九种城市空间类型及九种视觉元素的感知差异。

本研究数据提取自YFCC 100M图片数据集。首先, 利用场景识别模型识别了游客图片中的九种城市空间类型。其次, 应用语义分割模型识别了游客图片的九个视觉元素。这些分析结果被用于探究不同大洲游客的视觉感知差异。

来自不同大洲的游客对城市空间有不同的感知偏好。亚洲人更喜欢拍摄自己与著名的城市建筑, 欧洲人和北美人更喜欢自然元素, 如水、树叶和天空。不同大洲游客对视觉元素的偏好佐证了旅游凝视理论。

本研究选取了独特的城市空间为研究对象, 来验证游客凝视理论。此外, 两种计算机视觉模型为旅游研究提供了新的方法论视角。

La percepción de los turistas del espacio urbano: Un enfoque de vision artificial

Resumen

Los datos para este estudio se extrajeron del conjunto de datos YFCC 100 M. Inicialmente se identificaron nueve tipos de espacio urbano en Pekín mediante un modelo de reconocimiento de escenas. Posteriormente, se aplicó un modelo de segmentación semántica, que aportó pruebas sustanciales en relación con nueve elementos visuales que se utilizaron para suscitar percepciones diferentes entre turistas de distintos continentes.

El objetivo de este estudio es llevar a cabo una investigación empírica sobre las diferentes percepciones de nueve tipos de espacio urbano y nueve elementos visuales entre los turistas en destino, utilizando un enfoque de visión artificial (CV).

Los turistas de tres continentes tenían percepciones diferentes sobre los pasillos, los edificios antiguos, los miradores y los espacios de tráfico, lo que refleja su convención cultural. Los asiáticos, los europeos y los norteamericanos observaron de forma diversa el elemento paisajístico de los edificios, el follaje, el cielo y las personas en el espacio urbano. Todos ellos aportaron pruebas para contribuir a la construcción de la teoría de la mirada turística.

Este estudio describe por primera vez cómo los turistas perciben el símbolo turístico del espacio urbano. El novedoso enfoque de emplear dos modelos de vision artificial ofrece conocimientos metodológicos para la investigación del turismo relacionados con la percepción visual.

This study aims to examine the roles of face consciousness, materialism and emotions play in sustainable luxury brand consumption (SLBC) among Millennials in a Collective society.

Three experimental design studies using scenario-based methodologies along with the survey method were conducted in China to test the proposed research model.

Study 1 shows that face consciousness negatively and significantly affects SLBC, and this effect is mediated by materialism. Study 2 reveals that when Millennials experienced great authentic pride, there is a positive association between face consciousness and SLBC. Furthermore, Study 3 reveals that when Millennials are exposed to a high risk of embarrassment, materialists’ willingness to engage in SLBC increases.

The current research has significant theoretical implications for studying SLBC, especially among young consumers. This study contributes to a better understanding of the relationships among face consciousness, materialism, pride, risk of embarrassment and SLBC in a Collective culture context, where luxury consumption is valued.

Sustainable luxury consumption is a new and under-examined research area. This research extends the SLBC literature in the context of a collective society and provides empirical evidence for sustainable consumption and luxury consumption in general. The research also contributes to the literature by examining the moderating role of self-conscious emotion in the relationship between face consciousness and SLBC.

This paper takes Chinese A-share listed companies from 2007 to 2021 as research samples to investigate the influence of supplier concentration on debt maturity structure and its mechanism. It further analyzes whether the relationship between the two is different in the case of different monetary policies, collateral assets, and total debt. The research conclusion is of practical significance for enterprises to construct a balanced debt maturity structure and prevent financial risks.

This paper adopts the empirical research method. The data came from the CSMAR database, which eliminated ST and *ST and companies with missing data, resulting in a sample of 20,328. Stata16 was used for statistical analysis.

There is an inverted U-shaped relationship between supplier concentration and debt maturity structure, and market position and trade credit play an intermediary role. In the case of tight monetary policy, fewer collateral assets, and higher total debt, the inverse U-shaped relationship is more significant.

This paper examines the relationship between supplier concentration and debt maturity structure from a non-linear perspective for the first time, providing theoretical support for enterprises to form a reasonable debt structure, and deepening the theoretical cognition of the relationship between supplier concentration and corporate debt maturity structure.

The purpose of this paper is to contribute to the extant literature about the co-evolvement of Business Process Management (BPM) and the Internet of Things (IoT) by proposing the IoT-enabled Context-aware BPM (IoT-CaBPM) framework to bridge from the IoT infrastructure to context-aware business processes.

Motivated by the “Three Waves” of BPM research, IoT-enabled context-awareness is, therefore, expected to be achieved for enhancing the business process design, which pilots a new wave of BPR (Business Process Redesign/Reengineering) to enable the business process coevolve with IoT and analytics. This paper reports an illustrative case study of BPR in a Chinese bulk port, one of the hub seaports that widely adopted IoT technologies over the last few years.

The IoT implementation and data analytics has increased the efficiency and improve the monitoring effectively. The proposed IoT-CaBPM framework availably helps to identify and match nodes of IoT devices, business decisions and analytic models in order to redesign a business process towards context-aware variability. As IoT is rapidly becoming the new dominant IT paradigm is moving towards mature implementation in various industries, the corresponding BPR must be planned and executed strategically for achieving better benefits.

Despite some research extend BPM standard by integrating IoT devices as a sort of resources or report generically that the ports operations are affected by IoT, there is still a lack of layers from the IoT infrastructure to context-aware business processes. An industrial BPR case with business models in detail is also a lack for presenting the specific implications and effectiveness of the adoption of such technologies. This paper fills in this gap.

This paper aims to examine the effects of hotel general managers’ transformational leadership (TLS) and department managers (DMs)’ organizational commitment (OC) on their department’s performance in upscale hotels in Australia.

Data were collected by surveying DMs in four- and five-star hotels. The survey instrument included measures of comprehensive sustainable performance, TLS and OC adapted from the literature. The data were analyzed through factor analysis and regression with a resampling method of bootstrapping.

The findings indicated that TLS influenced hotel departments’ non-financial as well as social and environmental performance dimensions directly and indirectly through OC. However, the mediation effect of OC did not exist for financial performance.

The key theoretical contribution is the use of performance assessment based on critical success factors of hotel businesses and the bootstrapping regression model.

Senior managers should pay attention to TLS qualities when appointing core managers, provide on-going structured TLS training and concentrate on leading performance dimensions for performance assessment.

This study responds to the call for leadership research to move beyond its emphasis on individual performance and to address performance more holistically by considering its multidimensionality and the processes underlying effective performance.

Distance is the core concept in tourism. However, previous studies focused on single distance dimensions and generated contradictory findings due to omitted variable biases. This paper aims to introduce the well-established CAGE (cultural, administrative, geographical, and economic) distance framework into international tourism research to measure the comprehensive distance and explore its impact on inbound tourist satisfaction.

The comprehensive distance was calculated based on the Mahalanobis formula. Combining tourist review data from TripAdvisor, this study used ordinary least square regressions to explore the influence of the comprehensive distance on inbound tourist satisfaction and the mediating role of inbound tourist emotion.

Results show that CAGE distance effectively describes the dynamic change in distance. The comprehensive distance also positively impacts tourist satisfaction, and tourist emotion plays a mediating role in this impact.

This paper advances knowledge about distance in international tourism by introducing the CAGE distance framework and addresses the contradictory findings with specific distance dimensions by the comprehensive distance.

距离是旅游的核心概念。然而, 以前的研究集中在单一的距离维度上, 并且由于遗漏变量偏差而产生了相互矛盾的结果。 本文旨在将成熟的 CAGE 距离框架引入国际旅游研究中, 以衡量综合距离并探讨其对入境游客满意度的影响。

综合距离根据马氏距离公式计算。 结合TripAdvisor网站的游客评论数据, 采用普通最小二乘（OLS）回归分析综合距离对入境游客满意度的影响以及入境游客情绪的中介作用。

结果表明, CAGE距离有效地描述了距离的动态变化。 综合距离也正向影响游客满意度, 游客情绪在此影响中起中介作用。

本文通过引入 CAGE 距离框架来提升国际旅游中的距离知识。 本研究还通过综合距离解决了特定距离维度的矛盾发现。

La distancia es el concepto central en el turismo. Sin embargo, estudios previos se han centrado en dimensiones de una sola distancia, generando resultados contradictorios debido a los sesgos por la omisión de variables. Este trabajo tiene como objetivo introducir el marco de distancia CAGE, establecido en la investigación turística internacional, con la intención de medir la distancia integral y explorar su impacto en la satisfacción del turista receptor.

La distancia integral se calculó con base en la fórmula de Mahalanobis. Combinando los datos de reseñas turísticas de TripAdvisor, se utilizaron regresiones de mínimos cuadrados ordinarios (OLS) para explorar la influencia de la distancia integral en la satisfacción del turista receptor y el papel mediador de la emoción del turista receptor.

Los resultados muestran que el modelo CAGE describe el cambio dinámico en la distancia de una forma efectiva. La distancia integral también impacta positivamente en la satisfacción del turista, y la emoción del turista juega un papel mediador en este impacto.

Este documento avanza en el conocimiento sobre la distancia en el turismo internacional mediante la introducción del marco de distancia CAGE. Además, aborda resultados contradictorios con las dimensiones de distancia específicas mediante la distancia integral.

Innovation in fintech presents great opportunities and huge challenges for accounting practices around the world. This paper aims to examine the impact of Fintech on accounting practices including financial reporting, performance management, budgeting, auditing, risk and fraud management. Fintech is proxied by the adoption of AI and big data analysis in accounting practices.

We chose African countries as our focus countries and surveyed chartered and qualified accountants in both Ghana and Nigeria. With 201 questionnaires qualified for our final analyses, we adopted the structural equation modelling to analyse the impact of Fintech on accounting practices.

The empirical results show that the impact of AI and big data on accounting practices is positive and significant, indicating that fintech could potentially mitigate the agency problem in accounting practices and lead to better accounting practices. Interestingly, we find that, in general, the impact of AI is larger than that of big data.

Our results provide significant insights to regulators, policymakers and managers about the future development of adopting fintech in the regulation and governance framework at both macro and micro levels for accounting practice.

Destination monitoring is crucial to understand performance and identify key points of differentiation. Visitor satisfaction is an essential driver of destination performance. With the fast-growing volume of user-generated content through social media, it is now possible to tap into very large amounts of data provided by travellers as they share their experiences. Analysing these data for consumer sentiment has become attractive for destinations and companies. The idea of drawing on social media sentiment for satisfaction monitoring aligns well with the broader move towards smart destinations and real-time information processing. Thus, this paper aims to examine whether the electronic word of mouth originating from Twitter posts offers a useful source for assessing destination sentiment. Importantly, this research examines what caveats need to be considered when interpreting the findings.

This research focusses on a prominent tourist destination situated on Australia’s East Coast, the Gold Coast. Using a geographically informed filtering process, a collection of tweets posted from within the Gold Coast destination was created and analysed. Metadata were analysed to assess the population of Twitter users, and sentiment analysis, using the Valence Aware Dictionary for Sentiment Reasoning algorithm, was performed.

Twitter posts provide considerable information, including about who is visiting and what sentiment visitors and residents express when sending tweets from a destination. They also uncover some challenges, including the “noise” of Twitter data and the fact that users are not representative of the broader population, in particular for international visitors.

This paper highlights limitations such as lack of representativeness of the Twitter data, positive bias and the generic nature of many tweets. Suggestions for how to improve the analysis and value of tweets as a data source are made.

This paper contributes to understanding the value of non-traditional data sources for destination monitoring, in particular by highlighting some of the pitfalls of using information sources, such as Twitter. Further research steps have been identified, especially with a view to improving target-specific sentiment scores and the future employment of big-data approaches that involve integrating multiple data sources for destination performance monitoring.

The identification of cost-effective ways of measuring and monitoring guest satisfaction can lead to improvements in destination management. This in turn will enhance customer experience and possibly even resident satisfaction. The social benefits, especially at times of considerable visitation pressure, can be important.

The use of Twitter data for the monitoring of visitor sentiment at tourist destinations is novel, and the analysis presented here provides unique insights into the potential, but also the caveats, of developing new, smart systems for tourism.

目的地监控对理解绩效和确立区别关键点至关重要。游客满意是目的地绩效的关键动力。随着社交媒体上用户生成内容的快速增长, 研究其游客提供的大量数据变成可能, 这些数据体现了游客的旅游体验。分析这些消费者情绪的数据对目的地和有关企业的吸引力巨大。研究社交媒介情绪数据和满意度与更广泛地对智慧旅游和实时信息处理等方面的研究和谐一致。因此, 本论文旨在检验Twitter帖子中的在线口碑效应是否成为测量目的地情绪的有用数据。更重要的是, 本论文检验在研究结果中哪些领域应该着重考虑研究。

本论文集中研究了澳大利亚东海岸的一处旅游目的地, 黄金海岸。本论文使用地理信息过滤的处理方式, 有关黄金海岸的tweets为样本, 进行分析。本论文分析了元数据, 使用VADER数算, 检测了Twitter用户人口和情绪分析。

Twitter帖子提供相当多的信息, 包括谁是游客, 当游客发布有关旅游目的地的tweets的时候, 拥有什么样的情绪。研究结果还指出了一些挑战, 包括twitter数据的“杂音”, 用户并不能代表广大研究对象的事实, 特别是国际游客。

本论文强调了几点限制, 如Twitter数据的代表性、积极偏见、大多数tweets千篇一律等。本论文对如何提高分析结果和使用tweets作为数据源的价值提出了几点建议。

本论文对非传统数据以对旅游目的地监控的价值做出贡献, 尤其是强调了使用信息数据的弊端, 如Twitter。未来研究方向应该着重研究目标明确的情绪指数, 以及运用大数据分析方法, 分析多个数据源来检测旅游目的地性能。

本论文确立的经济有效的方法以衡量和监控游客满意度, 对提高目的地管理有着巨大帮助。同时, 这也可以提高游客体验和甚至提高当地居民的满意度。社会利益, 特别有的时候很大的旅游压力, 是巨大的。

The purpose of this paper is to develop a compressive sensing (CS) algorithm for noisy solder joint imagery compression and recovery. A fast gradient-based compressive sensing (FGbCS) approach is proposed based on the convex optimization. The proposed algorithm is able to improve performance in terms of peak signal noise ratio (PSNR) and computational cost.

Unlike traditional CS methods, the authors first transformed a noise solder joint image to a sparse signal by a discrete cosine transform (DCT), so that the reconstruction of noisy solder joint imagery is changed to a convex optimization problem. Then, a so-called gradient-based method is utilized for solving the problem. To improve the method efficiency, the authors assume the problem to be convex with the Lipschitz gradient through the replacement of an iteration parameter by the Lipschitz constant. Moreover, a FGbCS algorithm is proposed to recover the noisy solder joint imagery under different parameters.

Experiments reveal that the proposed algorithm can achieve better results on PNSR with fewer computational costs than classical algorithms like Orthogonal Matching Pursuit (OMP), Greedy Basis Pursuit (GBP), Subspace Pursuit (SP), Compressive Sampling Matching Pursuit (CoSaMP) and Iterative Re-weighted Least Squares (IRLS). Convergence of the proposed algorithm is with a faster rate O(k*k) instead of O(1/k).

This paper provides a novel methodology for the CS of noisy solder joint imagery, and the proposed algorithm can also be used in other imagery compression and recovery.

According to the CS theory, a sparse or compressible signal can be represented by a fewer number of bases than those required by the Nyquist theorem. The new development might provide some fundamental guidelines for noisy imagery compression and recovering.

Big science has become a new normative standard in transforming science policy with the interdisciplinary research (IDR) pattern serving as an organizational strategy in scientific inquiries. This paper aims to show how policy-making is organized in the real situation of the R&D sectors for this trend.

Cultural theory and new institutionalism are tinkered for a close examination of the ways in which IDR has been enacted and implemented in BGI Group, an exemplar of big science and leading biotechnology research facility in China, by interrogating institutional cultures in the context of big science projects, whilst investigating how IDR is evolved against the specific social process of interaction.

The findings include that the IDR has profoundly influenced how scientific knowledge is produced, the social interactions between stakeholders and the innovation of research policy within the network of China’s biotechnology industry.

Advances in biotechnology and related fields are redrafting China’s hi-tech industry development and governance landscape. This is the first empirical study of innovation in R&D management for big science project as presented by the IDR pattern in the BGI. It makes an important contribution to the understanding of both the nature of China’s biotechnology industry governance practices and the culture of scientific innovation within which the IDR mediates social interactions and thereby the policy-making process.