Search results

Value cocreation has become an important way to enhance the brand equity of a tourism destination. Different from common tourism contexts, agritourism has strong participatory and productive characteristics and is regarded as a critical platform of value cocreation. Therefore, this paper aims to explore the relationship between agritourism experience value cocreation and brand equity of rural tourism destinations from the perspective of tourists.

A questionnaire survey was conducted, and 602 valid questionnaires were collected by a random sample in 2021. Structural equation modeling was used to empirically analyze the data.

The results revealed that tourists’ participation, interaction and citizenship behaviors play a critical role in brand equity of rural tourism destinations. Meanwhile, tourists’ interaction and citizenship behaviors influenced brand equity of rural tourism destinations, via hedonic enjoyment and eudaimonia experience, and perceived experience value. Tourists’ participation behavior influenced brand equity of rural tourism destinations via hedonic enjoyment experience and perceived experience value.

This study focusing on agritourism as a critical platform of value cocreation explores the impact of agritourism experience value cocreation on brand equity of rural tourism destinations from the perspective of tourists. It enriches the existing literature on the relationship between value cocreation and brand equity of tourism destination, expands the research on value cocreation and happiness experience and also provides management basis for promoting brand equity of rural tourism destinations.

价值共创已成为提升旅游目的地品牌资产的重要途径。与一般的旅游情境不同, 农业旅游具有强烈的参与性和生产性特征, 被视为价值共创的重要平台。因此, 本文基于游 客视角探讨了农业旅游体验价值共创与乡村旅游目的地品牌资产之间的内在关系。

本文于2021 年实施问卷调查, 随机抽取602 份有效问卷。结构方程模 型用于实证分析数据。

游客参与、互动和公民行为对乡村旅游目的地品牌资产具有关键作用。同时, 游客互动和公民行为通过享乐型和实现型体验以及感知体验价值影响乡村旅游目的地品牌 资产。游客参与行为通过享乐型体验和感知体验价值影响乡村旅游目的地品牌资产。

本研究将农业旅游作为价值共创的重要平台, 基于游客视角探讨了农业旅游 体验价值共创对乡村旅游目的地品牌资产的影响, 丰富了价值共创与旅游目的地品牌资产 关系的文献, 拓展了价值共创与快乐体验的研究, 为促进乡村旅游目的地品牌资产提供了 管理依据。

La cocreación se ha convertido en una forma importante de mejorar el valor de marca de un destino turístico. A diferencia de los entornos turísticos comunes, el agroturismo tiene fuertes características participativas y productivas, y se considera una plataforma indispensable de cocreación de valor. Este artículo explora la relación entre la cocreación de valor de la experiencia de agroturismo y el valor de marca de los destinos de turismo rural desde la perspectiva de los turistas.

Se realizó una encuesta y se recogieron 602 cuestionarios válidos mediante un muestreo aleatorioa en 2021. Se utilizó un modelo de ecuaciones estructurales para analizar empíricamente los datos.

Los resultados revelaron que la participación e interacción de los turistas y los comportamientos de la ciudadanía juegan un papel crítico en el valor de marca de destinos de turismo rural. La interacción de los turistas y los comportamientos de la ciudadanía impactaron el valor de marca de destinos de turismo rural a través del disfrute hedónico, la experiencia eudaimonia y el valor percibido de la experiencia. El comportamiento de participación de los turistas influyó en el valor de marca de los destinos de turismo rural a través de la experiencia hedónica de disfrute y el valor percibido de la experiencia.

Este estudio, centrado en el agroturismo como plataforma importante para la cocreación de valor, explora el impacto de la cocreación de valor de la experiencia de agroturismo en el valor de marca de destinos de turismo rural desde la perspectiva de los turistas. Enriquece la literatura existente sobre la relación entre la cocreación de valor y el valor de marca de los destinos turisticos, expande la investigación sobre la cocreación de valor y la experiencia de felicidad, y ofrece también bases de gestión para promover el valor de marca de destinos de turismo rural.

This study examines how informal business networks achieve marketing goals in socially uncertain contexts. Drawing from multiple historical sources, Shangbangs, a type of business network that thrived in pre-1949 China, are analyzed.

The Critical Historical Research Method (CHRM) undergirds a study of Shangbangs’ historicity (i.e. their socio-historically embedded multiplicity, including organizational forms, activities and connotations.

As informal regional, professional, project-based, special-product-based or mixed marketing networks, Shangbangs relied on “flexible specialization” and coupled multiple business needs to market goods and services, business organizations, specific social values and, when necessary, to debrand business rivals.

This analysis extends theories about marketing networks by probing their subtypes, diverse marketing activities, multipronged channels and relationship building with social entities (including underground societies, business associations and guilds) in response to pre-1949 China’s market uncertainties. Substantiating an alternative approach to “flexible specialization” and marketing innovations within the pre-1949 Chinese economy shows how a parallel theoretical framework can complement western-based marketing theories.

This first comprehensive analysis of Shangbangs, an innovative historical Chinese marketing network outside the conventional market-corporate dichotomy, can inform theory building for marketing strategy-making and management conditioned by social contexts.

The author proposed a friction plunge micro-welding (FPMW) method and applied it to column grid array packaging to realize the connection of copper columns without precision molds assisted positioning. The purpose of this paper is to study the flow behavior of the solder undergoing frictional thermo-mechanical action during the FPMW and to determine the source of the solders in the micro-zones with different microstructure characteristics near the solder/Cu column friction interface.

Three kinds of Sn58Bi/SAC305 and SAC305/Pb90Sn composite solder samples were designed to study the flow behavior of the solder during FPMW using Bi and Pb as tracer elements.

The results show that most of the solders in the position occupied by the copper column was softened and plasticized during the welding process and was extruded to side of the copper column, flowing axially, circumferentially and radially along a trajectory similar to a conical spiral line. Under the drive of the tangential friction force and the radial hold-tight force, the extruded out visco-plastic solders fully mixed with the visco-plastic solders on the sides of the copper column, and bonded with the solders that deformed plastically on the periphery, so that a stir zone and a dynamic recrystallization zone finally evolved. The outside plastically deformed solders evolved into a thermo-mechanical affected zone.

The flow behavior of the solder during the FPMW was determined, as well as the source of the solders in micro-zones with different microstructure characteristics.

This research unfolds a holistic association between economic policy uncertainty (EPU) and three important markets (oil, stock and gold) in the Indian context. To do same, the current study uses the monthly dataset of each variable spanning from November 2005 to March 2022.

The authors have portrayed the wavelet-based coherence, correlation and covariance plots to explore the interaction between EPU and markets' behavior. Then, a wavelet-based quantile on quantile regression model and wavelet-based Granger causality has been applied to examine the cause-and-effect relation and causality between the EPU and markets.

The authors’ findings report that the Indian crude oil buyers do not need to consider Indian EPU while negotiating the oil deals in the short term and medium term. However, in case of the long-term persistence of uncertainty, it becomes difficult for a buyer to negotiate oil deals at cheap rates. EPU causes unfavorable fluctuation in the stock market because macroeconomic decisions have a substantial impact on it. The authors have also found that gold is a gauge for economic imbalances and an accurate observer of inflation resulting from uncertainty, showing a safe haven attribute.

The authors’ work is original in two aspects. First, their study solely focused on the Indian economy to investigate the impact and causal power of Indian EPU on three major components of the Indian economy: oil, stock and gold. Second, they will provide their findings after analyzing data at a very microlevel using a wavelet-based quantile on quantile and wavelet-based Granger causality.

Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.

The swivel construction method is a specially designed process used to build bridges that cross rivers, valleys, railroads and other obstacles. To carry out this construction method safely, real-time monitoring of the bridge rotation process is required to ensure a smooth swivel operation without collisions. However, the traditional means of monitoring using Electronic Total Station tools cannot realize real-time monitoring, and monitoring using motion sensors or GPS is cumbersome to use.

This study proposes a monitoring method based on a series of computer vision (CV) technologies, which can monitor the rotation angle, velocity and inclination angle of the swivel construction in real-time. First, three proposed CV algorithms was developed in a laboratory environment. The experimental tests were carried out on a bridge scale model to select the outperformed algorithms for rotation, velocity and inclination monitor, respectively, as the final monitoring method in proposed method. Then, the selected method was implemented to monitor an actual bridge during its swivel construction to verify the applicability.

In the laboratory study, the monitoring data measured with the selected monitoring algorithms was compared with those measured by an Electronic Total Station and the errors in terms of rotation angle, velocity and inclination angle, were 0.040%, 0.040%, and −0.454%, respectively, thus validating the accuracy of the proposed method. In the pilot actual application, the method was shown to be feasible in a real construction application.

In a well-controlled laboratory the optimal algorithms for bridge swivel construction are identified and in an actual project the proposed method is verified. The proposed CV method is complementary to the use of Electronic Total Station tools, motion sensors, and GPS for safety monitoring of swivel construction of bridges. It also contributes to being a possible approach without data-driven model training. Its principal advantages are that it both provides real-time monitoring and is easy to deploy in real construction applications.

Legged walking robots have numerous advantages over the wheel or tracked robots due to their strong operational ability and exposure to the complex environment. This paper aims to present details about the mechanical formation and a new conceptual elliptical trajectory generation discussed throughout the paper of the quadruped robot.

Initially, a realistic CAD model of the four-legged robot is developed in Solidwork-2019. The proposed model’s forward and inverse kinematics equations are deduced using Denavit–Hartenberg parameters. Based on geometry and kinematics, manipulability and obstacle avoidance are investigated. A method of galloping trajectory is proposed for aiming the increase of upright direction impulse, which is produced by ground reaction force at each step frequency. Furthermore, the locomotion equation of the ellipse trajectory is derived by setting transition angle polynomial of free-fall phase, stance phase and swing phase and the constraints.

Finally, a successive simulation on a 2D sagittal plane is performed to check and verify the usefulness of the proposed trajectory. Before the development of the full quadruped, a single prototype leg is generated for experimental verification of the dynamic simulations.

The proposed trajectory is novel in that it uses force tracking control, which is intended to improve the quadruped robot’s robustness and stability.

The effect of different service parameters on the current-carrying tribological properties of CF-Al₂O₃/Cu composites was investigated, and the damage behavior of the composites under different service parameters was probed. The purpose of this study is to provide a theoretical basis for the application of CF-Al₂O₃/Cu composites.

The composites were fabricated by internal oxidation combined with powder metallurgy. The current-carrying tribological properties of CF-Al₂O₃/Cu composites were investigated on an electrical damage test system at different loads and currents.

As the load increases, the wear mechanism of the composite changes from abrasive wear to delamination wear. As the current increases, the oxidation wear and arc erosion of the composites gradually intensified. Under the service parameters of 0–25 A and 30–40 N, the composite has relatively stable current-carrying tribological properties.

This paper could provide a theoretical basis for the practical application of CF-Al₂O₃/Cu composites.

The urgency to address climate change and its devastating consequences has never been more pressing. As societies become increasingly aware of the detrimental impact of traditional housing on the planet, there is a growing demand for eco-friendly housing solutions that prioritize energy efficiency, resource conservation and reduced carbon emissions. Therefore, this study aims to investigate the factors that influence customers’ priority toward eco-friendly house purchasing intention.

This study collected 386 data using a quantitative research strategy and purposive sampling method. This study uses a hybrid analysis technique using partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) approaches to identify the influencing factors.

The PLS-SEM analysis found that attitude toward the eco-friendly house, subjective norms, performance expectancy, environmental knowledge and environmental sensitivity have a positive influence on eco-friendly house purchasing intention. However, perceived behavioral control and willingness to pay were found to have insignificant effect on customers’ intention to purchase eco-friendly houses. The fsQCA results further revealed complex causal relationships between the influencing factors.

This research will not only contribute to academic knowledge but also provide practical guidance to real estate developers, policymakers and individuals looking to make environmentally responsible choices. By understanding the factors that influence consumers’ intentions to purchase eco-friendly houses, we can pave the way for a more sustainable and resilient future.

This study has used a hybrid analysis technique, combining PLS-SEM and fsQCA, to enhance the predictive accuracy of eco-friendly house purchase intentions among individuals residing in densely populated and highly polluted developing countries, such as Bangladesh.