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Given that existing retail brand research tends to treat each level of a retail brand as a separate concept, this paper aims to unveil the holistic nature of a multi-level retail brand, considering the distinctiveness of each level and the interrelationships between the images of different levels.

This study uses a scoping review approach that includes 478 retail brand articles. Subsequently, a thematic analysis method is applied.

The brand attributes that shape the distinct image of each retail brand level encompass diverse intrinsic and extrinsic attributes. Moreover, the holistic nature of a multi-level retail brand is formed by the interrelationships between the images of different levels, which are reflected in the presence of common extrinsic attributes and their interplay at attribute, benefit and attitude levels.

Theoretically, this review provides conceptual clarity by unveiling the multi-level yet holistic nature of a retail brand, helping researchers refine and extend existing theories in retail branding, while also providing new research opportunities in this field. Practically, the findings could guide retailers in implementing differentiated branding strategies at each level while achieving synergy across all levels.

This paper aims to explore the impact of the origin of hops on the sensory and hedonic evaluation of highly involved craft beer consumers.

Data was collected through a between-subject tasting experiment, where the origin of hop was manipulated (imported vs locally grown). The craft beer samples used in the experiment were produced using hops of similar age but grown in two distinct places: USA (imported hop) and in the city of Ribeirão Preto, Brazil, where the experiment was conducted (locally grown hop). The sensory and hedonic evaluations of highly involved craft beer consumers (n = 100) were collected after tasting the samples.

The origin of hop proved to be significant in affecting participants’ sensory and hedonic evaluations. It was observed that women were more sensitive than men to the origin information: when information was given, differences were found only on men’s scores of dryness/astringency; while in women, significant differences were found not only in dryness/astringency, but also in bitterness and refreshing, which are important attributes in the sensory profile of craft beer. It was also confirmed the effect of localness in hop cultivation, once men’ and women’s scores on liking were higher for the sample brewed with locally grown hop.

To the best of the authors’ knowledge, this is the first work using craft beer brewed with hops cultivated in Brazil and a sample of Brazilian craft beer consumers, therefore, providing a significant contribution to the field of consumer behavior. Furthermore, it adds to the discussion on sex-/gender-related differences regarding sensory expectation and perception of foods.

Holy cities in India are seeing tremendous gentrification. This study aims to investigate the effect of the changing lifestyle of people towards spirituality and the changing lifestyle's impact on consumer buying behavior on properties in Indian holy cities which has not been studied anecdotally.

The research is exploratory in nature. A questionnaire has been sent to collect primary data through SurveyMonkey. Simple random sampling was used to collect a sample of 450 respondents which was also verified using G* software. The data were analyzed using descriptive statistics and partial least square–structured equation modeling (PLS-SEM).

Findings obtained through the structural model using bootstrapping technique suggest that intrinsic and extrinsic factors are attracting tourists leading to an increase in the demand for real estate in holy cities.

The research findings may vary as per the cultural differences and belief in spirituality, which is subject to perceptual biases in different holy cities.

The traditional determinants of property buying behavior are considered inadequate to attract real estate investments. The inclusion of these behavioral aspects – intrinsic and extrinsic factors may improve the investment inflows in India.

Spirituality connects to the concept of behavioral real estate, where the decision to buy property is largely affected by the emotional attachment of people.

This research adds value to fill the gap by finding out the latent determinant – emotional reasons impacting transnational gentrification in India.

Wine tourism is gaining increasing popularity among Chinese tourists, making it necessary to thoroughly examine tourist behavior. While online reviews posted by wine tourists have been extensively studied from the perspectives of destinations and wineries, the perspective of the tourists themselves has been overlooked. To address this gap, this study aims to identify significant attributes intrinsic to the tourism experiences of Chinese wine tourists by adopting a text-mining approach from a tourist-centric perspective.

The authors use topic modeling to extract these attributes, calculate topic intensity to understand tourists’ attention distribution across these attributes and conduct topical sentiment analysis to evaluate tourists’ satisfaction levels with each attribute. The authors perform importance-performance analyses (IPAs) using topic intensity and sentiment scores. Furthermore, the authors conduct semistructured in-depth interviews with Chinese wine tourists to gain insights into the underlying reasons behind the key findings.

The study identifies eleven attributes for domestic wine tourists and seven attributes for outbound wine tourists. From the reviews of both domestic and outbound tourists, three common attributes have been identified: “scenic view”, “wine tasting and purchase” and “wine knowledge”.

According to the results of the IPAs, there is a pressing need for enhancements in the wine tasting and purchasing experience at domestic wine attractions. Additionally, managers of domestic wine attractions should continue to prioritize the positive aspects of the family trip experience and scenic views. On the other hand, for outbound wine attractions, it is crucial for managers to maintain their efforts in providing opportunities for wine knowledge acquisition, ensuring scenic views and upholding the reputation of wine regions.

First, this study breaks new ground by adopting a tourist-centric perspective to extract significant attributes from real wine tourism reviews. Second, the authors conduct a comparative analysis between Chinese wine tourists who travel domestically and those who travel abroad. The third novel aspect of this study is the application of IPA based on textual review data in the context of wine tourism. Fourth, by integrating topic modeling with qualitative interviews, the authors use a mixed-method approach to gain deeper insights into the experiences of Chinese wine tourists.

Doctoral degrees are generally the highest level of education provided by educational institutions in Western countries. Nevertheless, doctoral degree holders – i.e. Philosophiae Doctors (PhDs) – struggle to find a job that matches their knowledge and expertise. This article investigates the effects that PhDs' satisfaction with different attributes of educational services has on their ability to obtain employment either in academia or outside it.

Secondary data were accessed from a nationwide survey performed in Italy between February and July 2014. More than 16,000 people who achieved a doctoral degree between January 2008 and December 2010 were involved in the analysis. The four-years' time-span was justified by the need to avoid potential biases produced by a short time lapse between data collection and the awarding of the respondents' doctoral degree. A logistic regression model was designed to shed light on the relationship between doctoral degree holders' satisfaction and their ability to find employment.

This study results suggested that the attributes of educational services had varying effects on the doctoral degree holders' ability to obtain work. More specifically, the perceived quality of research and methodological courses delivered by educational institutions and the quality of the technologies and digital resources available at the host university were found to positively affect the ability of doctoral degree holders to get a job in academia. Conversely, the satisfaction with the quality of the teaching activities was positively related to the doctoral degree holders' employability outside academia.

The quality of educational services provided to students attending a doctoral degree course affects their ability to find work. Enhancing the quality of educational services may reduce the risk of unemployment amongst doctoral degree holders.

To the best of the authors' knowledge, few attempts have been made to investigate the interplay between the quality of educational services and doctoral degree holders' employability.

A visual sweetness scale with an arrow pointing to a specific sweetness level is now required on all labels of AOC Alsace. The sweetness scale makes it easier for consumers to understand what is in the bottle. What is less clear, however, is whether such labeling is always effective. To fill this gap, the current research paper aims to examine the positive and negative effects (double-edged effects) of a visual sweetness scale and identify the boundary condition.

Two studies were conducted using a 2 (cue type: scale vs text) by 2 (consumer type: novices vs experienced wine consumers) between-subjects, quasi-experimental design.

The double-edged effects are only significant among wine novices. Specifically, though wine novices are more likely to purchase wine with a sweetness scale (vs text) due to perceived diagnosticity (Study 1), they are unwilling to pay more due to low perceived quality (Study 2).

The study findings provide practical implications for wine producers, marketers and restaurants regarding when and how to use the sweetness scale on wine labels and wine service.

To the best of the authors’ knowledge, this research is the first to reveal the impact of visualizing wine style on wine labels. More importantly, while most previous research demonstrates the positive effects of using visual cues, this research sheds light on its drawbacks and examines the underlying mechanisms.

In recent years, the global consumption of craft beer witnesses remarkable growth. This growth is attributed to the evolving demographics of beer consumers, particularly the emergence of a new generation known as Digitarians or Generation Z. This study aims to analyze the key determinants influencing craft beer consumption among Digitarians.

An online questionnaire is administered, and a total of 296 completed responses are included in the statistical analysis. The methodology uses logistic regressions combined with a backward selection process and variance inflation factor analysis to address multicollinearity. The logistic regressions are conducted in three steps to delve into the research objective and gain insights into the behavior of young consumers. The stepwise backward selection aids in obtaining robust coefficients as a variable selection tool.

The results shed light on how Digitarians’ preferences for craft beer are influenced by various factors, including self-perceived knowledge, alcohol content, gender, food pairings, environment and companionship.

To the best of the authors’ knowledge, this paper contributes novel insights by being the first study to explore the significance of craft beer choices among Digitarians, identifying the role of several predictors in their consumption patterns.

This study aims to provide insights into wine consumers in Hong Kong and Mainland China, and the diversity of their behavior, by investigating their motivations, consumption and purchasing behavior and segmenting the sample based on wine knowledge and frequency of consumption to identify three distinct clusters that are then profiled.

Data was collected through an online survey of wine consumers of ethnic Chinese origin residing in Mainland China and Hong Kong, using two methods of recruitment (a convenience sample from wine-related databases, a panel survey undertaken by an international market research firm). The final sample comprised 477 respondents, about equally divided among Mainland Chinese and Hong Kong wine consumers. Analysis of the data using the Statistical Package for Social Sciences for Windows (SPSS) 29 included a series of descriptive analyses, followed by a two-step cluster analysis using an Euclidean distance method.

Wine knowledge and frequency of wine consumption were relatively higher within the sample as a whole than previous studies, but three distinct consumer segments are evident. There is evidence of a democratization of wine consumption, and a greater focus on wine consumption for enjoyment in relaxed and informal settings. rather than consumption driven by health and status, occurring primarily in commercial or business settings. The dominance of red wine in this market is also declining, and intrinsic cues – specifically, prior experience of the wine – are becoming important in wine purchase decisions.

This study uses a broad sample of wine consumers to identify trends in wine consumption patterns and motivations, and purchase decision-making behavior, of Mainland Chinese and Hong Kong wine consumers. The identification of three clusters of wine consumers offers both points of comparison with previous segmentation research globally and within China, whilst also identifying scope for further research.

Project scheduling plays an essential role in the implementation of a project due to the limitation of resources in practical projects. However, the existing research tend to focus on finding suitable algorithms to solve various scheduling problems and fail to find the potential scheduling rules in these optimal or near-optimal solutions, that is, the possible intrinsic relationships between attributes related to the scheduling of activity sequences. Data mining (DM) is used to analyze and interpret data to obtain valuable information stored in large-scale data. The goal of this paper is to use DM to discover scheduling concepts and obtain a set of rules that approximate effective solutions to resource-constrained project scheduling problems. These rules do not require any search and simulation, which have extremely low time complexity and support real-time decision-making to improve planning/scheduling.

The resource-constrained project scheduling problem can be described as scheduling a group of interrelated activities to optimize the project completion time and other objectives while satisfying the activity priority relationship and resource constraints. This paper proposes a new approach to solve the resource-constrained project scheduling problem by combining DM technology and the genetic algorithm (GA). More specifically, the GA is used to generate various optimal project scheduling schemes, after that C4.5 decision tree (DT) is adopted to obtain valuable knowledge from these schemes for further predicting and solving new scheduling problems.

In this study, the authors use GA and DM technology to analyze and extract knowledge from a large number of scheduling schemes, and determine the scheduling rule set to minimize the completion time. In order to verify the application effect of the proposed DT classification model, the J30, J60 and J120 datasets in PSPLIB are used to test the validity of the scheduling rules. The results show that DT can readily duplicate the excellent performance of GA for scheduling problems of different scales. In addition, the DT prediction model developed in this study is applied to a high-rise residential project consisting of 117 activities. The results show that compared with the completion time obtained by GA, the DT model can realize rapid adjustment of project scheduling problem to deal with the dynamic environment interference. In a word, the data-based approach is feasible, practical and effective. It not only captures the knowledge contained in the known optimal scheduling schemes, but also helps to provide a flexible scheduling decision-making approach for project implementation.

This paper proposes a novel knowledge-based project scheduling approach. In previous studies, intelligent optimization algorithm is often used to solve the project scheduling problem. However, although these intelligent optimization algorithms can generate a set of effective solutions for problem instances, they are unable to explain the process of decision-making, nor can they identify the characteristics of good scheduling decisions generated by the optimization process. Moreover, their calculation is slow and complex, which is not suitable for planning and scheduling complex projects. In this study, the set of effective solutions of problem instances is taken as the training dataset of DM algorithm, and the extracted scheduling rules can provide the prediction and solution of new scheduling problems. The proposed method focuses on identifying the key parameters of a specific dynamic scheduling environment, which can not only reproduces the scheduling performance of the original algorithm well, but also has the ability to make decisions quickly under the dynamic interference construction scenario. It is helpful for project managers to implement quick decisions in response to construction emergencies, which is of great practical significance for improving the flexibility and efficiency of construction projects.

This study aims to examine the impact of autonomous vehicles adoption motivations (i.e. technological, ecological and intrinsic motivation) on tourists’ pro-environmental behavior and verify the mediating role of tourists’ green self-image between the relationship of eco-friendly attitudes and autonomous vehicles adoption motivations.

The data from 586 national and international tourists were analyzed using the partial least squares method.

The findings revealed that eco-friendly attitude is a significant predictor of tourists’ green self-image; tourists’ green self-image is a significant predictor of autonomous vehicles adoption motivations; and autonomous vehicles adoption motivations are significant predictors of tourists’ pro-environmental behavior. In addition, tourists’ green self-image mediated the relationship between eco-friendly attitudes and autonomous vehicles adoption motivations.

These outcomes provide valuable guidance for the future development of green destination tourism and allow interesting implications for the tourism industry and autonomous vehicles adoption.

本研究探讨自动驾驶汽车采纳动机（即技术、生态和内在动机）对游客环保行为的影响, 并验证游客绿色自我形象在环保态度和自动驾驶汽车采纳动机之间的中介作用。

收集586份来自中国国内外游客的数据, 采用偏最小二乘法进行分析。

研究结果表明, 环保态度显著影响游客绿色自我形象, 进而影响自动驾驶汽车采纳动机, 带来游客的环保行为。此外, 游客的绿色自我形象在环保态度与自动驾驶汽车采纳动机之间起到中介作用。

本研究提出了游客绿色自我形象的概念, 将游客与环保人士的日常行为进行区分。研究结果为绿色目的地旅游业的未来发展提供了方向, 对旅游业和自动驾驶汽车的采纳产生影响。

Este estudio tiene como objetivo examinar el impacto de las motivaciones para la adopción de vehículos autónomos (es decir, motivaciones tecnológicas, ecológicas e intrínsecas) en el comportamiento proambiental de los turistas y verificar el papel mediador de la autoimagen ecológica de los turistas en la relación entre las actitudes ecológicas. y las motivaciones para la adopción de vehículos autónomos.

Se analizaron los datos de 586 turistas nacionales e internacionales mediante el método de mínimos cuadrados parciales.

Los hallazgos revelaron que la actitud ecológica es un predictor importante de la autoimagen ecológica de los turistas; la autoimagen ecológica de los turistas es un predictor importante de las motivaciones para la adopción de vehículos autónomos; y las motivaciones para la adopción de vehículos autónomos son predictores importantes del comportamiento proambiental de los turistas. Además, la autoimagen ecológica de los turistas medió la relación entre las actitudes ecológicas y las motivaciones para la adopción de vehículos autónomos.

Estos resultados proporcionan una orientación valiosa para el desarrollo futuro del turismo de destino ecológico y permiten implicaciones interesantes para la industria turística y la adopción de vehículos autónomos.