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Anchored in the theories of brand gestalt and stakeholder perspectives, this study aims to undertake a comprehensive examination of the brand gestalt concept, emphasizing its multidimensional nature and the process of co-creation.

Focused within the context of the Wonderful Indonesia brand, the research draws upon a rich qualitative data set derived from in-depth interviews conducted with 18 international tourists, supplemented by netnography (or internet ethnography) of websites, social media and online articles related to Wonderful Indonesia. Using grounded theory methodology, the qualitative data undergo rigorous analysis to identify emergent themes and patterns.

The research elucidates the four dimensions (4S) comprising brand gestalt: storyscapes, sensescapes, servicescapes and stakeholderscapes. Each dimension is further delineated into essential categories, providing a comprehensive understanding of brand gestalt. This study highlights the collaborative nature of brand gestalt, emphasizing the involvement of multiple stakeholders in shaping the brand's identity and perception. Consumer perceptions of co-creation are identified as significant contributors to brand gestalt, enhancing the brand's value proposition.

Destination management and practitioners can use the insights from the research to refine their brand management and marketing strategies by leveraging the dimensions of brand gestalt. Recognizing the collaborative construct of brand gestalt can guide businesses in fostering meaningful relationships with stakeholders and aligning branding efforts with collective visions. Understanding the role of consumer co-creation in brand development can inform strategies aimed at enhancing brand equity and fostering consumer loyalty.

This study extends existing literature on brand gestalt by providing a comprehensive examination of its four dimensions and essential categories. By emphasizing the collaborative nature of brand gestalt, this study contributes to advancing the understanding of brand co-creation paradigms. The identification of consumer perceptions of co-creation as a significant factor in brand gestalt adds novel insights to the literature, offering valuable implications for brand management and marketing strategies.

From a supply chain perspective, logistics firms collaborate with other supply chain members to extend their business scope. Investment in circular economy projects in the supply chain can not only broaden the scope of business but also increase the value of the entire supply chain. Third-party logistics companies are gradually participating in the construction and operation of many circular economy projects. How to coordinate multiple circular economy supply chain projects is at the core of its operation.

This paper first analyzes some typical supply chain projects in China and summarizes the main features of these projects. Secondly, considering the benefits of the project and the stakes of each project, a multi-stage stochastic programming model is established. Finally, Cplex, nested decomposition, LocalSolver and other methods are adopted to simulate and analyze the model.

The final experimental results find that the importance of coordinating multiple circular economy supply chain projects to increase the value of the entire supply chain. The multi-stage stochastic programming model presented in this research can provide a useful tool for logistics enterprises and third-party logistics companies to optimize their investment decisions and maximize their profits in the context of a circular economy.

There are still some limitations to this study; for example, it is limited to the analysis of circular economy supply chain projects in China. The study focused on third-party logistics companies, and other enterprises in the circular economy supply chain were not considered. The research also assumed that the benefits of each circular economy project and the stakes of each project were known, which may not always be the case in real-world scenarios.

This manuscript found that investing in other circular economy projects in the supply chain can broaden the scope of business and increase the value of the entire supply chain. Third-party logistics companies are gradually participating in the construction and operation of many circular economy projects, such as recycling and repurposing initiatives. It highlights the importance of coordinating multiple circular economy supply chain projects to increase the value of the entire supply chain. The multi-stage stochastic programming model presented in this research can provide a useful tool for logistics enterprises and third-party logistics companies to optimize their investment decisions and maximize their profits in the context of a circular economy.

This study addresses tourists' post-consumption perspectives on the impact of online destination experiences and animosity on travel decisions. Developing a framework based on the stimulus-organism-response (SOR) theory, we examine the previously unexplored relationship between post-negative events, online destination brand experience (ODBE), tourists' animosity and destination boycott intentions within the domestic tourism context.

Data from 355 actively engaged domestic travelers in Pakistan who follow destination social media pages (i.e. Instagram and Facebook) was analyzed using structural equation modeling.

The findings reveal that post-negative events ODBE significantly stimulate tourists' animosity, which in turn drives destination boycott intentions. The ODBE indirectly affects boycott intentions through animosity, acting as a partial mediator. The analysis highlights the significance of the users' prior experience levels (novice vs experienced). Multigroup analysis shows that novice visitors are more sensitive to negative online experiences, resulting in stronger animosity than experienced visitors. Animosity significantly drives boycott intentions, particularly among experienced visitors.

This study’s novelty lies in its comprehensive examination of post-negative events, focusing on how the ODBE influences tourists' negative emotions and boycott intentions. These findings offer valuable insights for tourism researchers and destination marketers, underscoring the importance of optimizing post-service failure ODBE strategies for brand repair, online reputation management, digital marketing innovation and customized service recovery to mitigate the impact of negative events.

This paper explores what factors influence household textile washing behaviour and how these factors relate to greenhouse gas emissions during the textile use stage.

A questionnaire survey related to textile summer washing and care behavior was conducted among households in 16 administrative districts of Shanghai. This study used the modified Consumer Lifestyle Approach framework of the washing and care ecosystem. The research hypotheses were established by selecting related factors from four aspects: household demographic characteristics, economy and consumption characteristics, washing machines and detergents characteristics.

First, we have demonstrated how some course factors do not significantly affect greenhouse emissions. None of the demographics, detergent-related activities, economy and consumption constructs significantly affect greenhouse emissions. Second, we have identified that washing machine and related activities has a direct positive effect on GHG emissions. The washing machine is not only the de facto carrier of all washing activities but also the core of washing activities. Washing machine is crucial in reducing greenhouse emissions and adjusting consumer behaviors.

This paper conducts a study related to the washing and care behavior of households in Shanghai. The paper examines the factors influencing household washing behavior and the relationship between these factors and greenhouse gas emissions during the textile use phase.

Megaprojects have large impact on the environment and stakeholders should take collective action to ensure that these projects are developed in a socially responsible manner. Hitherto, it is not known whether group and subjective norms and social identity could compel stakeholders to take socially responsible collective actions in megaprojects. The aim of this study is to design and test a model to boost stakeholders' intention to take socially responsible collective action in the context of mega water transfer projects in China.

A quasi-experimental causal research design was adopted to establish cause–effect relationships among the dependent variable (we-intention) and independent variables (subjective norms, group norms, social identity and desire). This study adopts the belief–desire–intention model and social influence theory to empirically investigate how to boost the stakeholders' intention to participate in socially responsible collective action. An online questionnaire survey was conducted and data was collected from 365 respondents who were involved in mega water transfer projects in China. The partial least squares structural equation modeling technique was employed to analyze the data.

The results from partial least squares analyses indicate that the presence of subjective norms, group norms and social identity (collectively known as social influence process) could increase stakeholders' intention to take socially responsible collective action. In addition, the desire to be socially responsible also boosts stakeholders' intention to take collective action. Desire partially mediates the relationship between social influence process and intention to take socially responsible collective action.

This study adds to existing knowledge by discovering social influence process as an antecedent to taking socially responsible collective action in megaprojects. Strong group norms and subjective norms could propel stakeholders to be more socially responsible. The study also adds to knowledge by discovering that stakeholders' desire to fulfill social responsibility also leads them to take concrete actions. Implications and recommendations are provided on how to manipulate different types of social influence processes to facilitate stakeholders to adopt socially responsible collective action in the process of managing megaprojects.

This paper aims to study the direct synthesis of imino methyl ether amino resin using commercially available formaldehyde, melamine and methanol through one-step two-stage catalysis.

Initially, melamine undergoes a reaction with formaldehyde to form hydroxylmethylation melamine in a basic setting. Subsequently, hydrochloric acid is incorporated to facilitate the etherification process. The study delves into the impact of various factors during the etherification phase, including the quantity of methanol, the temperature at which etherification occurs, the number of etherification cycles and the amount of catalyst used, on the synthesis of imino methyl-etherified amino resins. Ultimately, the most favorable conditions for etherification are identified through comparative analysis to evaluate the resulting synthesized products.

The methyl-etherified amino resin, characterized by a stable structure and consistent performance, was efficiently synthesized through a one-step, two-stage catalytic process. Optimal conditions for the etherification stage were determined to be a reaction temperature of 35°C, a melamine to methanol ratio of 1:24 and an addition of hydrochloric acid ranging from 2.2 mL to 2.5 mL. Remarkably, the resulting resin notably enhanced the water resistance, salt resistance and gloss of the canned iron printing varnish coatings.

Amino resins, known for their broad applications across numerous industries, face sustainability and operational efficiency hurdles when produced through traditional methods, which predominantly involve the use of a 37% formaldehyde solution. To tackle these issues, our research introduces an innovative method that add 37% formaldehyde to facilitate industrial production. The use of 37% liquid formaldehyde in this paper has two benefits: first, it is convenient for industrial application and production; Second, it is convenient to provide mild reaction conditions at lower concentrations because the amino group is relatively active, which is convenient for the preservation of the amino group and integrates it with a one-step, two-stage catalytic process. The primary objective of our study is threefold: to reduce the environmental footprint of amino resin synthesis, to optimize the use of resources and to improve the economic viability for its large-scale production. By employing this new strategy, we try to provide a more sustainable and efficient manufacturing process for amino resins.

Objectively evaluating the fairness of the algorithm, exploring in specific scenarios combined with scenario characteristics and constructing the algorithm fairness evaluation index system in specific scenarios.

This paper selects marketing scenarios, and in accordance with the idea of “theory construction-scene feature extraction-enterprise practice,” summarizes the definition and standard of fairness, combs the application link process of marketing algorithms and establishes the fairness evaluation index system of marketing equity allocation algorithms. Taking simulated marketing data as an example, the fairness performance of marketing algorithms in some feature areas is measured, and the effectiveness of the evaluation system proposed in this paper is verified.

The study reached the following conclusions: (1) Different fairness evaluation criteria have different emphases, and may produce different results. Therefore, different fairness definitions and standards should be selected in different fields according to the characteristics of the scene. (2) The fairness of the marketing equity distribution algorithm can be measured from three aspects: marketing coverage, marketing intensity and marketing frequency. Specifically, for the fairness of coverage, two standards of equal opportunity and different misjudgment rates are selected, and the standard of group fairness is selected for intensity and frequency. (3) For different characteristic fields, different degrees of fairness restrictions should be imposed, and the interpretation of their calculation results and the means of subsequent intervention should also be different according to the marketing objectives and industry characteristics.

First of all, the fairness sensitivity of different feature fields is different, but this paper does not classify the importance of feature fields. In the future, we can build a classification table of sensitive attributes according to the importance of sensitive attributes to give different evaluation and protection priorities. Second, in this paper, only one set of marketing data simulation data is selected to measure the overall algorithm fairness, after which multiple sets of marketing campaigns can be measured and compared to reflect the long-term performance of marketing algorithm fairness. Third, this paper does not continue to explore interventions and measures to improve algorithmic fairness. Different feature fields should be subject to different degrees of fairness constraints, and therefore their subsequent interventions should be different, which needs to be continued to be explored in future research.

This paper combines the specific features of marketing scenarios and selects appropriate fairness evaluation criteria to build an index system for fairness evaluation of marketing algorithms, which provides a reference for assessing and managing the fairness of marketing algorithms.

Algorithm governance and algorithmic fairness are very important issues in the era of artificial intelligence, and the construction of the algorithmic fairness evaluation index system in marketing scenarios in this paper lays a safe foundation for the application of AI algorithms and technologies in marketing scenarios, provides tools and means of algorithm governance and empowers the promotion of safe, efficient and orderly development of algorithms.

In this paper, firstly, the standards of fairness are comprehensively sorted out, and the difference between different standards and evaluation focuses is clarified, and secondly, focusing on the marketing scenario, combined with its characteristics, key fairness evaluation links are put forward, and different standards are innovatively selected to evaluate the fairness in the process of applying marketing algorithms and to build the corresponding index system, which forms the systematic fairness evaluation tool of marketing algorithms.

Conceptual and empirical research over the past 20 years has moved the social media (SM) literature beyond the embryotic stage to a well-developed academic discipline. As the lead article in the special issue in the Journal of Research in Interactive Marketing on Cutting-Edge Research in Social Media and Interactive Marketing, this review and agenda article has two key goals: (1) to review key SM and interactive marketing research over the past three years and (2) to identify the next wave of high priority challenges and research opportunities.

Given the “cutting-edge” research focus of the special issue, this review and research agenda paper focused on articles published in 25 key marketing journals between January 2021 and March 2024. Initially, the search request was for articles with “social media, social selling, social commerce” located in the article title, author-selected key words and journal-selected keywords. Later, we conducted searches based on terminology from articles presented in the final review. In total, over 1,000 articles were reviewed across the 25 journals, plus additional ones that were cited in those journals that were not on the initial list.

Our review uncovered eight key content areas: (1) data sources, methodology and scale development; (2) emergent SM technologies; (3) artificial intelligence; (4) virtual reality; (5) sales and sales management; (6) consumer welfare; (7) influencer marketing; and (8) social commerce. Table I provides a summer of key articles and research findings for each of the content areas.

As a literature review and research agenda article, this paper is one of the most extensive to date on SM marketing, and particularly with regard to emergent research over the past three years. Recommendations for future research are integrated through the paper and summarized in Figure 2.

Consumer welfare is one of the eight emergent content areas uncovered in the literature review. Specific focus is on SM privacy, misinformation, mental health and misbehavior.

To enhance the understanding of the antecedents of students' career adaptability, this study employs the crossover model to explore the potential transfer of career adaptability from headteachers to students and the underlying mechanisms involved.

This study examined the proposed moderated mediation model using matched survey data collected from 37 headteachers and 1,598 students in Chinese higher vocational colleges.

Headteachers’ career adaptability is positively related to students’ career adaptability via students’ psychological capital. An increased frequency of headteacher–student interactions strengthened the indirect relationship between headteachers' career adaptability and students' career adaptability.

The findings suggest that, under certain conditions, headteachers’ career adaptability could be transferred to students via students’ psychological capital.

This paper aims to address the safety concerns of path-planning algorithms in dynamic obstacle warehouse environments. It proposes a method that uses improved artificial potential fields (IAPF) as expert knowledge for an improved deep deterministic policy gradient (IDDPG) and designs a hierarchical strategy for robots through obstacle detection methods.

The IAPF algorithm is used as the expert experience of reinforcement learning (RL) to reduce the useless exploration in the early stage of RL training. A strategy-switching mechanism is introduced during training to adapt to various scenarios and overcome challenges related to sparse rewards. Sensor inputs, including light detection and ranging data, are integrated to detect obstacles around waypoints, guiding the robot toward the target point.

Simulation experiments demonstrate that the integrated use of IDDPG and the IAPF method significantly enhances the safety and training efficiency of path planning for mobile robots.

This method enhances safety by applying safety domain judgment rules to improve APF’s security and designing an obstacle detection method for better danger anticipation. It also boosts training efficiency through using IAPF as expert experience for DDPG and the classification storage and sampling design for the RL experience pool. Additionally, adjustments to the actor network’s update frequency expedite convergence.