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The study employs two independent experimental studies to collect data. It focuses on the matching effect between advertising appeals and product types. The Elaboration Likelihood Model serves as the theoretical framework for understanding the cognitive processing involved in consumers' responses to these advertising appeals and product combinations.

This paper aims to investigate the impact of advertising appeals on consumers' intentions to purchase organic food. We explored the interaction between advertising appeals (egoistic vs altruistic) and product types (virtue vs vice) and purchase intention. The goal is to provide insights that can enhance the advertising effectiveness of organic food manufacturers and retailers.

The analysis reveals significant effects on consumers' purchase intentions based on the matching of advertising appeals with product types. Specifically, when egoistic appeals align with virtuous products, there is an improvement in consumers' purchase intentions. When altruistic appeals match vice products, a positive impact on purchase intention is observed. The results suggest that the matching of advertising appeals with product types enhances processing fluency, contributing to increased purchase intention.

This research contributes to the field by providing nuanced insights into the interplay between advertising appeals and product types within the context of organic food. The findings highlight the importance of considering the synergy between egoistic appeals and virtuous products, as well as altruistic appeals and vice products. This understanding can be strategically employed by organic food manufacturers and retailers to optimize their advertising strategies, thereby improving their overall effectiveness in influencing consumers' purchase intentions.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

To endure and cope in the rapidly changing environment, it is required of firms to gain a deeper acquisition of knowledge on market dynamics and subsequently concentrate on corporations' capacity to create, restructure and integrate their internal and external competences. Hence, the objective of this study is to investigate the influence of eco-dynamic capability (EDC) on the sustainability performance of small and medium-sized enterprises (SMEs).

Structured questionnaires were used to obtain primary data. The data were solicited from 500 employees and owner-managers of SMEs. The study’s hypotheses were tested using standard multiple regression through IBM SPSS Statistics (version 24).

The study revealed that EDC has a substantial positive effect on the economic, social and environmental sustainability performance dimensions.

The focus of this study is on EDC. Thus, although dynamic capability has been the subject of substantial study, little is known regarding the effect of EDC on the economic sustainability performance (ESP) (financial), environmental sustainability performance (ENSP) and social sustainability performance (SSP) of SMEs, predominantly amongst SMEs in emerging economies.

This paper elucidates the role of anger in error management (EM) and organizational learning behaviors. The study explores how anger can catalyze learning, emphasizing its strategic implications.

A double-layered moderated-mediated model was developed and tested using data from 744 Chinese CEOs. The psychometric properties of the survey instrument were rigorously examined through structural equation modeling, and hypotheses were tested using Hayes's PROCESS macros.

The findings reveal that anger is a precursor for recognizing the value of significant errors, leading to a positive association with learning behavior among top management team members. Additionally, the study uncovers a triple interaction effect of anger, EM culture and supply chain disruptions on the value of learning from errors. Extensive experience and positive grieving strengthen the relationship between recognizing value from errors and learning behavior.

This study uniquely integrates affect-cognitive theory and organizational learning theory, examining anger in EM and learning. The authors provide empirical evidence that anger can drive error value recognition and learning. The authors incorporate a more fine-grained approach to leadership when including executive anger as a trigger to learning behavior. Factors like experience and positive grieving are explored, deepening the understanding of emotions in learning. The authors consider both negative and positive emotions to contribute to the complexity of organizational learning.

This study considers the “technology creation” characteristic of technical knowledge-intensive business services (T-KIBS) and examines how human capital and intellectual property rights (IPR) protection affect the location choice of foreign direct investment (FDI) in China for two types of T-KIBS: (1) information transmission, software and information technology (ICT) services and (2) scientific research and technology (SCI) services.

Our empirical analysis is based on panel data on 22 Chinese provinces from 2009 to 2017. We use the generalized method of moments estimation for the regression analysis.

FDI in ICT services prefers regions with high human capital, while FDI in SCI services favors regions with good IPR protection.

Future research could use more comprehensive data and qualitative interviews to enhance the findings.

These findings provide a foundation for China’s future policy on attracting FDI into T-KIBS, especially in areas related to human capital and IPR protection.

This study bridges the research gap on the FDI location choice of T-KIBS in China by clarifying the influences of human capital and IPR protection and providing theoretical support for the location choice of T-KIBS FDI.

Sports marketing and sponsorship research is located at the intersection of behavioral and design research, which means that it analyzes the current world and shapes a future world. This dual focus poses challenges for formulating and testing theories of sports marketing.

This article develops criteria for categorizing theoretical concepts as either behavioral or formed as different ways of expressing ideas of sports marketing research. It emphasizes the need for clear concept categorization for proper operationalization and applies these criteria to selected theoretical concepts of sports marketing and sponsorship research.

The study defines three criteria to categorize theoretical concepts, namely (1) the guiding idea of research, (2) the role of observed variables, and (3) the relationship among observed variables. Applying these criteria to concepts of sports marketing research manifests the relevance of categorizing theoretical concepts as either behavioral or formed to operationalize concepts correctly.

This study is the first in sports marketing to clearly categorize theoretical concepts as either behavioral or formed, and to formulate guidelines on how to differentiate behavioral concepts from formed concepts.

This paper delves into cross-border E-business, unraveling its intricate dynamics and forecasting its future trajectory.

This paper projects the prospective market size of cross-border E-business in China for the year 2023 using the GM (1,1) gray forecasting model. Furthermore, to enhance the analysis, the paper attempts to simulate and forecast the size of China’s cross-border E-business sector using the GM (1,3) gray model. This extended model considers not only the historical trends of cross-border E-business but also the growth patterns of GDP and the digital economy.

The forecast indicates a market size of 18,760 to 18,934 billion RMB in 2023, aligning with the consistent growth observed in previous years. This suggests a sustained positive trajectory for cross-border E-business.

Cross-border e-commerce critically shapes China’s global integration and traditional industry development. The research in this paper provides insights beyond statistical trends, contributing to a nuanced understanding of the pivotal role played by cross-border e-commerce in shaping China’s economic future.

This study aims to examine the co-creation of customer experiences at different levels in service ecosystems, analyzing the case of a tourist destination.

A questionnaire was designed based on previously validated scales. The questionnaire was distributed through the social media platforms Facebook and Instagram. The survey yielded 1,476 valid responses for three types of destinations. Structural equation modeling and multigroup analysis were performed to test the hypotheses.

Aggregate service experience and memorable customer experience (MCE) in service ecosystems are determined by customer experiences at a dyadic level. Service experience at the ecosystem level is formed from ordinary experiences at the actor level, while MCE is formed from extraordinary experiences at the dyadic level. The type of ecosystem moderates the relationships between the variables but does not alter the importance of each of them.

The relationship between the co-creation of customer experiences at different levels of service ecosystems (dyadic vs aggregate) is addressed. A relationship is established between the ordinary and extraordinary character of experiences and their memorability at the ecosystem level.

Digital inclusive finance has a positive promotion effect on the development of the national economy, but little research exists on how digital inclusive finance affects high-quality consumption in economically developed regions. Therefore, to fill the gap, this paper aims to study the impact of digital inclusive finance on high-quality consumption development using the economically developed regions of Jiangsu, Zhejiang and Shanghai as examples.

Firstly, the entropy method is used to construct the index of high-quality consumption among residents. Then, the municipal-level data of Jiangsu, Zhejiang and Shanghai from 2011 to 2020 are used to test the impact. Subsequently, the mechanism of action test and heterogeneity analysis are conducted.

The results show that digital inclusive finance has a positive role in promoting the high-quality consumption of residents in Jiangsu, Zhejiang and Shanghai. At the same time, digital inclusive finance can promote high-quality consumption through its own digital payment and internet insurance channels. There is regional heterogeneity in the impact.

To the best of the authors’ knowledge, this study is the first to examine whether and how digital inclusive finance affects high-quality consumption. The authors consider multiple dimensions, such as consumption level, consumption structure, consumption ability, consumption environment and consumption mode, to measure high-quality consumption. The findings provide valuable insights for policymakers, investors and regulators in planning regulations.

This study aims to propose and evaluate the progress in the basic-pixel (a strategy to generate continuous trajectories that fill out the entire surface) algorithm towards performance gain. The objective is also to investigate the operational efficiency and effectiveness of an enhanced version compared with conventional strategies.

For the first objective, the proposed methodology is to apply the improvements proposed in the basic-pixel strategy, test it on three demonstrative parts and statistically evaluate the performance using the distance trajectory criterion. For the second objective, the enhanced-pixel strategy is compared with conventional strategies in terms of trajectory distance, build time and the number of arcs starts and stops (operational efficiency) and targeting the nominal geometry of a part (operational effectiveness).

The results showed that the improvements proposed to the basic-pixel strategy could generate continuous trajectories with shorter distances and comparable building times (operational efficiency). Regarding operational effectiveness, the parts built by the enhanced-pixel strategy presented lower dimensional deviation than the other strategies studied. Therefore, the enhanced-pixel strategy appears to be a good candidate for building more complex printable parts and delivering operational efficiency and effectiveness.

This paper presents an evolution of the basic-pixel strategy (a space-filling strategy) with the introduction of new elements in the algorithm and proves the improvement of the strategy’s performance with this. An interesting comparison is also presented in terms of operational efficiency and effectiveness between the enhanced-pixel strategy and conventional strategies.