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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 paper aims to study the material conscious information network (MCIN) to present new models of clothing products and persons and propose new crowd-designing patterns to reconstruct an improved supply–demand relationship in clothing industry.

This paper aims to study the MCIN to present new models of clothing products and persons and propose new crowd-designing patterns to reconstruct an improved supply–demand relationship in clothing industry.

At last, this paper implements a prototype system of novel e-commerce platform based on the CDCI to illustrate the effectiveness and soundness of the CDCI modeling.

Different from most related works just focusing on the physiology dimension in the matching of customer and clothing, this paper proposes that the dimension of physiology, character, knowledge and experience should be synthetically considered.

Collaborating with consumers during new product development can provide companies with significant benefits and competitive advantages. Although several studies have been conducted on the design of co-innovation platforms, there is still a need for a more comprehensive understanding of the co-innovation phenomenon. To address this gap, this research aims to identify the critical success factors of co-innovation platforms and provide an extensive analysis of the variables that determine their effectiveness.

This study presents a systematic literature review of co-innovation platforms based on an analysis of 89 articles published in 50 scholarly journals in the disciplines of information systems, marketing and business, covering the years from 2006 to 2022.

The review synthesizes the current state of scientific knowledge and groups prior studies thematically as critical success factors of co-innovation platforms. As a result, eight success factors have been identified in terms of quantity and quality of contributions. These factors include product involvement, perceived fairness, sense of community, interactive environment, employee involvement, participant diversity, assessment structure and task design.

The study consolidates existing research about the critical success of co-innovation platforms. It also provides a research framework that incorporates a diverse set of variables that can be used to assess co-innovation performance in future studies.

Clinical notes typically contain medical jargons and specialized words and phrases that are complicated and technical to most people, which is one of the most challenging obstacles in health information dissemination to consumers by healthcare providers. The authors aim to investigate how to leverage machine learning techniques to transform clinical notes of interest into understandable expressions.

The authors propose a natural language processing pipeline that is capable of extracting relevant information from long unstructured clinical notes and simplifying lexicons by replacing medical jargons and technical terms. Particularly, the authors develop an unsupervised keywords matching method to extract relevant information from clinical notes. To automatically evaluate completeness of the extracted information, the authors perform a multi-label classification task on the relevant texts. To simplify lexicons in the relevant text, the authors identify complex words using a sequence labeler and leverage transformer models to generate candidate words for substitution. The authors validate the proposed pipeline using 58,167 discharge summaries from critical care services.

The results show that the proposed pipeline can identify relevant information with high completeness and simplify complex expressions in clinical notes so that the converted notes have a high level of readability but a low degree of meaning change.

The proposed pipeline can help healthcare consumers well understand their medical information and therefore strengthen communications between healthcare providers and consumers for better care.

An innovative pipeline approach is developed to address the health literacy problem confronted by healthcare providers and consumers in the ongoing digital transformation process in the healthcare industry.

The purpose of this paper is to examine peer-to-peer sharing platform business models, their sources of competitive advantage, and the roles, motivations and behaviors of key actors in their ecosystems.

This paper uses a conceptual approach that is rooted in the service, tourism and hospitality, and strategy literature.

First, this paper defines key types of platform business models in the sharing economy anddescribes their characteristics. In particular, the authors propose the differentiation between sharing platforms of capacity-constrained vs capacity-unconstrained assets and advance five core properties of the former. Second, the authors contrast platform business models with their pipeline business model counterparts to understand the fundamental differences between them. One important conclusion is that platforms cater to vastly more heterogeneous assets and consumer needs and, therefore, require liquidity and analytics for high-quality matching. Third, the authors examine the competitive position of platforms and conclude that their widely taken “winner takes it all” assumption is not valid. Primary network effects are less important once a critical level of liquidity has been reached and may even turn negative if increased listings raise friction in the form of search costs. Once a critical level of liquidity has been reached, a platform’s competitive position depends on stakeholder trust and service provider and user loyalty. Fourth, the authors integrate and synthesize the literature on key platform stakeholders of platform businesses (i.e. users, service providers, and regulators) and their roles and motivations. Finally, directions for further research are advanced.

This paper helps platform owners, service providers and users understand better the implications of sharing platform business models and how to position themselves in such ecosystems.

This paper integrates the extant literature on sharing platforms, takes a novel approach in delineating their key properties and dimensions, and provides insights into the evolving and dynamic forms of sharing platforms including converging business models.

This paper aims to provide an overall review and assessment of the virtues and flaws of decentralized self-regulated markets, discussing in particular the extent to which deceiving attitudes by some market participants might be potentially diluted and contradicted.

To approach deception and morality in markets, the paper follows two paths. First, the relevant recent literature on the theme is reviewed, examined and debated, and second, one constructs a simulation model equipped with the required elements to discuss the immediate and long-term impacts of deceiving behaviour over market outcomes.

The discussion and the model allow for highlighting the main drivers of the purchasing decisions of consumers and for evaluating how they react to manipulating behaviour by firms in the market. Agents pursuing short-run gains through unfair market practices are likely to be punished as fooled agents spread the word about the malpractices they were allegedly subject to.

Markets are complex entities, where large numbers of individual agents typically establish local and direct contact with one another. These agents differ in many respects and interact in unpredictable ways. Assembling a concise model capable of addressing such complexity is a difficult task. The framework proposed in this paper points in the intended direction.

The debate in this paper contributes to a stronger perception on the mechanisms that attribute robustness and vitality to markets.

Different from manufacturing resources allocation problems, the prices and amounts of limited public service resources could not be changed with the consumers’ requirements and social fairness is the most important objective for improving allocation efficiency. To measure social fairness reasonably, the purpose of this paper is fourfold: first, divide social fairness into longitudinal comparative fairness and crosswise comparative fairness, therefore providing their calculation formula and describing the comprehensive fair degree by using the interval numbers. Second, the comparison regulations of interval numbers are given and the corresponding features are also described. Third, an extension of VIKOR method is put forward for evaluating social fairness of different allocation alternatives with interval numbers. Finally, a numerical example illustrates the proposed method and clarifies the main results developed in the paper.

In this paper, the author depicts the social fair degree as an interval number, and thus proposes the comparison method between any two interval numbers. Based on the basis procedure of the VIKOR method, the paper proposes an extension of the fuzzy VIKOR method with the interval numbers to rank and select the compromise allocation alternatives. Finally, a numerical example illustrates the practicability of the proposed method.

The comparison of interval numbers is very important when the author evaluates the decision alternatives. Through analyzing the present comparison methods, the paper proposes the simple method of comparing the interval numbers, which can obtain the same results with the above two methods. The fuzzy VIKOR method, a popular multi-criteria decision-making method, focusses on ranking and selecting from a set of alternatives in a fuzzy environment. For the fuzzy value, the paper also proposes the extension of the VIKOR method to perform an evaluation and get the compromise alternatives.

According to the huge customers’ requirement, how to improve their social fair degree has become the focus in public service resources allocation, where the social fair degree may be a comprehensive concept which includes the fair degree compared with all the other allocation alternatives and the fair degree compared with the other small group under the same allocation alternative. In the paper, the author defines the above two types of fair degree and then depicts the comprehensive fair degree as their integration, which will be interval numbers.

In this paper, the authors study the effect of consumers' fairness preferences on dynamic pricing strategies adopted by platforms in a non-cooperative game.

This study applies fair game and repeated game theory.

This study reveals that, in a one-shot game, if consumers have fairness preferences, dynamic prices will slightly decline. In a repeated game, dynamic prices will be reduced even when consumers do not have fairness preferences. When fairness preferences and repeated game are considered simultaneously, dynamic prices are most likely to be set at fair prices. The authors also discuss the effect of platforms' discounting factors, the consumers' income and alternative choices of consumption on the dynamic prices.

The study findings illustrate the importance of incorporating behavioral elements in understanding and designing the dynamic pricing strategies for platforms and the implications on social welfare in general.

The authors developed a theoretical model to incorporate consumers' fairness preference into the decision-making process of platforms when they design the dynamic pricing strategies.

Urban metropolitan consumers react to the different qualitative categorizations of the product thus creating homogeneous market segments. The aim of this paper is to identify specific market segments which allow for the definition of homogeneous olive oil consumer targets.

This study was based on the stated preferences of consumers and emphasizes the role that different quality scales of olive oil have in the eye of the consumer. The data, collected through a questionnaire, were analysed by means of inferential and multivariate statistics techniques, that is, the study specifically entailed a factorial and cluster analysis.

This paper explores olive oil market segments broken down by the different quality levels of existing products, thus trying to identify main consumer preferences. Our outcomes suggest the existence of three main quality classes of olive oil consumer: basic, popular and premium.

Even though we gathered data and information from a broad sample, the study does not fully reflect the average Italian population since we based our study on a convenience sample of northern Italian consumers. A more extended sample is needed to test our hypothesis in other regional areas.

The outcomes derived from this study provide useful insights both for marketers and olive oil producers by allowing more efficient strategic decisions in terms of product segmentation.

This study, aimed at matching olive oil market segments and consumer preferences, shows the existence of three well-defined quality classes of olive oil consumer: basic, popular and premium. In addition, this study ascertains for the first time how the attitude towards local products is positively influenced by family origin as a result of an inter-generational attitude.

By observing facts of the “reversal of agglomeration” of Chinese enterprises during the period of rapid Internet development and using a new economic geography model combined with the data of the real estate sector, this paper deduces the influence of the “reshaping mechanisms” of the Internet on China's economic geography based on the “gravitation mechanism” of the Internet that affects the enterprises and the “amplification mechanism” of the Internet that amplifies the dispersion force of house prices.

In the empirical aspect, the dynamic spatial panel data model is used to test the micromechanisms of the impact of the Internet on enterprises' choice of location and the instrumental variable method is used to verify the macro effects of the Internet in reshaping economic geography.

It is found that in the era of the network economy, the Internet has become a source of regional competitive advantage and is extremely attractive to enterprises. The rapidly rising house price has greatly increased the congestion cost and has become the force behind the dispersion of enterprises. China's infrastructure miracle has closed the access gap which gives full play to network externalities and promotes the movement of enterprises from areas with high house prices to areas with low house prices.

The Internet is amplifying the dispersion force of congestion costs manifested as house prices and is reshaping China's economic geography. This paper further proposes policy suggestions such as taking the Internet economy as the new momentum of China's economic development and implementing the strategy of regional coordinated development.