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This paper is devoted to describe how innovation should be branded and bridge the gap between branding and innovation, where the role of branding capability is crucial. The study aims to discuss the link between branding and innovation, both theoretically and empirically.

On the basis of current resource-based theory and dynamic capabilities theory and brand management, the research explores the role of branding capability for innovative companies. For the empirical part, an event study is first used to calculate the abnormal returns from new product announcement. Second, different regression models are analyzed to check the effect of branding capability on the stock market reaction to new product announcements made by those innovative companies.

The stock market response to new product announcements is related to branding capability, but negatively. The reason could be that the more famous the brand is, the higher expectations the investors would hold with its new products.

The empirical study is based on the computer/electronics industry, and the pooled sample consists of those strong brands in the marketplace, which is not representative for the innovative companies as a whole. Thus, this paper has limited scope to generalize the results.

With the development of wireless communication technologies, the new offerings from innovative companies would not be simply categorized by tangible devices or intangible services. Moreover, the brand alliance strategy in the tablet and handset market, or even PCs and netbook market, is much more complicated than simply choosing partners.

The main contribution of this paper is to extend the prior researches in branded innovation and fill in the gap between innovation and brand.

This paper aims to explore the factors that influence Generation Y’s positive or negative electronic word-of-mouth (eWOM) behavior via social media and mobile technology in the foodservice sector. Three types of dining experiences were examined: positive and negative customer experiences and negative customer service followed by a satisfactory recovery package.

A survey was adopted to test the factors posited to influence Generation Y consumers in these service contexts. Participants were recruited through Amazon Mechanical Turk , and multi-group structural equation modeling was performed to analyze the data.

Active use of social media and peer influence had a sweeping influence on Generation Y’s intentions to engage in eWOM about their service experiences. Technological sophistication with mobile technology influenced Generation Y to spread positive or negative service experiences, rather than satisfactory recovery experiences. Family influence had a mixed influence on Generation Y subgroups (21-24 years old vs 25-35 years old) to engage in eWOM about their satisfactory or poor service experiences. In satisfactory recovery experiences, family influence showed no significant influence on Generation Y’s eWOM behaviors.

This study enriches online reviews and eWOM marketing theories, adds to service failure and recovery literature and enhances understanding of consumer behavior expressed by Generation Y through the empirical investigation of Generation Y consumers’ behavioral motivations to engage in eWOM through social media and mobile technology.

Engaging Generation Y consumers with social media campaigns and mobile technology development is not merely sufficient in eWOM marketing strategies. Instead, it is essential to create integrative peer communities to motivate Generation Y consumers to engage in eWOM marketing. Marketers need to pay attention to the mixed effects of family influences on the eWOM behaviors of subgroups of Generation Y in positive or negative service experiences.

Given the scarcity of consumer behavior research into Generation Y as an emerging market segment, this paper makes an incremental contribution by developing and validating a model of factors that influence Generation Y consumers’ eWOM intentions through social networking and mobile technologies in three major service contexts: positive, negative and recovery following a service failure.

The deployment of vaccines is the primary task in curbing the COVID-19 pandemic. The purpose of this paper is to understand the public’s opinions on vaccines and then design effective interventions to promote vaccination coverage.

This paper proposes a research framework based on the spatiotemporal perspective to analyse the public opinion evolution towards COVID-19 vaccine in China. The framework first obtains data through crawler tools. Then, with the help of data mining technologies, such as emotion computing and topic extraction, the evolution characteristics of discussion volume, emotions and topics are explored from spatiotemporal perspectives.

In the temporal perspective, the public emotion declines in the later stage, but overall emotion performance is positive and stabilizing. This decline in emotion is mainly associated with ambiguous information about the COVID-19 vaccine. The research progress of vaccines and the schedule of vaccination have driven the evolution of public discussion topics. In the spatial perspective, the public emotion tends to be positive in 31 regions, whereas local emotion increases and decreases in different stages. The dissemination of distinctive information and the local epidemic prevention and control status may be potential drivers of topic evolution in local regions.

The analysis results of media information can assist decision-makers to accurately grasp the subjective thoughts and emotional expressions of the public in terms of spatiotemporal perspective and provide decision support for macro-control response strategies and risk communication.

The outbreak of COVID-19 has become a major public health emergency worldwide. How to effectively guide public opinion and implement precise prevention and control is a hot topic in current research. Mining the spatiotemporal coupling between online public opinion and offline epidemics can provide decision support for the precise management and control of future emergencies.

This study focuses on analyzing the spatiotemporal coupling relationship between public opinion and the epidemic. First, based on Weibo information and confirmed case information, a field framework is constructed using field theory. Second, SnowNLP is used for sentiment mining and LDA is utilized for topic extraction to analyze the topic evolution and the sentiment evolution of public opinion in each coupling stage. Finally, the spatial model is used to explore the coupling relationship between public opinion and the epidemic in space.

The findings show that there is a certain coupling between online public opinion sentiment and offline epidemics, with a significant coupling relationship in the time dimension, while there is no remarkable coupling relationship in space. In addition, the core topics of public concern are different at different coupling stages.

This study deeply explores the spatiotemporal coupling relationship between online public opinion and offline epidemics, adding a new research perspective to related research. The result can help the government and relevant departments understand the dynamic development of epidemic events and achieve precise control while mastering the dynamics of online public opinion.

The purpose of this study is to explore the motivational role of feedback information (positive and negative) provided by the firm in the face of participant heterogeneity, in terms of past success experience, under the research setting of crowdsourcing contests.

Taking insights from feedback studies and the dynamics of self-regulation theory, four theoretical hypotheses are proposed. An integrated dataset of 4,880 contest-participant pairs, which is obtained from an online contest platform and a survey, is empirically analyzed.

Empirical analysis shows that both positive feedback and negative feedback are able to stimulate the inner needs of participants. Notably, negative (positive) feedback becomes more (less) effective in intrinsically motivating crowds as they gain more successful experience during contest participation.

This study brings some new knowledge for the intrinsic motivation of crowds by exploring its antecedents, which have been undervalued in extant literature. The motivational role of feedback information is particularly explored.

Improving the agricultural products market integration is conducive to developing provincial comparative advantage, optimization of agricultural and industrial organization and enhanced competitiveness. The relationship between the emergencies and the agricultural products market integration in the production and consumption provinces is of great significance for stabilizing market prices and improving the efficiency of agricultural resource allocation.

The authors reviewed the literature on the market integration of agricultural products. Then, they adopted a two-way fixed effect model to investigate the impact of emergencies on the poultry market integration in the production and consumption provinces in China.

Highly pathogenic avian influenza (HPAI) caused abnormal fluctuations in the poultry market price and decreased the poultry market integration. The negative impact of HPAI on poultry market integration was strengthened in the main production provinces and weakened in the main consumption provinces.

This is the first study that applies empirical analysis to identify the emergencies’ impact on the poultry market integration considering production and consumption characteristics. The results indicate that the impact of avian influenza is more serious in production provinces than in consumption provinces. Due to the heterogeneity of production and consumption provinces, the government implements precise compensation policies to resume production quickly after the disaster. It can be conductive to market integration and promote the development of agricultural products market.

Using social network theory (SNT), this study empirically examines the impact of digital supply chain announcements disclosing corporate social responsibility (CSR) information on stock market value.

Based on 172 digital supply chain announcements disclosing CSR information from Chinese A-share listed companies, this study uses event study method to test the hypotheses.

First, digital supply chain announcements disclosing CSR information generate positive and significant market reactions, which is timely. Second, strategic CSR and value-based CSR disclosed in digital supply chain announcements have a more positive impact on stock market, however there is no significant difference when the CSR orientation is either towards internal or external stakeholders. Third, in terms of digital supply chain network characteristics, announcements reflecting higher relationship embeddedness and higher digital breadth and depth lead to more positive increases of stock value.

First, the authors consider the value of CSR information in digital supply chain announcements, using an event study approach to fill the gap in the related area. This study is the first examination of the joint impact of digital supply chain and CSR on market reactions. Second, compared to the previous studies on the single dimension of digital supply chain technology application, the authors innovatively consider supply chain network relationship and network structure based on social network theory and integrate several factors that may affect the market reaction. This study improves the understanding of the mechanism between digital supply chain announcements disclosing CSR information and stock market, and informs future research.

This paper aims to develop a theoretical model to understand co-creation/co-destruction of value through customer engagement in online channels. It also investigates the contributing factors.

The qualitative approach uses the critical incidents technique to answer the research questions. The authors identify 350 critical incidents in which customers expressed online customer engagement-induced value co-creation or co-destruction experiences. The factors and resulting propositions are identified through data analysis. Data coding and analysis are facilitated by using MAXQDA 12.

Co-creation through positively valenced engagement behaviors may occur when customers are delighted, feel valued, experience reciprocity, receive organizational incentives, are solicited for feedback, can count on service recovery efforts and interact with helpful, empathetic, polite and responsive employees. Co-destruction through negatively valenced engagement behaviors emerges from rude employee behaviors, indifference, confrontation with company representatives, technological failure, the lack of complaint outlets and customers’ desire for revenge.

Selecting and training employees to be helpful, polite, responsive and empathetic toward online visitors can trigger co-creation. Communication between firms and customers should boost customer approval and delight. Organizations can offer incentives, reliable service delivery and a recovery design to stimulate visitor participation. Soliciting feedback requires sound technological support and direct communication links with visitors.

This study presents the conditions and framework contributing to the duality of customer engagement-induced co-creation and co-destruction values in online channels from the customer, organizational, employee, service design and technological perspectives. It also addresses how value is co-created or co-destructed through examples.

Because of short life cycle and fluctuating greatly in total sales volumes (TSV), it is difficult to accumulate enough sales data and mine an attribute set reflecting the common needs of all consumers for a kind of experiential product with short life cycle (EPSLC). Methods for predicting TSV of long-life-cycle products may not be suitable for EPSLC. Furthermore, point prediction cannot obtain satisfactory prediction results because information available before production is inadequate. Thus, this paper aims at proposing and verifying a novel interval prediction method (IPM).

Because interval prediction may satisfy requirements of preproduction investment decision-making, interval prediction was adopted, and then the prediction difficult was converted into a classification problem. The classification was designed by comparing similarities in attribute relationship patterns between a new EPSLC and existing product groups. The product introduction may be written or obtained before production and thus was designed as primary source information. IPM was verified by using data of crime movies released in China from 2013 to 2017.

The IPM is valid, which uses product introduction as input, classifies existing products into three groups with different TSV intervals, mines attribute relationship patterns using content and association analyses and compares similarities in attribute relationship patterns – to predict TSV interval of a new EPSLC before production.

Different from other studies, the IPM uses product introduction to mine attribute relationship patterns and compares similarities in attribute relationship patterns to predict the interval values. It has a strong applicability in data content and structure and may realize rolling prediction.