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Underpinned by the lens of Contingency Theory (CT), the purpose of this paper is to empirically evaluate whether the impact of social media analytics (SMA) on customer satisfaction (CS) is contingent on the characteristics of different external stakeholders, including business partners (i.e. partner diversity), competitors (i.e. localised competition) and customers (i.e. customer engagement).

Using both subjective and objective measures from multiple sources, we collected primary data from 141 hotels operating in Greece and their archival data from TripAdvisor and the Hellenic Chamber of Hotels (HCH) database to test the hypothesised relationships. Data were analysed through structural equation modelling.

This study confirms the positive association between SMA and CS, but it remains subject to the varied characteristics of external stakeholders. We find that an increase in CS due to the implementation of SMA is more pronounced for firms that (1) adopt a selective distribution strategy where a limited number of business partners are chosen for collaboration or (2) operate in a highly competitive local environment. The results further indicate that high level of customer engagement amplifies the moderating effect of partner diversity (when it is low) and localised competition (when it is high) on the SMA–CS relationship.

The study provides novel insights for managers on the need to consider external stakeholder characteristics when implementing SMA to enhance firms' CS, and for researchers on the value of studying SMA implementation from the CT perspective.

This study aims to explore the impact of carbon neutral announcements on “stock market value” of publicly listed companies in China.

The event study approach is adopted. Market, market-adjusted, Carhart four-factor model and a cross-sectional regression model are employed to examine the impacts of carbon neutral announcements on “stock market value” of Chinese companies based on data from 188 carbon neutral announcements.

Carbon neutral announcements positively impact Chinese shareholder value. Carbon neutral announcements at the strategic level have a more positive and significant impact on Chinese stock market value. Innovative carbon neutral announcements do not significantly cause Chinese stock market reactions. Companies have more positive and significant stock market reactions when the companies make carbon neutral announcements that reflect high supply chain network resilience and heterogeneity and strong supply chain network relationships.

The findings uncover the business value of carbon neutral activities and provide operations managers in developing countries insights into how to improve enterprises' market value by actively implementing carbon neutral activities.

This paper is the first trial to apply an event study to examine the relationship between carbon neutral announcements and Chinese stock market value from the perspective of announcement level and type and supply chain networks. This paper introduces corporate reputation theory and enriches the application of corporate reputation theory in the field of low-carbon environmental protections and supply chains.

Ever since its emergence, the metaverse has presented opportunities and disruptions to every stakeholder, including individual users and organizations. This article aims to offer valuable perspectives on six identified critical areas that the metaverse could significantly impact: marketing ethics, marketing communication, relationship marketing, retail marketing, supply chain management and transportation management.

Through a multi-perspective approach, this paper gathers valuable perspectives from various invited contributors to each of the six identified key areas that the metaverse could significantly impact.

For each key area identified, the invited contributors first share their valuable perspectives by discussing the roles of the metaverse. Subsequently, the invited contributors discuss their views on vital opportunities, challenges and research agenda concerning the metaverse.

With the widespread metaverse, it is expected that each key area identified is likely to undergo significant levels of disruption. Against this backdrop, this paper contributes to the academic literature and industry by gathering different perspectives from invited contributors on the relevance of the metaverse in marketing and logistics domains.

The purpose of this paper is to develop an approach to measure business sustainability in food service operations. The main objectives are to understand the concepts of business sustainability and, after constructing a framework based on a literature review, to assess the relation between the proposed framework and the empirical case study in a fast food retailer chain.

In order to examine the applicability of the proposed framework, focus group interview and face-to-face interviews were conducted. Additionally, some other secondary data such as official websites or company reports were also used to support the interview results.

Finding of the research result has shown most of the factors of business sustainability employed to measure sustainability food service operations are supported.

This study contributes to the literature by showing that environmental and social sustainability are significantly recognized in the corporation. More importantly, through the data analysis, a new factor of social sustainability, namely, community contribution has been found. The contribution of this paper is certainly applicable to other food service operations who wish to achieve a good degree of business sustainability.

China is the only major economy in the world that has achieved positive gross domestic product (GDP) growth in 2020. The paper aims to explore the effect of China's public policy restarting supply and consumption after coronavirus disease-2019 (COVID-19).

Affected by the epidemic, global economic growth slowed down. Using the stock price data of Chinese A-share listed company, combining natural experiment and event study method, the paper examines the policy effects of work resumption and consumer vouchers.

Compared with demand capacity, the work resumption has a more significant role in promoting the supply industry. Issuing consumer vouchers can effectively promote local demand recovery, and the effect is mainly concentrated in the industries involved in consumption vouchers. At the same time, public management capacity and the income level of residents play an important role in restarting supply and demand.

Understanding China's public policies and effects are of positive significance to the restoration of economic development in other countries.

The study contributes to knowledge by empirically examining the effect of China's public policies against the COVID-19 pandemic. The paper also expands the scope of policy-oriented research based on the perspective of supply and demand capacity building.

Robots, as the crystallization of new artificial intelligence, are being applied in various fields, especially the hotel industry. They are seizing the opportunities, using technology to improve the overall quality and comprehensive competitiveness. However, they also cause many problems due to practical limitations. The purpose of this paper is to study customers' recognition and acceptance of hotel service robots to guide the successful promotion of this technology.

This paper proposed a comprehensive model based on the theory of planned behavior, the technology acceptance model and then the perceived value-based acceptance model. Exploratory factor analysis, confirmatory factor analysis, grouped regression analysis and path analysis was adopted to validate the impacts of each variable to obtain the final reliable model using data collected from hotel guests using a self-designed questionnaire.

The empirical research based on the theoretical model shows that the constructed conceptual model can thoroughly explain the influencing factors of hotel robot acceptance, enrich the acceptance theory and provide academic support for the use and popularization of hotel service robots. Among all variables, attitude, usefulness and perceived value are the factors that have the greatest impact on acceptance. They have significant differences in the effects of adjustment variables such as gender, educational level, whether hotel robots have been used, and whether other robot services have been experienced on different paths in the model.

This paper explored the customer acceptance of service robots in hotels, helped to understand the process of decision-making on service robot selection and contributed to the theoretical extension of the hospitality industry. The work guides hotel management to promote better-personalized products and services of robot technology in the hospitality industries.

The acceptance study on hotel service robots provides insight into the hotel industry to understand customers' attitudes and acceptance of emerging technology.

The purpose of this paper is to analyse consumer purchasing behaviour in different cultural settings by exploring the value of consumer reviews from various countries.

This study uses online review mining technology to collect, process and analyse user review data from multiple countries. The main procedures of this research are data collection, data pre-processing, feature extraction and sentiment analysis. Online reviews from the American, British and Indian websites for the iPhone 5s are analysed.

Every country has unique cultural characteristics, and these cultural differences affect consumers’ perceptions, attitudes and purchasing behaviours. The results show that consumers from different countries exhibit different levels of attention towards the same product and have different emotional inclinations for the same product feature. In addition, the study also identified the advantages and disadvantages of the product.

The user reviews provide abundant feedback information that serves as a good intelligence resource for companies. Under the premise of different language habits, this paper uses a universal approach to analyse consumer behaviour from online reviews in different countries, which can help reveal consumers’ emotional inclination towards each feature of a product. This approach can be extended to other brands of mobile phones or other industries.

Multinational companies should analyse the cultural characteristics of target groups when proposing transnational development strategies. Companies can understand the perceptions of their products based on the consumer reviews and can formulate their marketing and product strategies by considering consumer purchasing behaviours arising from cultural differences.

This study identifies differences in consumer behaviour in different cultural settings by using a data mining method, which can help companies understand consumer perceptions and the performance and quality of product features.

The purpose of the paper is to identify the multiple types of data that can be collected and analyzed by practitioners across the cold chain, the ICT infrastructure required to enable data capture and how to utilize the data for decision making in cold chain logistics.

Content analysis based literature review of 38 selected research articles, published between 2000 and 2016, was used to create an overview of data capture, technologies used for collection and sharing of data, and decision making that can be supported by the data, across the cold chain and for different types of perishable food products.

There is a need to understand how continuous monitoring of conditions such as temperature, humidity, and vibration can be translated to support real-time assessment of quality, determination of actual remaining shelf life of products and use of those for decision making in cold chains. Firms across the cold chain need to adopt appropriate technologies suited to the specific contexts to capture data across the cold chain. Analysis of such data over longer periods can also unearth patterns of product deterioration under different transportation conditions, which can lead to redesigning the transportation network to minimize quality loss or to take precautions to avoid the adverse transportation conditions.

The findings need to be validated through further empirical research and modeling. There are opportunities to identify all relevant parameters to capture product condition as well as transaction data across the cold chain processes for fish, meat and dairy products. Such data can then be used for supply chain (SC) planning and pricing products in the retail stores based on product conditions and traceability information. Addressing some of the above research gaps will call for multi-disciplinary research involving food science and engineering, information technologies, computer science and logistics and SC management scholars.

The findings of this research can be beneficial for multiple players involved in the cold chain like food processing companies, logistics service providers, ports and wholesalers and retailers to understand how data can be effectively used for better decision making in cold chain and to invest in the specific technologies, which will suit the purpose. To ensure adoption of data analytics across the cold chain, it is also important to identify the player in the cold chain, which will drive and coordinate the effort.

This paper is one of the earliest to recognize the need for a comprehensive assessment for adoption and application of data analytics in cold chain management and provides directions for future research.