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Carp is a traditional aquaculture fish with decreasing relevance in European markets. Despite this, it is a protein source which could contribute to the worldwide protein supply. Traditional carp ponds are part of human cultural heritage with high relevance for biodiversity. But, market shares of carp are small compared to other seafood market, mainly due to low consumer demand. The aim of this research was to contribute to the discussion on how to increase demand for carp by testing the acceptance of selected preprocessed carp products.

A quantitative online survey was conducted in Germany and Poland with the aim of identifying consumers' attitudes towards carp and carp products. On this basis recommendations on how to best market carp products are developed.

Carp is perceived to be a fish eaten primarily at Christmas and New Year's Eve and to be difficult to prepare. The analyses reveal that a potential for novel carp products does exist in Germany and in Poland. The wider introduction of a bonecut filet to the market, a better availability of carp products, and the avoidance of off-flavors are important prerequisites for higher market relevance of carp.

In this research consumer preferences were elicited “theoretically” by showing pictures of carp products and asking them for their preferences. In this regard, the results presented here state a general consumer interest and a potential for new carp products. Further research, integrating product tastings might give additional information on the likely success of new types of carp products.

In order to let people know about the new products and at the same time to combat the sometimes existent bad image of carp, product tastings, also in combination with information regarding local origin and environmental/cultural impact, should be offered at the point of sale.

Carp is a highly sustainable fish and offers a valuable protein source for human consumption. But, in its common ways of market presentation it is not highly appreciated by consumers. This paper demonstrates options of overcoming this situation.

This study aims to develop an educational tourism demand model, particularly in respect to dynamic effects, university quality (QU) and competitor countries. Educational tourism has been identified as a new tourism sub-sector with high potential, and is thus expected to boost economic growth and sustainability.

This study reviews the literature on the determinants of educational tourism demand. Even though the existing literature is intensively discussed, mostly focusing on the educational tourism demand from an individual consumer's perspective, this study makes an innovation in line with the aggregate demand view. The study uses data that consist of the enrolment of international students from 47 home countries who studied in Malaysia from 2008 to 2017. The study utilised the dynamic panel method of analysis.

This study affirms that income per capita, educational tourism price, price of competitor countries and quality of universities based on accredited programmes and world university ranking are the determinants of educational tourism demand in both the short and the long term. Also, a dynamic effect exists in educational tourism demand.

The results imply that government should take the quality of services for existing students, price decisions and QU into account to promote the country as a tertiary education hub and achieve sustainable development.

Research on the determinants of the demand for educational tourism is rare in terms of macro data, and this study includes the roles of QU, competitor countries and dynamic effects.

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.

Chinese beer consumption has undergone major changes within the last decade. The combination of a growing middle class and greater exposure to foreign products has resulted in a significant increase in beer imports. The authors examined transformations in this market and how beer preferences have changed over time. This study focuses on changes is origin-specific preferences (e.g. German beer and Mexican beer) as reflected by habit formation (i.e. dynamic consumption patterns) and changes in demand sensitivity to expenditure and prices.

The authors estimated Chinese beer demand – differentiated by source – using a generalized dynamic demand model that accounted for habit formation and trends, as well as the immediate and long-run effects of expenditures and prices on demand. The authors employed a rolling regression procedure that allowed for model estimates to vary with time. Preference changes were inferred from the changing demand estimates, with a particular focus on changes in habit formation, expenditure allocating behaviour, and own-price responsiveness.

Results suggest that Chinese beer preferences have changed significantly over the last decade, increasing for Mexican beer, Dutch beer and Belgian beer. German beer once dominated the Chinese market. However, all indicators suggest that German beer preferences are declining.

Although China is the world's third largest beer importing country behind the United States and France. Few studies have focused on this market. While dynamic analyses of alcoholic beverage demand are not new, this is the first study to examine the dynamics of imported beer preferences in China and implications for exporting countries.

This study investigated factors in the retail supply chains that were disrupted by the flow of the product distribution process from suppliers to retail stores and finally to consumers during the COVID-19 pandemic.

This qualitative study involved 12 key informants from two manufacturing industries and three retail industries in Indonesia. Meanwhile, the analysis of empirical conditions employed qualitative content analysis to discover facts of the inbound and outbound supplies in retail supply chains.

This study revealed high demands for certain products and a shift in consumer purchase trends during the pandemic screwed merchandising planning in retail stores. These conditions have brought continuous impacts on the production processes of manufacturing industries that also faced constrained raw material supplies. Container shortage in the global supply chain has increasingly aggravated the crisis of retail supply chains. 10;

Retailers and all related parties are ready to anticipate the changing of the supply chain by preparing strategies to overcome the crisis.

A contribution is made to the global retail supply chain in times of crisis and can serve as a framework for further research in each region.

The literature review aims to facilitate a broader understanding of on-demand service platform operations management and proposes potential research directions for scholars.

This study searches four databases for relevant literature on on-demand service platform operations management and selects 72 papers for this review. According to the research context, the literature can be divided into research on “a single platform” and research on “multiple platforms”. According to the research methods, the literature can be classified into “Mathematical Models”, “Empirical Studies”, “Multiple Methods” and “Literature Review”. Through comparative analysis, we identify research gaps and propose five future research agendas.

This paper proposes five research agendas for future research on on-demand service platform operations management. First, research can be done to combine classic research problems in the field of operations management with platform characteristics. Second, both the dynamic and steady-state issues of on-demand service platforms can be further explored. Third, research employing mathematical models and empirical analysis simultaneously can be more fruitful. Fourth, more research efforts on the various interactions among two or more platforms can be pursued. Last but not least, it is worthwhile to examine new models and paths that have emerged during the latest development of the platform economy.

Through categorizing the literature into two research contexts as well as classifying it according to four research methods, this article clearly shows the research progresses made so far in on-demand service platform operations management and provides future research directions.

Radical changes in consumer habits induced by the coronavirus disease (COVID-19) pandemic suggest that the usual demand forecasting techniques based on historical series are questionable. This is particularly true for hospitality demand, which has been dramatically affected by the pandemic. Accordingly, we investigate the suitability of tourists’ activity on Twitter as a predictor of hospitality demand in the Way of Saint James – an important pilgrimage tourism destination.

This study compares the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) time-series model with that of the SARIMA with an exogenous variables (SARIMAX) model to forecast hotel tourism demand. For this, 110,456 tweets posted on Twitter between January 2018 and September 2022 are used as exogenous variables.

The results confirm that the predictions of traditional time-series models for tourist demand can be significantly improved by including tourist activity on Twitter. Twitter data could be an effective tool for improving the forecasting accuracy of tourism demand in real-time, which has relevant implications for tourism management. This study also provides a better understanding of tourists’ digital footprints in pilgrimage tourism.

This study contributes to the scarce literature on the digitalisation of pilgrimage tourism and forecasting hotel demand using a new methodological framework based on Twitter user-generated content. This can enable hospitality industry practitioners to convert social media data into relevant information for hospitality management.

2019冠狀病毒病引致消費者習慣有根本的改變; 這些改變顯示，根據歷史序列而運作的慣常需求預測技巧未必是正確的。這不確性尤以受到大流行極大影響的酒店服務需求為甚。因此，我們擬探討、若把在推特網站上的旅遊活動視為聖雅各之路 (一個重要的朝聖旅遊聖地) 酒店服務需求的預測器，這會否是合適的呢?

本研究比較 SARIMA 時間序列模型與附有外生變數 (SARIMAX)模型兩者在預測旅遊及酒店服務需求方面的表現。為此，研究人員收集在推特網站上發佈的資訊，作為外生變數進行研究。這個樣本涵蓋於2018年1月至2022年9月期間110,456個發佈資訊。

研究結果確認了傳統的時間序列模型，若涵蓋推特網站上的旅遊活動，則其對旅遊需求方面的預測會得到顯著的改善。推特網站的數據，就改善預測實時旅遊需求的準確度，或許可成為有效的工具; 而這發現對旅遊管理會有一定的意義。本研究亦讓我們進一步瞭解朝聖旅遊方面旅客的數碼足跡。

現存文獻甚少探討朝聖旅遊的數字化，而本研究不但在這方面充實了有關的文獻，還使用了一個根據推特網站上使用者原創內容嶄新的方法框架，進行分析和探討。這會幫助酒店從業人員把社交媒體數據轉變為可供酒店管理之用的合宜資訊。

At present, the Chinese economy has entered the “new normal” phase with the transformation of development stages from the low-income to the middle-income ones. Accordingly, there appear a series of innovations in development theories. Innovations involve creative destructions. Therefore, innovative development theories at the present stage either deny the prevailing principles of development economics, or deny the theories that once effectively guided development at the low-income stage, or even sublate some of the development polices which were propelled and proved effective at the beginning of the reform and opening-up. The fundamental reason is that, as the development stages evolve, there occur new development tasks, new periodical characteristics and new laws of development. The paper aims to discuss these issues.

Any development theory from abroad will find it difficult to correctly guide and clarify development problems in a socialist country, such as the huge population and the extreme imbalance between the urban and the rural and among regional developments.

In conclusion, China, as a large world economy, has made innovations in its economic development theory, which indicates that it intends to perfect itself rather than seek hegemony. As the world’s second largest economy, China should adapt to the transformation and further free people’s minds instead of adhering to the old patterns of thinking. It should think over the path of development for a great world economy from the historical starting point of a large world economy and find development strategies to transform itself from a large economy to a great economy, so as to realize the dream of the Chinese nation to build a powerful country.

Only political economy studies both the relations of production and the productive forces, and only a theory combining both can correctly guide China’s economic development, which especially needs to be promoted by taking advantage of socialist economic system. Therefore, the first and foremost principle for a socialist political economy with Chinese characteristics is to insist on liberating and developing productive forces.