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In contrast to existing studies, this paper aims to propose that digital transformation does not depend on a single condition; rather, it depends on the interaction between internal and external factors of a firm. Therefore, the aim of this paper is to examine the effect of a combination of internal and external factors on a firm's digital transformation intention.

An empirical analysis on a sample of 112 Chinese small- and medium-sized firms was conducted by applying smart-PLS and fuzzy set qualitative comparative analysis (fsQCA).

The results of smart PLS show that external pressures (institutional and market pressures) and human capital have a positive impact on corporate digital transformation intentions. From a combination perspective, the results of the fsQCA show that there are five causal conditions that lead to high digital transformation intention. In contrast to the net effect, the results of fsQCA show that different combinations of states of internal (human capital, organizational culture and technological capital) and external elements (institutional and market pressures) of the firm are likely to stimulate digital transformation intention.

This study provides empirically based insights into firms' digital transformation intentions and advances the current understanding of the drivers and inhibitors of digital transformation. Unlike most current research, which tends to focus on the net effect of factors influencing the digital transformation of enterprises, this study focuses on identifying the core elements influencing enterprises' digital transformation intention, especially the joint effect of different factors, both internal and external to the enterprise. The combined SEM and fsQCA findings of this paper not only enrich the existing theories on digital transformation but also have high value in guiding the digital transformation of firms.

Building on the three-factor theory, this study aims to unravel how the role of hotel attributes such as basic, excitement and performance factors could differ in accordance with different hotel star ratings and distinct customer segments.

This study explores the asymmetric effects of hotel attributes on customer satisfaction by extracting 412,784 consumer-generated reviews from TripAdvisor across different cities in China.

By taking into account the origins of customers and hotel star ratings, the study uncovers that guests’ expectations of hotel performance differ with respect to their origins (domestic and international guests) and the star ratings of the hotels being reviewed, thereby moderating the asymmetric impact of hotel attributes on customer satisfaction.

The study compares and contrasts the determinants of customer satisfaction for domestic and international guests in the context of Chinese hotels. Care should still be exercised when generalizing the insights gleaned from this study to other contexts.

The findings from this study translate into actionable guidelines for hotel operators to make informed decisions regarding service improvement.

The study extends previous work by offering a deeper understanding of the asymmetric impact of hotel attributes on customer satisfaction. Specifically, this study provides a deep understanding of the different hotel attributes such as basic, performance and excitement factors in explaining customer satisfaction among different hotel customer segments. Findings from this study can not only inform hotel operators on the significance of various hotel attributes in determining customer satisfaction but also guide the formulation of business strategies to retain customers by inducing delight and not frustration.

Word‐of‐mouth (WOM) has been found to significantly influence consumers' decision making. Much attention has been paid to the effect of WOM characteristics such as the number of postings, the dispersion of online conversations, the reputation of the reviewers, and the review quality on product sales. Little research, however, has examined the interaction process of online reviews. The purpose of this paper is to investigate the consumers' product attitude formation process in online WOM. Three research questions will be addressed in this paper, i.e. the effect of prior responses on the following repliers' product attitude, the negativity effect and the role of main messages in shaping consumers' product attitude formation process.

The product attitude formation process of online WOM is investigated using the data of product reviews (main messages) and their corresponding responses. The paper collected 26 product reviews from various web sites and kept the first 40‐50 responses for each review, which resulted in 26 main messages and 1,173 observations (i.e. responses) in total. A hierarchical Bayesian ordinal choice model is then specified and estimated with the Markov Chain Monte Carlo method to address the research questions and to capture the main message heterogeneity.

The paper finds that the impact of prior responses (e.g. the proportion of positive and negative responses) on the product attitudes of the following responses differs significantly across products. This heterogeneity can be well explained by the characteristics of the main messages at the second‐level specification. Thereby, factors that influence consumers' product attitudes in the interaction process of online WOM include prior responses and main message characteristics. Another interesting finding is that positive responses have larger impacts on product attitudes than negative ones.

This research contributes to both academic research and the firms' online WOM management. Theoretically, this research is the first attempt to examine the formation process of attitudes toward new products in online communications. This research contributes by modeling how the dynamic process of online WOM influences new product attitudes. Furthermore, inconsistent with the “negativity effect” proposed by researchers (e.g. Skowronski and Carlston), the paper finds that positive responses matter more than negative ones in online communications. In addition, the way the paper configures the data for online communications is innovative and provides a perspective to quantitatively model the communication process. Managerially, this research provides implications for firms to intervene in the online communication process and influence consumer attitude of new products.

While previous research has demonstrated the positive effects of digital business strategies on operational efficiency, financial performance and value creation, little is known about how such strategies influence innovation performance. To address the gap, this paper aims to investigate the impact of a firm’s digital business strategy on its innovation performance.

Drawing on the dynamic capability view, this study examines the mechanism through which a digital business strategy affects innovation performance. Data were collected from 215 firms in China and analyzed using multiple regression and structural equation modeling.

The empirical analysis reveals that a firm’s digital business strategy has positive impacts on both product and process innovation performance. These impacts are partially mediated by knowledge-based dynamic capability. Additionally, a firm’s digital business strategy interacts positively with its entrepreneurial orientation in facilitating knowledge-based dynamic capability. Moreover, market turbulence enhances the strength of this interaction effect. Therefore, entrepreneurial-oriented firms operating in turbulent markets can benefit more from digital business strategies to enhance their knowledge-based dynamic capabilities and consequently improve their innovation performance.

This study contributes to the understanding of how a firm’s digital business strategy interacts with entrepreneurial orientation in turbulent markets to shape knowledge-based dynamic capability, which in turn enhances the firm’s innovation performance.

The purpose of this paper is to describe and discuss the use of Chinese medicine in the prevention and treatment of coronavirus disease 2019 (COVID-19) in China and Asia.

This paper provides a brief overview of the COVID-19. Based on the syndrome differentiation (辨證論治), the concept of clearing heat and detoxifying lung in traditional Chinese medicine is used to prevent and treat COVID-19 through restoring the vital qi (正氣) in human body and regulating the lung as well as spleen to strengthen the immune system. Traditional Chinese medicine has been used as a complementary therapy for the possible intervention of COVID-19 including traditional Chinese herbal decoctions, Chinese traditional patent medicines, acupuncture and moxibustion as well as the traditional health exercises in China and parts of Asia.

Traditional Chinese medicine plays a significant role in the prevention and treatment of COVID-19 pandemic. The infection cases of China are around 80,000 and a steady decline compared with the USA which has 5,000,000 infection cases and continuous increases. It is shown that more than 90% of patients recovered after the treatment of traditional Chinese herbal decoctions and Chinese traditional patent medicines without any side-effect compared to the use of Remdesivir (GS-5734). Acupuncture (針灸) and moxibustion (艾灸) stimulate the immune and nervous systems for preventing infectious diseases. Taichi (太極) and Baduanjin (八段錦) as the auxiliary aerobic exercise under the theory of Chinese medicine can enhance the immune system and improve the lung function. Thus, an integration of traditional Chinese Medicine and Western medicine is the best strategy for the prevention, treatment and control of COVID-19 pandemic in the future.

This paper describes traditional Chinese medicine as an effective way for the prevention and treatment of COVID-19.

This paper explores the role of traditional Chinese medicine (TCM) as a tourism recovery drawcard to boost China's inbound tourism after COVID-19.

This paper employed a mixed method involving a cross-disciplinary literature review along with reflections from experts in TCM and health communication to inform tourism management. Specifically, this paper examines TCM and its potential benefits as a medical tourism drawcard to combat COVID-19. The selected literature focusses on the image and merits of TCM to frame how this medical philosophy can be used to position China as a tourist destination. Reflections on the use of TCM as a tourism marketing tool can guide promotional strategies from the Chinese government and destination managers during and after COVID-19.

The Chinese government, the tourism industry (e.g. destination managers), the media and tourists must focus on three aspects of the role of TCM: to provide medical benefits to travellers amid COVID-19 and beyond, elevate China as a destination for global medical tourists and be leveraged as a tool for economic recovery.

The paper builds a tourism recovery framework for stakeholders to adopt tailored TCM communication strategies to boost its inbound tourism programme.

This paper is the first academic paper to review TCM comprehensively and critically in relation to China tourism and post-COVID-19 recovery measures.

The paper aims to develop an alternative valuation model for money‐back guarantees (MBG) using a real‐option approach and examine the validity of the proposed model with an experimental design. This study attempts to address how retailers appropriately price MBG from a consumer value‐based viewpoint.

The study defines the perceived post‐purchase product value as a stochastic underlying process, and then MBG option value could be theoretically determined by the real‐option pricing approach. For the test of the real‐option perspective on MBG, a 2×2×2 factorial experimental design is conducted to examine the empirical effects.

With model specification, the study investigated the effects of three key factors, i.e. price level, perceived risk level, and consumers' risk‐aversion, which are characterized by a two‐sided effect on MBG option value. The relationships among those factors also are clarified through theoretical analyses. The empirical results could be explained well by the proposed model.

Faced with increasingly competitive market, retailers typically need more sophisticated pricing strategies. The study can offer retailers a more comprehensive understanding of consumers' perceived value of MBG in various situations and thereby suggest some management implications for the MBG pricing issue.

The purpose of this study is to investigate the understanding and application of crime of sabotaging production and operation in internet era, and, at the same time, discuss the basic position for criminal law interpretation in cyberspace.

Doctrinal analysis and case study.

Along with the advent of the internet era, how to apply the traditional crime of sabotaging production and operation in virtual space has attracted people’s attention. The controversy caused by the conviction of malicious application of fake transactions is a typical example. The legal interest protected here includes not only the property value of the means of production itself, but also the expectation interest that can be obtained by normal production and operation activities. There is no reliable basis to believe that overlap of articles between special provision and general laws occurs in crime of sabotaging production and operation and crime of intentional damage of property. The production and operation activities carried out online can also be covered by crime of sabotaging production and operation, without doubt. Ejusdem Generis Rule should be fully respected, but crime of sabotaging production and operation has a dual structure of means behavior and purpose behavior, where the purpose behavior, sabotaging production and operation, is the key to the conviction. However, it is not necessarily premised on physical damage and violent characteristics. The understanding and application of traditional crimes should keep pace with the times in the internet era, and we should not stick to a completely rigid subjective interpretation.

This study demonstrates the possible application of crime of sabotaging production and operation in cyberspace, and clarifies many misunderstandings about this crime.

This study aims to explore the determinants of public debt in selected South Asian Association for Regional Cooperation (SAARC) countries for 19 years, from 2001 to 2019.

Using ordinary fixed and random effect models, the authors examine the role of internal and external factors in determining the composition of public debt. Furthermore, for robustness, they compare the results with two-stage least square (2SLS) regression estimates after considering the problem of endogeneity, overidentification, under-identification and weak instruments.

The findings show that among the selected macroeconomic variables, inflation, exchange rate and broad money have significant negative effects on the debt-GDP ratio. In contrast, military spending, corruption and interest rates appear to positively influence the same as per 2SLS results. From the policymaking perspective, SAARC countries should focus more on reducing military spending and make a concerted effort to augment investments in productive projects. Further, with strong fiscal consolidation and institutional quality, it is important to mitigate the frequent occurrence of corruption conundrums in emerging economies for the development of a transparent economic system.

The study is distinct from previous studies in two ways. First, to the best of the authors’ knowledge, there are no studies focusing on SAARC countries in the context of public debt. Second, the study expands the existing literature on public debt by taking into account both external and internal debts to decipher the within-country and cross-country determinants of debt accumulation. More specifically, this model considers accountability and transparency in the public sector, cross-border security challenges and benefits of globalization by including explanatory variables such as corruption, military expenditure spending and capital inflows.

Housing prices in China have increased rapidly over the past decade. Motivated by the fact that the real estate market and bank credit scale are vastly different in Chinese cities, the purpose of this paper is to compare the impact of bank credit on house prices in first- and second-tier cities in China.

In this study, a panel data method was used to investigate 19 first-tier cities and 30 second-tier cities between the period 2003 and 2018.

The empirical analysis undertaken in this study found that bank credit was relevant to house prices but varied in different cities in which house prices in second-tier cities tended to be more affected by bank credit compared to those in first-tier cities. In contrast, population was found to be a dominant factor that influenced house prices in first-tier cities. Likewise, the factors, per capita and gross domestic product, were found to exert a significant influence on house prices in first- and second-tier cities.

This paper provided numerous policies to control the price of housing in first- and second-tier cities.

The housing prices, bank credit scale and population distribution are vastly different in different cities in China. This research considers these differences while examining the dominant factors that affect house prices in first- and second-tier cities in China.