Dr Senmao Xia

This research analyzes managers’ perceptions of the multiple types of artificial intelligence (AI) required at each stage of the business-to-business (B2B) service recovery journey for successful human-AI collaboration in this context. Study 1 is an exploratory study that identifies managers’ perceptions of the main stages of a B2B service recovery journey based on human-AI collaboration and the corresponding roles of the human-AI collaboration at each stage. Study 2 provides an empirical examination of the proposed theoretical framework to identify the specific types of intelligence required by AI to enhance performance in each stage of B2B service recovery, based on managers’ perceptions. Our findings show that the prediction stage benefits from collaborations involving processing-speed and visual-spatial AI. The detection stage requires logic-mathematical, social, and processing-speed AI. The recovery stage requires logic-mathematical, social, verbal-linguistic, and processing-speed AI. The post-recovery stage calls for logic-mathematical, social, verbal-linguistic, and processing-speed AI.

The visitor economy is responsible for a substantial percentage of the global carbon footprint. The mechanisms used to decarbonize it are insufficient, and the industry is relying on carbon trading with substandard credits that allow businesses to outsource the responsibility to decarbonize. We aim to transform carbon markets, help finance climate investments, and support decarbonization strategies. We identify and define the problem, outline the components and their interactions, and develop a conceptual model to transform carbon markets. The new, blockchain-based Carbon Tokenomics Model rolls out a decentralized database to store, trade, and manage carbon credits, with the goal of enabling sustainable climate finance investment. We outline the criteria needed for an industry-wide carbon calculator. We explain the process needed to increase rigor in climate investments in the visitor economy and introduce a delegated Proof of Commitment consensus mechanism. Our inclusive and transparent model illustrates how to reduce transaction costs and how to build consumer and industry trust, generating much-needed investments for decarbonization.

A virtual influencer (VI) is a computer-generated, imagery-based digital character. It has become one of the hottest marketing trends, motivating researchers to investigate how consumers perceive VIs. However, consumers’ emotional attachment and benefit seeking behaviour to different types of VIs has remained under-investigated. Therefore, considering the level of perceived humanness and appearance realism, this research examines how consumers’ emotional attachment and benefit seeking differs across the three types of VI (i.e., mimic-human VI, animated-human VI, and non-human VI). We further propose that VIs may influence consumer emotional attachment and different benefit seeking behaviour through social presence because, specifically, when a VI shows a higher level of social presence, a higher level of emotional attachment and stronger benefit seeking behaviour will result. The experimental studies lend support to our theorization. This research provides insights into the different types of VIs in marketing literature and extends the context of social presence theory.

Purpose Previous experience is a critical factor affecting entrepreneurial activities; however, it has not been fully studied in the existing literature. This study attempts to comprehensively reveal the routes and mechanisms of occupational experience that affect entrepreneurial activities and assess the entrepreneurial potential of different occupational practitioners. Design/methodology/approach By matching occupational characteristics with entrepreneurs' competence, this study proposes ten hypotheses about how occupational experience affects entrepreneurial entry and performance. This empirical study is based on the Occupational Information Network database and Chinese survey data. Factor and regression analyses were used in the empirical research. Findings This study verifies that different occupational practitioners have varied entrepreneurial potential. Occupational experience, including occupational uncertainty, market contact and social capital, gained from previous experience significantly affects entrepreneurial entry. Meanwhile, occupational characteristics, including management experience, marketing experience, social capital, financial capital, risk-taking ability and creativity, accumulated from previous experience, have a significant impact on entrepreneurial performance. Originality/value This study is a pioneering attempt to reveal the relationship between occupational experience and entrepreneurial activities. The transmission mechanism of previous experiences affecting entrepreneurial activities is comprehensively revealed by relaxing the assumption of a representative occupation. These findings provide a theoretical foundation for empirical evidence and have important practical value.

Strategic alliance theories have been studied widely over the past few decades. However, their key arguments may face new limitations and challenges brought by emerging technologies such as big data analytics capability (BDAC). This paper aims to identify the challenges BDAC brings to strategic alliance theories and the associated changes to strategic alliance research. Specifically, this paper systematically reviews and identifies how BDAC challenges the key arguments in the strategic alliances' theories through the lens of three stages of strategic alliances: formation, governance and achieving alliance performance. Meanwhile, this study also finds some changes in strategic alliance research brought by BDAC. Finally, this study proposes promising directions for future research on strategic alliances under the influences of BDAC.

The popularity of the circular economy attracts more attention to balance environmental and economic impacts. Many supply chain remanufacturing firms have started to use the cash flow to invest in cost-reduction technologies to increase profits. However, the uncertainty of cash flow significantly affects the technology investment effectiveness, and therefore, some firms attempt to adopt cash hedging strategies to mitigate the uncertainty. This study investigates the impacts of cash hedging on remanufacturing firms' profits and the environment through the lenses of cost-reduction technologies investments. The proposed nonlinear programming models were drawn on cash hedging and risk management theory. Empirical regression analysis was conducted using longitudinal datasets of listed Chinese remanufacturing firms for ten years ranging from 2010 to 2019. Different from the traditional wisdom which argues that cash hedging has a single effect (i.e., positive, negative, or no impact) on corporate economic performance, this paper's results indicate that the impact of cash hedging on corporate profits varies in different conditions; Further, this study is one of the first to identify some interesting conditions, in which cash hedging can bring along remanufacturing firms with profits while protect environment. This study provides insightful suggestions for the manufacturer's and government's policy design.

Creativity is key for organizations’ ability to remain relevant in today's disruptive world. In this paper, we identify new ways in which organizations can use artificial intelligence (AI) more effectively for creativity. Drawing on the resource-based view as a background mechanism, we developed and empirically tested a new integrative model. We collected the research data via a large survey of managers distributed to 600 organizations in China. Our findings show that coupling AI capability with strategic agility can directly support creativity. It also mediates the effects of ambidexterity, customer orientation and competitor orientation on organizations’ creativity and performance when developing new products and services. In addition, our findings show that coupling AI capability and strategic agility can significantly improve firms’ new product creativity and new service development performance when there is a high level of government institutional support. Our findings provide theoretical and practical implications for academics and practitioners interested in managing AI for organizational creativity.

The unprecedented COVID‐19 pandemic required millions of people across the world to become remote workers. However, little is known about how to achieve effective remote working for organizations. This study investigates the types of employees that are more suited to accepting remote working by considering two determinants: gender and internet skills. Based on an official data set from China, this study reveals that females are more likely to accept remote working, as are those employees with advanced internet skills. This study further investigates the impacts of perceived benefits on employees’ acceptance of remote working. It appears that the preference of females for remote working is attributed to avoiding face-to-face interaction rather than free time planning. This study is among the first to reveal how skill matching matters in order to be successful remote workers. Meanwhile, this study indicates that it is gender-specific psychological differences rather than the division of labor in families that motivate females to accept remote working, an important observation which has been neglected so far. The findings are helpful for employers and employees in the post-pandemic era.