Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

Revisiting the ICAPM under the distortion of risk–return tradeoff in short-horizon stock returns

We suggest that the distortion of the positive risk–return relation in the ICAPM is a consequence of trading by informed investors to exploit mispricing. We hypothesize and demonstrate that a non-positive (strongly positive) risk–return relation following positive (negative) market returns is attributed to short-selling (purchasing) of overpriced (underpriced) stocks along with optimistic (pessimistic) expectations conditional on good (bad) market news. We verify this asymmetry in the risk–return relation through the indirect risk–return relation conditional on good (bad) market news. We also find that the attenuation (reinforcement) of the positive risk–return relation is more profound in high- (low-) sentiment periods.     

Assessing customer passion,commitment, and word-of-mouth intentions in digital assistant usage: The moderating role of technology anxiety

Consumers develop a passion for the use of innovations, which is a critical determinant of their success. Research has largely examined drivers of initial acceptance of digital assistants (DAs) and has yet to fully understand the factors driving or deterring consumers’ passion towards DAs and the behavioural outcomes. Drawing on the stimulus-organism-response framework, this study examines a unique set of factors (usefulness, ease of use, privacy concern, and localisation) that act as stimuli to drive an organismic state of passion for DAs, and how this produces behavioural responses of word-of-mouth (WOM) intention and commitment to DA use. The study also examines how technology anxiety moderates passion’s impact on WOM intentions and commitment. The findings show that usefulness, ease of use, privacy concern, and localisation are significant explanatory variables of consumers’ passion towards DAs. Furthermore, passion towards DAs results in WOM intentions and commitment to its use. The findings further show that passion’s effect on DAs in explaining WOM intentions and commitment is weakened by technology anxiety. Lastly, passion is the mediating mechanism through which usefulness, ease of use, privacy concern, and localisation impact WOM intentions and commitment. The implications of these findings for theory and practice are highlighted.     

Place attachment,host–tourist interactions,and residents’ attitudes towards tourism development: the case of Boa Vista Island in Cape Verde

A clear understanding of residents’ attitudes towards tourism development and its determinants is a crucial pillar for designing tourism development strategies to promote sustainable development. The literature on the influence of host–tourist interactions and place attachment on residents’ attitudes towards tourism development in developing countries is still scarce. To extend knowledge in this field, this study aims at developing and testing a structural model to examine direct and indirect causal effects of place attachment, host–tourist interaction, and perceived positive and negative tourism impacts on the residents’ attitudes towards tourism development in an island tourism destination – Boa Vista Island in Cape Verde. Results suggest that the residents’ attitudes are positively affected by place attachment, host–tourist interaction, and perceived positive impacts; and negatively affected by perceived negative impacts. Host–tourist interaction emerges as the strongest (direct and indirect) determinant of the residents’ attitudes towards tourism development. Moreover, although both positive and negative perceptions of tourism impacts have significant impacts on the residents’ attitudes, the influence of the former is stronger than that of the latter. The paper ends with relevant theoretical and practical implications to promote positive residents’ attitudes towards tourism development in Boa Vista.     

Tourists’ hotel event experience and satisfaction: an integrative approach

ABSTRACT

Tourists’ hotel event experiences have received little attention in tourism research. By proposing an integrated model of expectation–confirmation theory (ECT) and the experience economy concept, this research explores the relationship between tourists’ event experience and their satisfaction regarding the hotel event setting. The hypothesized model was empirically validated using a sample of 663 tourists who experienced a holiday event at a resort hotel. Results confirmed that the integration of the experience economy and ECT provided a better understanding of tourists’ post-satisfaction in a pleasure-driven setting. This affective–cognitive approach advances the knowledge of tourists’ experiences and satisfaction at hotel events.     

Persistence of Price–Cost Margin and Technical Efficiency in the Indonesian Food and Beverage Industry

Abstract

This research investigates the persistence of price–cost margin (PCM) and technical efficiency (TE) of firms and the relation between these two factors in 44 subsectors of the Indonesian food and beverage industry in the period 1980–2014. Data envelopment analysis with a bootstrapping approach is applied to estimate TE. An autoregressive model, accounting for endogeneity, is applied to estimate the persistence coefficients of PCM and TE. A cross-sectional regression model is also applied to estimate the relation between the persistence of the PCM and the persistence of TE. The results show that for these food and beverage firms, high PCM and low TE persist. Furthermore, the persistence of PCM negatively affects the persistence of TE in the industry.     

Institutional quality,investment efficiency,and the choice of public–private partnerships

We examine a sample of 625 public–private partnership (PPP) firms from 1980 to 2015 that straddle nine countries with varying degrees of economic development and PPP markets. We find that the motivations of the firms that undertake PPP investments vary. While private sector firms in economies with low institutional quality choose to engage in PPPs to alleviate capital constraints attributed to underinvestment, those in economies with high institutional quality participate in PPPs to solve the problem of overinvestment due to an abundant cash flow. In the long run, the benefits of lower capital constraints through PPP investments are more pronounced in economies with high institutional quality.     

Factor state–space models for high-dimensional realized covariance matrices of asset returns

We propose a dynamic factor state–space model for high-dimensional covariance matrices of asset returns. It makes use of observed risk factors and assumes that the latent integrated joint covariance matrix of the assets and the factors is observed through their realized covariance matrix with a Wishart measurement density. For the latent integrated covariance matrix of the assets we impose a strict factor structure allowing for dynamic variation in the covariance matrices of the factors and the residual components as well as in the factor loadings. This factor structure translates into a factorization of the Wishart measurement density which facilitates statistical inference based on simple Bayesian MCMC procedures making the approach scalable w.r.t. the number of assets. An empirical application to realized covariance matrices for 60 NYSE traded stocks using the Fama–French factors and sector-specific factors represented by Exchange Traded Funds (ETFs) shows that the model performs very well in- and out of sample.     

Modelling distribution of aggregate expenditure on tourism

The aim of this article is to obtain a statistical distribution that describes the aggregate expenditure of tourists related to their length of stay at a given location. This distribution enables us to estimate two parameters simultaneously; one controls the length of stay and the other, the expense incurred. We propose two distribution models, for which closed-form expressions are obtained. Covariates are introduced in order to study the factors that affect the aggregate expenditure. The results obtained indicate that the models achieve a reasonably good fit, with and without covariates.     

Impacts of peer-to-peer accommodation on the hotel industry: Hoteliers’ perspectives

The sharing economy is a new phenomenon that has considerable implications for traditional industries in general and the hospitality sector in particular. Although some recent studies have investigated the effects of sharing economy on the hotel industry, they primarily focused on quantifying its effects which are not exploratory for a phenomenon. This study attempts to achieve two research objectives. First, an exploratory qualitative method via a semi-structured in-depth interview is employed to investigate the impacts of P2P accommodation on the industry from hoteliers’ perspectives in China. Second, the current study provides valuable insights about traditional hotel marketing and operations. A social science perspective is proposed because prior hospitality research, merely in its commercial sense, fails to capture the essence of hospitality. Results indicate that P2P accommodation has effects on the hotel industry in terms of host–guest interactions, product offerings, staff empowerment, and platform collaboration. The study also suggests that the extent to which P2P accommodation impacts the hotel industry is different in terms of hotel star ratings and operating model. P2P accommodation and the hotel industry in China have a supplementary relationship. This study contributes to social studies of the hospitality literature by gaining insights from hotel senior management level. It also has great implications for the hotel marketing and management practices within the sharing context.