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The purpose of this paper is to understand the effect of online cross-recommendation of products from e-retailers on consumers’ instant cross-buying intention, and compare the effect between the contexts that the decision making on focal product is difficult and easy.

Based on the information adoption model, this paper develops a theoretical model to investigate how online cross-recommendation of products from e-retailers influence consumers’ instant cross-buying intention. Empirical data were collected from 224 online shoppers. The Partial Least Squares technique was used to test the proposed research model.

Choice confidence on focal product and perceived usefulness of cross-buying is the antecedents of instant cross-buying intention. Brand awareness of recommended product, one-stop shopping convenience, and perceived price advantage are the antecedents of perceived usefulness of cross-buying and choice confidence on focal product when the decision making on focal product is difficult, whereas brand awareness is not when it is easy to make focal product decision. Choice confidence on focal product positively affects perceived usefulness of cross-buying when it is easy to make focal product decision, whereas the effect is not significant when the decision making on focal product is difficult.

Knowledge about the effect of online cross-recommendation of products on instant cross-buying intention is scarce. This study reveals the psychological mechanism of the effect of online cross-recommendation of products on consumers’ instant cross-buying intention and finds that decision-making difficulty on focal product is an important moderator.

Robotic chefs are starting to replace human chefs in restaurant industry. Whether customers have a good food quality prediction may have an important effect on their patronage decision. Based on the stereotype content model, the purpose of this paper is to investigate the impact of robotic chef anthropomorphism on food quality prediction through warmth and competence.

An empirical analysis was done to test the theoretical model by using the SmartPLS software. A nonhuman-like robotic chef and a robotic chef with humanoid hands were used as background materials in the questionnaire. The effective sample was 221.

Robotic chef anthropomorphism affects food quality prediction through the sequential mediators of warmth and competence. Age is a significant control variable.

Robotic chef anthropomorphism positively affects food quality prediction. The halo effect of warmth perception on competence perception should be considered in the context of robot anthropomorphism.

Restaurants which feature robotic chefs should use robotic chefs with anthropomorphic designs and promote the anthropomorphic elements of robotic chefs in advertisements.

The anthropomorphic design of robot chefs will facilitate the development of artificial intelligence in restaurants in the future.

To the best of the authors’ knowledge, this paper is one of the first to focus on how robotic chef anthropomorphism affects food quality prediction and reveals the roles of warmth and competence in the influence of robotic chef anthropomorphism on food quality prediction.

With the development of location-based services and mobile phones, local retailing stores have the opportunity to send location-based advertisings (LBAs) to consumers at a right time and right place. However, knowledge about the influence of LBAs on consumers’ store patronage is limited. The purpose of this paper is to understand how the content of LBAs influences consumers’ store patronage intention. In particular, the paper investigates the influence of perceived accuracy and transaction cost reduction from the content of LBAs on consumers’ store patronage intention through the emotional reactions of pleasure and arousal.

This study developed a theoretical model to examine how the content of LBAs influences the store patronage intention of consumers. Empirical data were collected from 351 undergraduate and graduate students. The partial least squares technique was used to test the research model.

Perceived accuracy and transaction cost reduction from the content of LBAs have a significant influence on the store patronage intention of consumers through pleasure and arousal. Brand image and purchase plan are control variables.

Knowledge about the influence of LBAs on consumer store patronage is limited. This study provides empirical evidence about how perceived accuracy and transaction cost reduction from the content of LBAs affect the emotional reactions of consumers and then determine their store patronage intention.

Robot chefs and robot waiters have emerged in the restaurant industry. Based on the curiosity theory and the stimulus–organism–response paradigm, this study aims to understand the influence of robot restaurant attributes on customer behavioral intention before purchase.

Based on research data from 289 respondents comprising undergraduates, postgraduates and non-students in China, the theoretical model is tested via the partial least squares technique.

Food quality perception directly affects regular patronage intention, but it has no significant influence on experience intention. Service quality perception and high-tech atmosphere perception positively affect experience intention and regular patronage intention through the mediator of interest in robot restaurants.

Different from previous studies focusing on human employee restaurants, this study, to the best of the authors’ knowledge, is the first to systematically investigate the influence of robot restaurant attributes on customer behavioral intention, and it finds that these attributes have their own uniqueness vis-à-vis influencing customer behavioral intention.

机器人厨师和机器人服务员已经出现在餐饮业。基于好奇心理论和刺激-有机体-反应模型, 本研究旨在了解机器人餐厅属性对顾客购买前行为意向的影响。

基于来自中国289名本科生、研究生和非学生的研究数据, 通过偏最小二乘法对理论模型进行了检验。

食品质量感知直接影响常客意愿, 但对体验意愿没有显着影响。服务质量感知和高科技氛围感知通过对机器人餐厅的兴趣作为中介变量正向影响体验意愿和常客意愿。

与以往专注于人类员工餐厅的研究不同, 本研究首次系统地研究了机器人餐厅属性对顾客行为意图的影响, 并发现这些属性在影响顾客行为意图方面具有其独特性。

机器人餐厅, 体验意向, 惠顾意向, 食物品质, 服务质量, 氛围

研究型论文

The purpose of this paper is to understand how free gifts with purchase influence the purchase satisfaction of online consumers, and compares the difference between the contexts, which the consumers are certain and uncertain with the free gifts before purchase.

This study developed a theoretical model to examine how free gifts with purchase influence the purchase satisfaction of online consumers. The moderating effect of uncertainty was also examined. Using a survey questionnaire, empirical data were collected from 288 Taobao users. The partial least squares technique was used to test the proposed research model.

Perceived usefulness, perceived quality, perceived cost, and perceived ingenuity are antecedents of happiness toward a free gift with purchase. Happiness has a positive effect on the purchase satisfaction of online consumers. Uncertainty is an important moderator.

The findings extend the current state of knowledge about the relationship between online purchase with free gifts and purchase satisfaction, as well as reveal the psychological mechanism of the effects of online purchase with free gifts on purchase satisfaction.

The findings of this study provide e-retailers with a deep understanding of how free gifts with purchase affect the purchase satisfaction of online consumers in different presentation approaches of the gifts.

Knowledge about the role of free gifts with purchase on the purchase satisfaction of online consumers is scarce. This study provides empirical evidence about the effect of free gifts with purchase on the purchase satisfaction of online consumer in different presentation approaches of the gifts.

Although supplier-initiated punishment is widely used to manage distributors’ opportunism, its spillover effect on unpunished distributors (i.e. observers) within the same distribution network remains under-researched. Specifically, this paper aims to investigate the curvilinear effect of punishment severity on an observer’s opportunism, and how such an effect is contingent on the observer’s network position.

This paper uses regression analysis with survey data gathered from 218 distributors in China’s automobile industry.

Punishment severity has an inverted U-shaped effect on the observers’ opportunism, and such effect is weakened by both the observers’ network centrality and their degree of dependence on the supplier.

The findings should encourage suppliers to focus more on the spillover effects of punishment on observers. To this end, the supplier must deliberately initiate the appropriate level of punishment severity against its distributors because an inappropriate level of punishment severity (e.g. too lenient) may unexpectedly raise the unpunished observers’ level of opportunism. Moreover, the supplier should be fully aware that observers’ specific network positions may produce varying spillover effects of the punishment.

This study enriches the literature on channel governance by revealing the curvilinear mechanism through which punishment severity influences observers’ opportunism. By applying social learning theory to channel punishment research, this study unveils both the inhibitive learning and the imitative learning forces inherent in a single punishment event, and it delineates their joint effect on an observer’s opportunism. In addition, this study outlines the observer’s vertical and horizontal relationships within the distribution network and explores their contingent roles in determining the spillover effects of punishment.

Information and communication technologies (ICTs) are a key player in the food services and restaurants sector; thus, the aim of this work consists in studying the previous research on ICTs in food services and restaurants in the context of tourism and hospitality through a systematic literature review.

The systematic literature review is performed on full papers published in journals included in the Journal Citation Report of the WoS in the category of Hospitality, Leisure, Sport and Tourism. A total of 165 articles from 28 journals are analyzed, following different criteria, such as the research methods, perspectives, statistical techniques, geographical focus, topics, technologies, authors and universities.

The restaurant sector is more and more based on the creation of experiences and ICTs, through their multiple possibilities, can undoubtedly contribute to adding value to the simple meal and create and recreate experiences to attract and retain customers who are increasingly sophisticated and hooked on ICTs. ICTs are basic for managers taking decision at the highest level in food services and restaurants, so ICTs should not be seen as a technical tool but as an essential element for top management.

This paper examined articles from very well-known tourism and hospitality journals, leaving aside others as well as different publication formats such as books or papers presented at conferences.

A significant contribution made with this paper is the availability of a list of topics in the context of ICTs in food services and restaurants. These topics are classified into three areas (Consumers, Suppliers and Environment and Tendencies) that can serve as a future research framework. The paper also provides useful information to restaurant managers about ICTs, to researchers for their future projects and to academics for their courses.

Although studies have investigated reasons for software as a service (SaaS) adoption, it is unclear how firm-level SaaS use impacts future SaaS intentions. The purpose of this paper is to propose a theoretical model that integrates the technology-organization-environment framework, institutional theory, diffusion-of-innovation theory and the opportunity-risk framework to analyze the drivers of SaaS use and its continuance intention.

The authors evaluated the direct, moderating and mediating effects of determinants on SaaS continuance intentions using structural equation modeling and data from 301 firms.

Results found that top management support and normative pressures influenced SaaS use. Cost saving and security concerns were direct predictors of perceived opportunities and perceived risks, respectively. Perceived opportunities and risks and actual SaaS use influenced SaaS continuance. Interestingly, perceived opportunities were found to be a negative moderator on the relationship between SaaS use and SaaS continuance.

The results reveal insightful and controversial findings for SaaS research.

The recent COVID-19 outbreak and severe natural disasters make the design of the humanitarian supply chain network (HSCN) a crucial strategic issue in a pre-disaster scenario. The HSCN design problem deals with the location/allocation of emergency response facilities (ERFs). This paper aims to propose and demonstrate how to design an efficient HSCN configuration under the risk of ERF disruptions.

This paper considers four performance measures simultaneously for the HSCN design by formulating a weighted goal programming (WGP) model. Solving the WGP model with different weight values assigned to each performance measure generates various HSCN configurations. This paper transforms a single-stage network into a general two-stage network, treating each HSCN configuration as a decision-making unit with two inputs and two outputs. Then a two-stage network data envelopment analysis (DEA) approach is applied to evaluate the HSCN schemes for consistently identifying the most efficient network configurations.

Among various network configurations generated by the WGP, the single-stage DEA model does not consistently identify the top-ranked HSCN schemes. In contrast, the proposed transformation approach identifies efficient HSCN configurations more consistently than the single-stage DEA model. A case study demonstrates that the proposed transformation method could provide a more robust and consistent evaluation for designing efficient HSCN systems. The proposed approach can be an essential tool for federal and local disaster response officials to plan a strategic design of HSCN.

This study presents how to transform a single-stage process into a two-stage network process to apply the general two-stage network DEA model for evaluating various HSCN configurations. The proposed transformation procedure could be extended for designing some supply chain systems with conflicting performance metrics more effectively and efficiently.