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Successful sensorless collision detection by a robot depends on the accuracy with which the external force/torque can be estimated. Compared with collaborative robots, industrial robots often have larger parameter values of their dynamic models and larger errors in parameter identification. In addition, the friction inside a reducer affects the accuracy of external force estimation. The purpose of this paper is to propose a collision detection method for industrial robots. The proposed method does not require additional equipment, such as sensors, and enables highly sensitive collision detection while guaranteeing a zero false alarm rate.

The error on the calculated torque for a robot in stable motion is analyzed, and a typical torque error curve is presented. The variational characteristics of the joint torque error during a collision are analyzed, and collisions are classified into two types: hard and soft. A pair of envelope-like lines with an effect similar to that of the true envelope lines is designed. By using these envelope-like lines, some components of the torque calculation error can be eliminated, and the sensitivity of collision detection can be improved.

The proposed collision detection method based on envelope-like lines can detect hard and soft collisions during the motion of industrial robots. In repeated experiments without collisions, the false alarm rate was 0 per cent, and in repeated experiments with collisions, the rate of successful detection was 100 per cent. Compared with collision detection method based on symmetric thresholds, the proposed method has a smaller detection delay and the same detection sensitivity for different joint rotation directions.

A collision detection method for industrial robots based on envelope-like lines is proposed in this paper. The proposed method does not require additional equipment or complex algorithms, and highly sensitive collision detection can be achieved with zero false alarms. The proposed method is low in cost and highly practical and can be widely used in applications involving industrial robots.

The purpose of this paper is to present the state-of-the-art E-commerce logistics in supply chain management by investigating worldwide implementations and corresponding models together with supporting techniques via furniture industry.

Typical E-commerce logistics companies from North America, Europe, and Asia Pacific are comprehensively investigated so as to get the lessons and insights from these practices.

Future technologies like Internet of Things, Big Data Analytics, and Cloud Computing would be possibly adopted to enhance the E-commerce logistics in terms of system level, operational level, and decision-making level that may be real time and intelligent in the next decade.

This paper takes the furniture industry for example to illustrate the E-commerce logistics and supply chain management (LSCM). Other industries like electronic appliance industry are not considered.

Opportunities and future perspectives are summarized from practical implementations so that interested parties like E-commerce and logistics companies are able to get some guidance when they are contemplating the business.

E-commerce is booming with the development of new business models and will be continuously boosted in the near future. With large number of enterprises carrying out E-commerce, logistics has been largely influenced.

Insights and lessons from this paper are significant for academia and practitioners for considering E-commerce LSCM.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

As a standard source of capital for entrepreneurs, crowdfunding has recently gained wide attention in business and academia. With scientific endorsement, some research is conducted to explore the antecedents of online crowdfunding success. The factors that can influence the backers’ investment which is the key to success are information from prior backers’ and creators’ behaviors. Based on the signaling theory, the purpose of this paper is to systematically investigate the dynamic influences and interaction effects of signals with different forms (action-based or opinion-based signals) and sources (creator-sourced or backer-sourced signals) on backers’ investment behaviors over a project-funding cycle.

A panel data set of 3,010 projects with 640,625 transaction records from April 28, 2013 to September 31, 2017 is collected from a famous online crowdfunding platform – Zhongchou.cn in China and the negative binomial panel data model with fixed effect is used to obtain our empirical results.

The findings demonstrate that the work of different signals is significantly effective at the early stage of a project and decreases with time. Furthermore, our results show that there are both synergistic effect and substitution effect among different signals. Specifically, the direction of interaction effect depends on the forms of signals and the backers’ sensitivity toward that signal, and the interaction effects are also dynamic.

This paper has shed light on the roles of different signal types and their interactions in influencing funding behavior over a project-funding cycle, enriched the literature on crowdfunding and provided both theoretical and practical implications.

area E-Business; Corporate Strategy; Strategic Management; Operation Management.

level/applicability Senior undergraduate; MBA; EMBA.

overview After development for 10 years, JD was now China’s second largest business-to-customer (B2C) e-retailer and the largest in self-operated sector. It was September 2015 when Liu Qiangdong was deciding whether to persist with JD’s self-operated model and the heavy investment in the self-built logistics system. JD’s business model had been functioning well. However, as JD grew bigger and bigger, it became too expensive to expand its logistics system. JD had not made a profit since it raised funds from investors. Liu had to come up with a good proposal before the next monthly meeting to convince them that JD would finally overtake its biggest rival, Alibaba which ran on a different business model. In addition, JD was exploiting the rural and the global markets, as well as a new business in internet finance. Facing challenges and dilemmas, should JD persist with its model? How could Liu align short-term profitability with long-run development? How could JD overcome attacks from Alibaba and other competitors?

learning outcomes This case is appropriate for courses in e-business and strategy, particularly those with a strong focus on doing e-business in emerging markets (e.g. China). After studying the case, students should be able to: understand the e-commerce market in China; understand business models and key strategies of e-retailers; identify and analyse the pros and cons of the self-operated business model and self-built logistics system in e-commerce; learn how to evaluate performance, strategies and business models of e-commerce companies; and extract key trends in the market and compare different strategies.

materials Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 11: Strategy.

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.

E-commerce live streaming is a new influencer advertising method that allows influencers to interact directly with consumers on e-commerce platforms. Although evidence suggests that influencer live-streaming advertisements (ads) on social media can increase consumers’ buying impulses, little research examined how this similar but new advertising method on e-commerce platforms may influence consumers’ urge to buy impulsively. This study explores the role of influencer credibility, celebrity effect, perceived entertainment, trust and perceived usefulness on consumers’ attitudes toward influencer ads and their urge to buy impulsively.

A questionnaire containing seven constructs was developed and distributed to participants using a convenient sample and snowball sampling approach. The constructs were measured based on validated measurement items from the literature and adjusted according to this study’s focus. A total of 236 valid responses were obtained from the survey and used for data analysis. A partial least squares structural equation modeling approach was employed for parameter estimation and model testing.

The empirical results show that all constructs influenced consumers’ urge to buy impulsively via attitude toward influencer ads. The proposed research model explains 61.7% of the variance in attitude toward influencer ads and 19.4% of the urge to buy impulsively.

This is an early study investigating the relationship between influencer advertising and impulse buying. The results provide valuable insights into improving the design of influencer ads and marketing strategies.

1. I-eIB model tests the mechanism of influencer ads on consumers’ buying impulse.

2. Consumers’ attitude towards influencer ads affects their urge to buy impulsively.

3. Influencer credibility affects consumer attitude via celebrity effect as a mediator.

4. Trust affects consumer attitude via perceived usefulness as a mediator.

5. Entertaining ads help develop favorable consumer attitude.

I-eIB model tests the mechanism of influencer ads on consumers’ buying impulse.

Consumers’ attitude towards influencer ads affects their urge to buy impulsively.

Influencer credibility affects consumer attitude via celebrity effect as a mediator.

Trust affects consumer attitude via perceived usefulness as a mediator.

Entertaining ads help develop favorable consumer attitude.

Cybersecurity and data protection concerns have gained notoriety in past years intensified by the Facebook-Cambridge Analytica “scandal” in early 2018, which exposed millions of individual data. This case revealed that both regulatory measures and data protection mechanisms were, and still are, insufficient, with several countries reforming or promulgating new legislation. The Article 19 EU General Data Protection Regulation (GDPR) contains controversial extra-territorial provisions, which might violate State Sovereignty principles. It is still unknown how the GDPR will be implemented. This chapter reveals data protection as an Ethics discipline, considering that it is a fundamental right of individuals to share or not to share data, vis-á-vis the rights to have the personal data well-protected. The empirical research will be developed based on the need to build up a concept of Responsible Entrepreneurship in the technology sector, applied to cross-border e-commerce. The Digital Silk Road is the case study selected since it represents a complex international cooperation initiative done without institutionalization yet with eminent data surveillance concerns when building network infrastructure and satellite navigation systems.

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