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This study aims to investigate whether the increasing robot adoption will affect employment rate and wages to contribute to the economic cycle and sustainable development in the world.

The authors introduce a two-way fixed effect model and ordinary least-squares (OLS) model to evaluate the influence based on relevant data of the eighteen countries with the largest robot stocks and robot densities in the world from 2006 to 2019 to test the influences and do the robustness test and endogeneity test by using empirical models.

The authors’ research findings suggest that increasing robot adoption can cause strong negative impacts on employment for both males and females in these economies. Second, the effect of robots on reducing job opportunities has penetrated different industries. It means that this negative impact of robots is comprehensive for the industry. Third, robot adoption can have a strong positive influence on wages and increase workers' incomes.

The limitations of the study are that the influence of industrial intelligence technologies on the circular economy is diversities in different countries. Thus, this study should consider the development levels of different economies to do additional confirmatory studies.

This study makes out the correlations between industrial robots and the employment market from the circular economy perspective. The result proves the existence of this influence relationship, and the authors propose some suggestions to promote sustainable economic development.

This paper addresses the activity of industrial intelligence technologies in the labor market. The employment market is an important part of the circular economy, and it will benefit social development if the government provides appropriate guidance for social investment and industrial layout.

This study is one of the few studies which considered the impact of industrial robots on employment and wages from the perspective of different industries, and this is very important for the circular economy in the world. The results of this paper provide an instructive reference for government policymakers and other countries to stabilize the labor market and optimize human resources for sustainable economic development.

The purpose of this paper is to simulate the tension process of tension-type anchor cable and to explore the mechanical characteristics and tension-torsion coupling effect of anchor cable subjected to tension.

ABAQUS numerical software is applied to construct the numerical models of tension-type anchor cables with different diameters. Through explicit contact, the characteristics of contact between grouting body-anchor cable and grouting body-rock mass are determined. Confining pressure is applied to the model through surface pressure, and drawing force is applied to the model by displacement loading so as to simulate the tension process of the anchor cable.

The results show that the stress is transmitted in both axial and radial directions in the anchorage section and distributed in a cone. The shear stress in the grouting body is unevenly distributed, and its peak value increases with the rise in confining pressure and anchor cable diameter. The stress characteristics of torque and axial force are basically consistent and evenly distributed in the free section; they gradually decrease in the anchorage section. Due to the tension-torsion coupling effect, the internal stress characteristics of the anchor cable structure vary. On average, the anchorage performance of each anchor cable model is improved by 6.19%.

The proposed method of numerical modelling is effective in addressing the interface contact between the anchor cable and the grouting body and in solving the problem with convergence of calculation. Compared with the indoor test, this method is more suited to collecting the internal mechanical data of the anchor body.

Artificial intelligence (AI) technology has revolutionized customers' interactive marketing experience. Although there have been a substantial number of studies exploring the application of AI in interactive marketing, personalization as an important concept remains underexplored in AI marketing research and practices. This study aims to introduce the concept of AI-enabled personalization (AIP), understand the applications of AIP throughout the customer journey and draw up a future research agenda for AIP.

Drawing upon Lemon and Verhoef's customer journey, the authors explore relevant literature and industry observations on AIP applications in interactive marketing. The authors identify the dilemmas of AIP practices in different stages of customer journeys and make important managerial recommendations in response to such dilemmas.

AIP manifests itself as personalized profiling, navigation, nudges and retention in the five stages of the customer journey. In response to the dilemmas throughout the customer journey, the authors developed a series of managerial recommendations. The paper is concluded by highlighting the future research directions of AIP, from the perspectives of conceptualization, contextualization, application, implication and consumer interactions.

New conceptual ideas are presented in respect of how to harness AIP in the interactive marketing field. This study highlights the tensions in personalization research in the digital age and sets future research agenda.

This paper reveals the dilemmas in the practices of personalization marketing and proposes managerial implications to address such dilemmas from both the managerial and technological perspectives.

This is one of the first research papers dedicated to the application of AI in interactive marketing through the lenses of personalization. This paper pushes the boundaries of AI research in the marketing field. Drawing upon AIP research and managerial issues, the authors specify the AI–customer interactions along the touch points in the customer journey in order to inform and inspire future AIP research and practices.

The purpose of this study is to examine how the childhood trauma experiences of CEOs influence firms’ internationalization.

The research used a difference-in-difference method with constructing a treatment group whose chief executive officer (CEO) experienced the great famine in China between the ages of 7 and 11, and a control group whose CEO was born within three years after 1961.

The study reveals a significant inverse correlation between CEOs’ childhood trauma experiences and firm internationalization. However, this correlation is weaker in the case of state-owned enterprises and firms led by CEOs with overseas work experience.

To the best of the authors’ knowledge, this study is the first to extend the theoretical framework to elucidate firms’ internationalization by introducing childhood trauma theory into the field of international business literature. Second, the authors link the literature on the effect of CEO explicit traits and psychological traits on firm internationalization by exploring how CEOs’ childhood trauma experience shapes their risk aversion, which, in turn, influences firm internationalization. Third, the authors address the call for examining the interplay of CEO life experiences by scrutinizing the moderating effect of CEO overseas work experience on the association between CEOs’ childhood trauma exposure and firm internationalization.

This paper aims to provide feasible countermeasures for the application of lean manufacturing in automatic sand casting workshops to optimize production line balance.

A production line balance optimization model for sand casting workshops is proposed. The value stream mapping (VSM) approach is applied to diagnose the problems in the production process. An optimization scheme is established based on eliminate, combine, rearrange, simplify and increase theory and Kanban management method. Further, simulation is done to compare current VSM and future VSM.

After implementing the proposed model, findings indicated that the idle time of equipment was effectively reduced, the line of balance of the production line was increased by 44.7%, the production lead time was shortened by 60.3% and the production capacity was increased by 50.0%.

Application of the optimization model in this study is limited to sand casting workshops that have realized automatic or semi-automatic production.

This paper provides an optimization model for the implementation of lean manufacturing in sand casting workshops and provides a reference case that reflects the actual application of lean manufacturing tools in a real situation.

Based on virtual maintenance, this paper aims to propose a time prediction method of assembly and disassembly (A&D) actions of product maintenance process to enhance existing methods’ prediction accuracy, applicability and efficiency.

First, a framework of A&D time prediction model is constructed, which describes the time prediction process in detail. Then, basic maintenance motions which can comprise a whole A&D process are classified into five categories: body movement, working posture change, upper limb movement, operation and grasp/placement. A standard posture library is developed based on the classification. Next, according to motion characteristics, different time prediction methods for each motion category are proposed based on virtual maintenance simulation, modular arrangement of predetermined time standard theory and the statistics acquired from motion experiment. Finally, time correction based on the quantitative evaluation method of motion time influence factors is studied so that A&D time could be predicted with more accuracy.

Case study of time prediction of products’ various A&D processes is conducted by implementing the proposed method. The prediction process of diesel cooling fan disassemble time is presented in detail. Through comparison, the advantages and effectiveness of the method are demonstrated.

This paper proposes a more accurate, efficient and applicable product A&D time prediction method. It can help designers predict A&D time of a product maintenance accurately in early design phases without a physical prototype. It can also provide basis for the verification of maintainability, the balance of the design of product structure and system layout.

In recent years, the textile industry has been required to develop new methods and technologies through introduction of some new materials in various processes rather than employing the same conventional chemicals. The aim of this research was to investigate the changes induced on the cotton fibre by the nanoclay treatment using a pre‐treatment method.

The fibres were dyed with basic and direct dyes after the nanoclay pre‐treatment. Technical measurements were studied including Fourier‐transform infrared spectroscopy (FTIR), UV‐visible spectrophotometer, differential scanning calorimetry (DSC), thermal degradation analysis (TGA), scanning electron microscopy (SEM), moisture regain measurement (MRM), tensile strength test (TST), reflectance spectroscopy (RS) and fastnesses evaluation.

The intensity of the major peaks in FTIR spectra of the nanoclay treated sample is in favour of the chemical changes of the cellulose functional groups. Basic dyes showed a higher dyeability on the clay pre‐treated samples compared to raw materials. The results of the colour measurements showed that the more concentration of the clay mineral was used, the darker the colour of the dyed sample was. Some interesting results were obtained in the research.

The nanoclay and a dispersing agent used in the present context were used as received. Besides, the type of the dispersing agent is important for preparation of a colloidal dispersion of nanoclay.

The method developed in this research provides a simple and practical solution for improving the dyeability of cotton with direct and basic dyes.

The method for enhancing the dyeability of cotton is novel and can be used in cotton processing with new properties.

In this age of extremely well-developed social media, it is necessary to detect any change in the corporate image of an enterprise immediately so as to take quick action to avoid the wide spread of a negative image. However, existing survey-based corporate image evaluation methods are costly, slow and static, and the results may quickly become outdated. User comments, news reports and we-media articles on the internet offer varied channels for enterprises to obtain public evaluations and feedback. The purpose of this study is to effectively use online information to timely and accurately measure enterprises’ corporate images.

A new corporate image evaluation method was built by first using a literature review to establish a corporate image evaluation index system. Next, an automatic text analysis of online public information was performed through a topic classification and sentiment analysis algorithm based on the dictionary. The accuracy of the topic classification and sentiment analysis algorithm is then calculated. Finally, three internet enterprises were chosen as cases, and their corporate image was evaluated.

The results show that the author’s corporate image evaluation method is effective.

First, in this study, a new corporate image evaluation index system is constructed. Second, a new corporate image evaluation method based on text mining is proposed that can support data-driven decision-making for managers with real-time corporate image evaluation results. Finally, this study improves the understanding of corporate image by generating business intelligence through online information. The findings provide researchers with specific and detailed suggestions that focus on the corporate image management of emerging internet enterprises.

This paper examines the mediating process of enhancing employees' psychological ownership among family hotel employees.

A total of 1,005 employees from 197 budget-to-three-star family hotels took part in the study by completing an either self-reported or interviewer questionnaire. The respondents were selected using a convenient sampling technique. A partial least square structural equation was used to analyse the data.

Work engagement and organisational performance were shown to significantly predict psychological ownership, except for counterproductive work behaviour. Both counterproductive work behaviour and organisational performance were found to predict psychological ownership. Finally, the relationship between (1) counterproductive work behaviour and psychological ownership and (2) organisational performance and psychological ownership is mediated by work engagement.

Replication of this model in different countries and other work settings is highly recommended for cross validating the reported findings in this study. The study emphasises the need for family hotel owners to create a conducive work environment devoid of conditions that promote counterproductive work behaviour among employees and encourage them to engage in higher productivity.

This study appears to be one of the first to have investigated a model linking counterproductive work behaviour, performance to psychological ownership through work engagement in the family hotel context.