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The purpose of this paper is to propose and demonstrate a new additive manufacturing approach that breaks the layer-based point scanning limitations to increase fabrication speed, obtain better surface finish, achieve material flexibility and reduce equipment costs.

The freeform additive manufacturing approach conceptually views a 3D article as an assembly of freeform elements distributed spatially following a flexible 3D assembly structure, which conforms to the surface of the article and physically builds the article by sequentially forming the freeform elements by a vari-directional vari-dimensional capable material deposition mechanism. Vari-directional building along tangential directions of part surface gives surface smoothness. Vari-dimensional deposition maximizes material output to increase build rate wherever allowed and minimizes deposition sizes for resolution whenever needed.

Process steps based on geometric and data processing considerations were described. Dispensing and forming of basic vari-directional and vari-dimensional freeform elements and basic operations of joining them were developed using thermoplastics. Forming of 3D articles at build rates of 2-5 times the fused deposition modeling (FDM) rate was demonstrated and improvement over ten times was shown to be feasible. FDM compatible operations using 0.7 mm wire depositions from a variable exit-dispensing unit were demonstrated. Preliminary tests of a surface finishing process showed a result of 0.8-1.9 um Ra. Initial results of dispensing wax, tin alloy and steel were also shown.

This is the first time that both vari-directional and vari-dimensional material depositions are combined in a new freeform building method, which has potential impact on the FDM and other additive manufacturing methods.

This paper utilizes the improved particle swarm optimization (IPSO) with bounded constraints technique on velocity and positioning for adjusting the gains of a proportional-integral-derivative (PID) and iterative learning control (ILC) controllers. The purpose of this paper is to achieve precision motion through bettering control by this technique.

Actual platform positioning must avoid the occurrence of a large control action signal, undesirable overshooting, and preventing out of the maximum position limit. Several in-house experiments observation, the PSO mechanism is sometimes out of the optimal solution in updating velocity and updating position of particles, the system may become unstable in real-time applications. The proposed IPSO with new bounded constraints technique shows a great ability to stabilize nonminimum phase and heavily oscillatory systems based on new bounded constraints on velocity and positioning in PSO algorithm is evaluated on one axis of linear synchronous motor with a PC-based real-time ILC.

Simulations and experiment results show that the proposed controller can reduce the error significantly after two learning iterations. The developed method using bounded constraints technique provides valuable programming tools to practicing engineers.

The proposed IPSO-ILC-PID controller overcomes the shortcomings of conventional ILC-PID controller with fixed gains. Simulation and experimental results show that the proposed IPSO-ILC-PID algorithm exhibits great speed convergence and robustness. Experimental results confirm that the proposed IPSO-ILC-PID algorithm is effective and achieves better control in real-time precision positioning.

In this “Info-plosion” era, recommendation systems (or recommenders) play a significant role in finding interesting items in the surge of online digital activity and e-commerce. The purpose of this paper is to model users' preference evolution to recommend potential items which users may be interested in.

A novel recommendation system, namely evolution-learning recommendation (ELR), is developed to precisely predict user interest for making recommendations. Differing from prior related methods, the authors integrate the matrix factorization (MF) and recurrent neural network (RNN) to effectively describe the variation of user preferences over time.

A novel cumulative factorization technique is proposed to efficiently decompose a rating matrix for discovering latent user preferences. Compared to traditional MF-based methods, the cumulative MF could reduce the utilization of computation resources. Furthermore, the authors depict the significance of long- and short-term effects in the memory cell of RNN for evolution patterns. With the context awareness, a learning model, V-LSTM, is developed to dynamically capture the evolution pattern of user interests. By using a well-trained learning model, the authors predict future user preferences and recommend related items.

Based on the relations among users and items for recommendation, the authors introduce a novel concept, virtual communication, to effectively learn and estimate the correlation among users and items. By incorporating the discovered latent features of users and items in an evolved manner, the proposed ELR model could promote “right” things to “right” users at the “right” time. In addition, several extensive experiments are performed on real datasets and are discussed. Empirical results show that ELR significantly outperforms the prior recommendation models. The proposed ELR exhibits great generalization and robustness in real datasets, including e-commerce, industrial retail and streaming service, with all discussed metrics.

This study investigated the mediating role of job satisfaction and the moderating role of career growth opportunity in the relationship between public service motivation (PSM) and public employees' turnover intention.

The authors recruited 587 public employees from Yunnan Province, China to test moderation and mediation hypotheses. The authors conducted confirmatory factor analysis to determine the discriminant and convergent validity of the measures of PSM, turnover intention, job satisfaction and career growth opportunity. Finally, the authors carried out bootstrapping to ascertain direct, indirect and conditional indirect effects.

PSM had a negative effect on public employees' turnover intention, but this relationship was partially mediated by job satisfaction. Career growth opportunity moderated the association between job satisfaction and turnover intention. In particular, the indirect effect of PSM on turnover intention through job satisfaction weakened under high career growth opportunities.

The results highlighted the significance of PSM and career growth opportunity in shaping public employees' work-related attitudes and behaviors. Public organizations should consider PSM a key criterion in recruitment and selection and pay more attention to the significance of intervening in career growth to satisfy public employees' psychological needs related to individual career development.

This study contributes to the literature on the disputed link between PSM and turnover intention and uncovered the underlying mechanism through which PSM affects public employees' turnover intention by proposing job satisfaction and career growth opportunity as a mediator and moderator, respectively.

Tourism spot or point-of-interest (POI) recommendation has become a common service in people's daily life. The purpose of this paper is to model users' check-in history in order to predict a set of locations that a user may soon visit.

The authors proposed a novel learning-based method, the pattern-based dual learning POI recommendation system as a solution to consider users' interests and the uniformity of popular POI patterns when making recommendations. Differing from traditional long short-term memory (LSTM), a new users’ regularity–POIs’ popularity patterns long short-term memory (UP-LSTM) model was developed to concurrently combine the behaviors of a specific user and common users.

The authors introduced the concept of dual learning for POI recommendation. Several performance evaluations were conducted on real-life mobility data sets to demonstrate the effectiveness and practicability of POI recommendations. The metrics such as hit rate, precision, recall and F-measure were used to measure the capability of ranking and precise prediction of the proposed model over all baselines. The experimental results indicated that the proposed UP-LSTM model consistently outperformed the state-of-the-art models in all metrics by a large margin.

This study contributes to the existing literature by incorporating a novel pattern–based technique to analyze how the popularity of POIs affects the next move of a particular user. Also, the authors have proposed an effective fusing scheme to boost the prediction performance in the proposed UP-LSTM model. The experimental results and discussions indicate that the combination of the user's regularity and the POIs’ popularity patterns in PDLRec could significantly enhance the performance of POI recommendation.

Prior studies have extensively explored individual examples of unethical behavior in sales organizations but focused little on repeated violation (RV) of ethical codes, particularly when managers develop salesforces. Based on social learning theory (SLT), the authors propose a multilevel model of RV antecedents and suggest that organizational influence (social cues and modeling) and individual factors (observer characteristics and behavioral outcomes) affect RV, especially with increasing recruitment of salespeople.

Using data from a leading financial company in Taiwan, the authors analyzed 1,231 records of salespeople’s misbehavior through logistic regression and average marginal effects.

Modeling in the organization (i.e. peer misconduct), observer characteristics (i.e. experience concerning job tenure and prior violations) and behavioral outcomes (i.e. information concealment violations) were all found to affect the likelihood of RV, and the interactional effect of organizational size was confirmed.

This study contributes to ethical decision-making theory by explaining aspects of RV through SLT. Its multilevel model, integrated with organizational strategy theories, adds an SLT-focused paradigm into unethical behavior research by considering vicarious learning and self-learning, alongside the reciprocal determinism of cognition, behavior, and environment.

Managers should consider socially based patterns of violation when initiating a sales business plan. The chances of RV are increased by unethical models in the organization and offenders’ potential for violations, which is reinforced by social environment.

This study clarified the key drivers of RV decision-making using SLT and identified an effective sales development strategy to maintain an ethically responsible salesforce.

This study aims to analyze communication from the perspective of social marketing, positive emotions, and the topics chosen by Spanish tourist destinations to show their destination image. Additionally, this research shows a message classification model, based on the aforementioned characteristics, that has generated a greater impact, offering clarity to tourism managers on the type of content they should publish to achieve greater visibility.

The methodology used in this work combines content analysis and data mining techniques. The classification tree using the chi-square automatic interaction detector (CHAID) algorithm was selected to determine predictors of like behaviour.

The results show that the predictor variables have been emotions, social marketing and topics. Also, the characteristics of the messages most likely to have a high impact are those related to emotions of joy or happiness, their purpose is behavioural, and they talk about rural, cultural issues, special dates, getaways, or highlights of a town or city for something specific.

This study is the first to analyze the content of the tweets shared by destination tourism managers from a social marketing, positive emotions, and sustainability perspective, determining the possible predictors of likes on Twitter. The authors contribute to the literature by deepening the understanding of how social marketing and the positive emotions promoted drive a more significant impact in tourism communication campaigns on social media. The authors provide destination managers with a way better to understand the variables relevant to users in tourism content.

This study aims to investigate hazards in theater venues on the performance day by combining operational risk theory with a service blueprint method.

Interviews and Delphi method are applied to find the hazards, then a survey and ANOVA are followed. The study explores a profile of hazards using data from theater venues in Taiwan and examines whether employee characteristics (i.e. professional tasks, experience and working location) affect risk perception.

The study suggests a new framework represented by a 5 (types of loss events) × 6 (service systems) matrix to check operational risks. The analyses indicate two types of hazards: risk perception about performance and operations by performers and crew (RPPOPC) and audience behaviors and safety (RPABS). RPPOPC is related to the core show, but not all employees possess high RPPOPC. Seniors have relatively low RPPOPC, and frontend house employees possess insufficient RPABS. Further, front house employees, seniors and those working in municipal cities show relatively high RPPOPC in high-loss situations.

Managers can use the analytic framework to effectively identify operational risks in the core show operations and audience service offerings. They can promote risk perception considering employee differences and loss severity. However, the framework does not discuss the cause-and-effect relationship. Incorporating a large amount of loss experience into a risk information system would help clarify this complex relationship.

This study contributes to hazard mitigation in the performing arts sector, both in the peripheral services for customers and in the core show services.

Based on job embeddedness (JE) theory, the purpose of this paper is to explore the impact of goal orientation (GO) and JE on job stress for financial service salespersons in the indeterminate situation.

Participants were 298 insurance salespersons employed at two major life insurance institutions in Taiwan: Nan Shan and Fubon – which were formerly the subsidiaries of two international financial groups, American International Group and International Netherland Group, respectively. The models were tested using the two-step structural equation procedure.

Findings indicated that, compared with salespersons in the newly merged Fubon, those in Nan Shan, which was undergoing mergers and acquisitions, were found to be subject to higher job stress with lower JE. In the process of reducing stress, JE is an important mechanism. However, the modulating influence of embeddedness is dependent on salespersons’ GO. In situations of higher stress, learning-oriented salespersons (in Nan Shan) were unable to significantly reduce job stress until JE was introduced as a full mediator. However, in a lower stress context, performance-oriented salespersons (in Fubon) fully applied JE in order to relieve job stress.

Managers endeavor to help salespersons effectively improve stability and reduce job stress by exploiting salespersons’ dispositions.

The contribution of this study includes identifying the role of JE on the relationship between GO and job stress for the contingency of an indeterminate state.

The purpose of this paper is to explore the effects of learning orientation (LO) and team embeddedness (TE) on the turnover intention of team members within the context of both culturally diverse and uniform teams.

A structural model was adopted to test the hypotheses with the help of data collected from a survey of 324 foreign and local students of an international university located in Taiwan. To compare the effects of TE and LO in the context of culturally diverse teams (CDT), a multi-group structural equation modeling was employed to investigate individual team behavior.

The LO of team members in a culturally diverse context will positively influence their intention to leave the team. However, such an intention can be reduced by strengthening members’ TE along with the LO. Nonetheless, the direct effect of LO on team turnover intention in the context of same-culture teams was found to be insignificant, leaving TE as the only critical mediator in this case. Furthermore, capability validation, sought by performance-orientated individuals, was found to be an important factor worthy of special consideration for those in a single-culture team context.

This study provides evidence regarding the applicability of the concept of job embeddedness to team relationships and the link between goal orientation and team mobility in a multi-cultural setting. Such an approach is helpful for determining ways to strengthen and stabilize team resources in the context of CDT.