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The purpose of this paper is to propose a new acceleration/deceleration (acc/dec) algorithm for motion profiles. The motion efficiency, flexibility of the motion profiles and the residual vibration of the movement are discussed in this paper.

A dynamics model is developed to assess the residual vibration of these two kinds of motion profile. And a Simulink model is created to assess the motion efficiency and flexibility of the motion profiles with the proposed acc/dec algorithm.

Considering the flexibility of trigonometric motion profiles and the higher motion efficiency of S-curve motion profiles, the authors add the polynomial parts into the jerk profile of the cosine function acc/dec algorithm to hold the jerk when it reaches the maximum so that the motion efficiency can increase and decrease residual vibration at the same time. And the cyclical parameter k shows the decisive factor for the flexibility of trigonometric motion profiles.

Comparing with the traditional motion profiles, the proposed motion profiles have higher motion efficiency and excite less residual vibration. The acc/dec algorithm proposed in this paper is useful for the present motion control and servo system.

The purpose of this study is to examine the impact of social media affordances, specifically social engagement and social endorsement, on knowledge contribution in online Q&A communities. Building on self-determination theory, this research seeks to tackle the issue of under-provision of knowledge in these communities.

The study employs a sample collected from a popular social Q&A community in China and uses linear panel data models along with multiple robustness checks to test the research model.

The findings reveal that both social engagement and social endorsement have a positive effect on users' knowledge contribution to the online Q&A community. However, the impact of social engagement is mitigated by social endorsement.

This paper makes a valuable contribution to the field by filling the research gap on the role of social engagement behaviors and their interaction with social endorsement in online Q&A communities. The results provide insights into how social media affordances can be leveraged to enhance knowledge contribution in these communities.

The digital revolution and the use of big data (BD) in particular has important applications in the construction industry. In construction, massive amounts of heterogeneous data need to be analyzed to improve onsite efficiency. This article presents a systematic review and identifies future research directions, presenting valuable conclusions derived from rigorous bibliometric tools. The results of this study may provide guidelines for construction engineering and global policymaking to change the current low-efficiency of construction sites.

This study identifies research trends from 1,253 peer-reviewed papers, using general statistics, keyword co-occurrence analysis, critical review, and qualitative-bibliometric techniques in two rounds of search.

The number of studies in this area rapidly increased from 2012 to 2020. A significant number of publications originated in the UK, China, the US, and Australia, and the smallest number from one of these countries is more than twice the largest number in the remaining countries. Keyword co-occurrence is divided into three clusters: BD application scenarios, emerging technology in BD, and BD management. Currently developing approaches in BD analytics include machine learning, data mining, and heuristic-optimization algorithms such as graph convolutional, recurrent neural networks and natural language processes (NLP). Studies have focused on safety management, energy reduction, and cost prediction. Blockchain integrated with BD is a promising means of managing construction contracts.

The study of BD is in a stage of rapid development, and this bibliometric analysis is only a part of the necessary practical analysis.

National policies, temporal and spatial distribution, BD flow are interpreted, and the results of this may provide guidelines for policymakers. Overall, this work may develop the body of knowledge, producing a reference point and identifying future development.

To our knowledge, this is the first bibliometric review of BD in the construction industry. This study can also benefit construction practitioners by providing them a focused perspective of BD for emerging practices in the construction industry.

This study aims to identify the impact of affective components on behavioral intentions applying electronic word of mouth (eWOM) and is based on the “cognitive–affective–conative” model. EWOM allows researchers to get new insights about consumers’ behavior and explores new patterns of consumers’ decision-making processes.

This study is based on the theory of planned behavior (Ajzen, 1991), doubled with “cognitive–affective–conative” model (Oliver, 2014). This study applies structural topic modeling to examine the impact of satisfaction dimensions from all the Tripadvisor reviews on consumer behavioral intentions. The research sample covers all restaurants located in St. Petersburg (n = 10,424) and all consumers’ reviews (n = 286,642).

In this study, the dimensions of the affective component were identified. The results demonstrate that dimensions of the affective component (food quality, service quality, atmosphere and cost fairness) affect behavioral intention (willingness to share positive emotions). In total, 20 topics, forming these dimensions, have been indicated. Consumers tend to pay more attention toward food quality and restaurant staffs’ work when they are willing to share positive emotions and tend to point out auxiliary service when they have less willingness to share positive emotions. Random restaurant visits tend to increase the willingness to share positive emotions.

Research originality lies in a new methodological approach which is based on text mining techniques. To the best of the authors’ knowledge, this study is the first attempt to examine consumer behavior through the lens of the “cognitive–affective–conative” model based on eWOM and covers all businesses in the specific economic sphere. This has allowed the researchers to reveal new dimensions of consumer behavior and brought more insights into the consumers’ decision-making process.

The purpose of this paper is to investigate the role of Customer Participation (CP) in the effectiveness of New Service Development (NSD) by examining the moderating roles of Customer Empowerment (CE) and Customer Satisfaction (CS). The research reduces the risk of failure of the NSD process and/or improves the NSD processes used by companies through the consideration of the results in the practical dimension.

This study investigates the effects of CP at different stages of NSD using a quantitative approach. Data were collected through an online survey questionnaire. Smart PLS was used to analyse the data collected from 509 newsreaders and users of the news agency’s application.

The model confirmed that CE has an impact on the effectiveness of NSD in the idea generation and commercialization stages, but not in the development stage. Empowerment and customer satisfaction did not influence the three stages of NSD indirectly but directly. The results show that CP, CS and CE do not always have a direct or indirect effect on the development of new services. Therefore, in order to design new service development projects, media news companies need to determine the level of user cooperation.

The lack of objective data, especially on company performance, forces researchers to use questionnaires to analyse NSD effectiveness. Another limitation is that newspaper users answered the questionnaires, which creates “common method variance.”

Researchers on NSD effectiveness must use questionnaires due to a lack of objective data, especially on company performance. Another limitation is “common method variance” from newspaper users answering questionnaires.

This paper is a response to a perceived need for an examination of how new service development can be successful and effective.

This study investigates the impact of personal, organisational and innovation capability on technological innovation and further impacts on small and medium enterprises’ (SMEs') performance during uncertainty. Moreover, the moderator role of social sustainability orientation on the relationships of technological innovation, innovation performance and organisational resilience is also examined.

A quantitative approach using 524 SME responses and Smart PLS 4.0 are adopted in this research.

The results indicate a correlation between three types of capabilities with technological innovation and further conversion to organisational resilience. Additionally, social sustainability shows a negative moderating effect between innovation performance and organisational resilience. The research findings advanced the resources-based-view (RBV) by proposing three capability dimensions as platforms for SMEs' innovation success, which later generate resilience possibilities. Specifically highlighted in this study are the personal capabilities of managers, organisational capabilities and innovation capabilities in setting business objectives and resource allocation towards economic and sustainable goals during turbulence and uncertainty.

This study investigates the role of technological innovation and innovation on SME resilience. Notably, we deploy the social sustainability orientation as moderators towards the relationship between technological innovation, innovation performance and SMEs’ resilience. SMEs employing social sustainability orientation might negatively inhibit the translation from innovation performance to SME resilience, providing novel insights into navigating uncertainty in modern business. It has no effect on the relationship between technological innovation and its consequences.

The purpose of this study is to examine the effects of banking innovations (INNs) on customer experience (EXP), satisfaction (SAT) and loyalty (LOY).

The author evaluated the data using a structural equation method-artificial neural network (SEM-ANN) method. The author’s results show the presence of relationship between INN, EXP, SAT and LOY. In this study, the node layers of ANNs add an input layer, hidden layers and an output layer. Each “node” acts as an artificial neuron that communicates with others. The ANN model takes the variables from the SEM analysis as input neurons.

The author observed the significant effects between INN, EXP, SAT and LOY using the normalised importance generated by the multilayer perceptron used in the feed-forward back propagation of the ANN methodology. In this study, the ANN model can predict LOY through service innovation, with a forecast accuracy of 77.6%.

By applying neural network modelling, this research helps us understand how service innovation affects customer behaviour. For the first time, the author examined service innovations' direct and indirect impact on loyalty through EXP and SAT. The author made a significant conceptual contribution by using a non-compensatory model of ANNs to circumvent the limitations of linear models.

Agricultural science and technology (AST) often need the form of industry-university-research cooperation in successfully completing breakthrough agricultural technology innovations. Therefore, AST industry-university-research cooperation is not only the need of the AST development strategy in China but also the only way for the development of agricultural colleges and universities, agricultural scientific research institutions and agricultural enterprises. Among them, in the process of cooperative breakthrough agricultural technology innovation, the correct selection of partners is the basis for ensuring its effective operation.

Aiming at the time-series characteristics and information ambiguity of decision information in the dynamic selection process of AST industry-university-research partners, this research introduces the dynamic intuitionistic fuzzy multi-criteria decision-making method of time degree and orthogonal projection. On this basis, field theory is used to construct the cooperative innovation capability field model of the partners, and the threshold for the partners to enter or exit the system is designed to dynamically select and eliminate the partners.

Results show that this method fully considers the situation of cooperative innovation resources within the AST industry-university-research system and the resource complementarity of candidate partners.

Combined with examples from agricultural scientific research institutions, the applicability and superiority of the model are verified.

This paper aims to review recent research in design for additive manufacturing (DfAM), including additive manufacturing (AM) terminology, trends, methods, classification of DfAM methods and software. The focus is on the design engineer’s role in the DfAM process and includes which design methods and tools exist to aid the design process. This includes methods, guidelines and software to achieve design optimization and in further steps to increase the level of design automation for metal AM techniques. The research has a special interest in structural optimization and the coupling between topology optimization and AM.

The method used in the review consists of six rounds in which literature was sequentially collected, sorted and removed. Full presentation of the method used could be found in the paper.

Existing DfAM research has been divided into three main groups – component, part and process design – and based on the review of existing DfAM methods, a proposal for a DfAM process has been compiled. Design support suitable for use by design engineers is linked to each step in the compiled DfAM process. Finally, the review suggests a possible new DfAM process that allows a higher degree of design automation than today’s process. Furthermore, research areas that need to be further developed to achieve this framework are pointed out.

The review maps existing research in design for additive manufacturing and compiles a proposed design method. For each step in the proposed method, existing methods and software are coupled. This type of overall methodology with connecting methods and software did not exist before. The work also contributes with a discussion regarding future design process and automation.

Knowledge loss (KL) is still an unfortunate fact, causing many challenges, including poor organisational performance, despite prior efforts to investigate knowledge retention methods. Therefore, this study identifies early approaches to combat KL and poor organisational performance, shifting focus on employee personality traits.

Grounded on the social exchange theory (SET) cross-section data from 400 Chinese construction knowledge employees were used to investigate the role of internal work locus of control (IWLC) on job rotation (JR), KL and organisational performance. The data were analysed through IBM SPSS Statistics 25 and SmartPLS 4 software.

The results demonstrated that IWLC minimises KL and positively influences JR. Then, JR negatively influences KL and decreases in organisational performance. The negative mediating effect of JR in the relationship between IWLC, KL and decreased organisational performance were also found. Finally, KL proved to positively influence a decrease in organisational performance.

This study contributes to the new understanding of individual behaviour and its influence on organisational outcome variables. Specifically, for ultimate KL prevention and organisational performance improvement, an organisation should understand its employees' behaviours to establish progressive collective learning and knowledge sharing.

This study contributes to the new understanding of individual behaviour and its influence on organisational outcome variables. Specifically, for ultimate KL prevention and organisational performance improvement, an organisation should understand its employees’ behaviours to establish progressive collective learning and knowledge sharing.

This study is the first attempt to explore the influence of personality traits in the early minimisation of KL, particularly the role of IWLC and JR in combating KL and improving organisational performance.