Search results

This paper aims to explore how enterprise microblogging can influence consumer loyalty and thus generate business value for firms. The study aims to expand traditional brand community theory.

The paper is based on brand community theory, social identity theory and usage and gratifications theory. Using a pre-survey of the fans of an enterprise microblog and a random sample survey of such fans on Sina Weibo, the authors tested the structural equation model with LISREL, which includes multiple fit indices.

The paper provides empirical insights about how enterprise microblogging can influence consumer loyalty and thus generate business value for firms. It suggests that consumers’ perceived value could strengthen their microblog identification, which will influence their perceived relationship with the enterprise and its products directly and indirectly through the mediation of enterprise identification. Perceived relationship can further influence purchase and recommendation intentions.

Because of the chosen data collecting approach, the research results may be still subjective. Moreover, the study overlooks the effects of the different types of enterprise microblogging and consumers.

Enterprises should operate their official microblogging from the perspective of maintaining brand community to improve consumer loyalty. They can generate more value for consumers through their microblogging and predict the operating performance by evaluating the degree of consumers’ relationship perception.

This paper considers enterprise microblogging as a new form of virtual brand community and identifies its features, and expands theories of brand community, and social media/IT business value, social identity theory and gratifications theory.

The coupling impact of hybrid uncertain errors on the machine precision is complex, as a result of which the designing method with multiple independent error sources under uncertainties remains a challenge. For the purpose of precision improvement, this paper focuses on the robot design and aims to present an assembly precision design method based on uncertain hybrid tolerance allocation (UHTA), to improve the positioning precision of the mechanized robot, as well as realize high precision positioning within the workspace.

The fundamentals of the parallel mechanism are introduced first to implement concept design of a 3-R(4S) &3-SS parallel robot. The kinematic modeling of the robot is carried out, and the performance indexes of the robot are calculated via Jacobian matrix, on the basis of which, the 3D spatial overall workspace can be quantified and visualized, under the constraints of limited rod, to avoid the singular position. The error of the robot is described, and a probabilistic error model is hereby developed to classify the hybrid error sensitivity of each independent uncertain error source by Monte Carlo stochastic method. Most innovatively, a methodology called UHTA is proposed to optimize the robot precision, and the tolerance allocation approach is conducted to reduce the overall error amplitude and improve the robotized positioning precision, on the premise of not increasing assembly cost.

The proposed approach is validated by digital simulation of medical puncture robot. The experiment highlights the mathematical findings that the horizontal plane positioning error of the parallel robotic mechanism can be effectively reduced after using UHTA, and the average precision can be improved by up to 39.54%.

The originality lies in UHTA-based precision design method for parallel robots. The proposed method has widely expanding application scenarios in industrial robots, biomedical robots and other assembly automation fields.

Compared with cusp height and area deviation ratio, volume error (VE) caused by the layer height could represent the stair-case effect more comprehensively. The proposed relative volume error (RVE)-based adaptive slicing method takes VE rather than cusp height as slicing criteria, which can improve part surface quality for functionalized additive manufacturing.

This paper proposes a volumetric adaptive slicing method of manifold mesh for rapid prototyping based on RVE. The pre-height sequences of manifold mesh are first preset to reduce the SE by dividing the whole layer sequence into several parts. A breadth-first search-based algorithm has been developed to generate a solid voxelization to get VE. A new parameter RVE is proposed to evaluate the VE caused by the sequence of the layer positions. The RVE slicing is conducted by iteratively adjusting the layer height sequences under different constraint conditions.

Three manifold models are used to verify the proposed method. Compared with uniform slicing with 0.2 mm layer height, cusp height-based method and area deviation-based method, the standard deviations of RVE of all three models are improved under the proposed method. The surface roughness measured by the confocal laser scanning microscope proves that the proposed RVE method can greatly improve part surface quality by minimizing RVE.

This paper proposes an RVE-based method to balance the surface quality and print time. RVE could be calculated by voxelized parts with required accuracy at a very fast speed by parallel.

This paper endeavors to create a predictive model for the energy consumption associated with the multi-material fused deposition modeling (FDM) printing process.

An online measurement system for monitoring power and temperature has been integrated into the dual-extruder FDM printer. This system enables a comprehensive study of energy consumption during the dual-material FDM printing process, achieved by breaking down the entire dual-material printing procedure into distinct operational modes. Concurrently, the analysis of the G-code related to the dual-material FDM printing process is carried out.

This work involves an investigation of the execution instructions that delineate the tooling plan for FDM. We measure and simulate the nozzle temperature distributions with varying filament materials. In our work, we capture intricate details of energy consumption accurately, enabling us to predict fluctuations in power demand across different operational phases of multi-material FDM 3D printing processes.

This work establishes a model for quantifying the energy consumption of the dual-material FDM printing process. This model carries significant implications for enhancing the design of 3D printers and advancing their sustainability in mobile manufacturing endeavors.

Emerging markets face the developmental circumstances of a weak foundation in both manufacturing and services. Although servitization is viewed as an opportunity to realise industry transformation and upgrading, ways for emerging market firms to implement a high-level servitization strategy is still understudied. This study examines combinations of causal conditions for emerging market firms to implement a high level of servitization.

Anchored in the strategy tripod model, this study examines the configurations for implementing a high-level servitization strategy by using fuzzy-set qualitative comparative analysis (fsQCA) and data from the China Stock Market and Accounting Research Database (CSMAR).

The findings identify three kinds of configurations for achieving a high-level servitization strategy: market-cultivational servitization, competition-driven servitization and government-related servitization. Furthermore, the mechanisms for implementing a high-level servitization strategy differ within the regional marketization level and state-owned equity. Specifically, the improvement of the regional marketization level helps manufacturing firms realise a high level of servitization by strengthening service capacity, and state-owned equity helps firms gain distinctive legitimacy to integrate suppliers and providers into the servitization context.

The proposed multilevel perspective frameworks enable manufacturing firms in emerging markets to achieve a high level of servitization strategy.

This paper explores the impact of institutional environment, industry conditions and firm-level microfoundations on servitization, therefore providing a reference framework for emerging market firms interested in implementing high-level servitization strategies.

The purpose of this paper is to verify the performance and function of the scale-up prototypes by predicting the material and energy consumption on the basis of dimension-reduced prototypes. Additive manufacturing (AM) costs determine carbon emissions in total life cycle, among which material and energy consumption are major components. Predicting material and energy consumption is fundamental to reducing costs.

This paper presents a material and energy co-optimization method for AM via multiple layers prediction (MLP). Material and energy consumption are predicted to reduce the AM costs. In particular, scalable, complex curved surface component is used to improve forecasting efficiency. Subsequently, the back pressure distribution is obtained by scale-up specimens, which can lay the foundation for the ergonomic conceptual design.

Taking evolutionary ergonomic product as an example, the relative gravity direction of backrest is calculated. The material and energy consumption are predicted with low deviation. Physical experiments were carried out to validate information. Digital and physical tests have revealed that material and energy co-optimization improves manufacturing efficiency.

The innovatively proposed MLP method predicts material and energy consumption of scale-up prototypes to reduce the costs. It is propitious to improve the carbon emission efficiency in life cycle of AM. The originality may be widely adopted alongside increasing environmental awareness.

Enterprise resource planning (ERP) implementation brings with it a set of challenges. In order to gain a better understanding of these and they can be mitigated during the implementation process, the purpose of this paper is to use Esteves and Bohórquez (2007) classification based on ERP lifecycle framework, and content analysis to review the literature on ERP implementation in a structured format with a focus on larger enterprises, and provide a platform for practitioners to plan implementation with minimum possibility of failure.

Esteves and Bohórquez (2007) classification based on the ERP lifecycle framework is used to develop and present a comprehensive structured review of the literature on ERP system implementation in large enterprises (LEs), with a particular focus on pre-implementation, implementation, and post-implementation.

Drawing from the literature, organisations can plan implementation based on the findings and strategies presented in the study. This can lead to a better understanding of implementation with minimal probability of failure. The authors find that top management support, good project management teams, and good communications are the top three most important critical successful factors during implementation. The authors also identify critical gaps in current research. Existing research focusses predominantly on the implementation phase, but research on pre- and post-implementation is lacking, and that no industry standard implementation methodology has been developed.

This review primarily focusses on the literature in the area of ERP implementation. ERP implementation planning involves access to effective implementation strategies. Despite the literature identifying a myriad of different ERP implementation models, no standard industry ERP implementation model has been developed. The findings for ERP implementation are repetitive, inconsistent, and lack empirical research, rendering these two of the most critical areas for future research, and collaboration between ERP practitioners, system developers, and researchers. Researchers, in turn, need to become more innovative in terms of their research techniques when examining ERP implementation.

This paper provides guidance to researchers and practitioners with an insight into published research work and their findings. It provides a better understanding of ERP implementation, which can be applied towards overcoming operational difficulties during the implementation process.

This study is innovated in its use of Esteves and Bohórquez (2007) classification based on the ERP lifecycle framework, and content analysis to present a comprehensive structured literature review of the ERP implementation literature with a specific focus on pre-implementation, implementation, and post-implementation in LEs between the period 1989 and 2014. The technique and time period used in this study differs from those of other studies on ERP implementation. The paper brings together theoretical and practical developments on ERP implementation under a single source, which should aid practitioners, researchers and ERP developers with future research and decision making.

This study was designed to investigate how the material properties of the tea-drinking receptacle interact with a participant's motivation and preference for extracting and using information obtained via haptic perception, namely the need for touch (NFT), to influence his or her tea-drinking experience.

72 blindfolded participants were instructed to sample room temperature tea beverages served in a cup that was made of ceramic, glass, paper or plastic. They were then asked to rate how familiar they were with the taste of the beverage, to rate how pleasant the taste was and to specify how much they would like to pay for it (i.e. willingness-to-pay ratings).

The material of the receptacles used to serve the tea exerted a significant influence over the pleasantness ratings of the tea and interacted with the participants' NFT, exerting a significant influence over their willingness to pay for the tea. Specifically, high-NFT participants were willing to pay significantly more for the same cup of tea when it was served in a ceramic cup rather than in a paper cup, whereas the low-NFT participants' willingness to pay for the tea was unaffected by the material of the receptacles.

Our findings suggest that consumers may not be equally susceptible to the influence of the receptacle in which tea, or any other beverage, is served. Our findings also demonstrate how the physical properties of a receptacle interact with a consumer's motivation and preference to influence his or her behavior in the marketplace.