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The purpose of this paper is to target on individual perceptions of BIM practice in terms of BIM benefits, critical success factors (CSFs) and challenges in Chongqing which represented the less BIM-developed metropolitan cities in China.

Adopting a questionnaire-survey approach followed by statistical analysis, the study further divided the survey population from Chongqing into subgroups according to their employer types and organization sizes. A further subgroup analysis adopting statistical approach was conducted to investigate the effects of employer type and organization size on individual perceptions.

Subgroup analysis revealed that governmental employees held more conservative and neutral perceptions toward several items in BIM benefit, CSFs and challenges. It was inferred that smaller organizations with fewer than 100 full-time employees perceived more benefits of BIM in recruiting and retaining employees, and considered more critical of involving companies with BIM knowledge in their projects.

This study contributed to the body of knowledge in managerial BIM in terms that: it extended the research of individual perceptions toward BIM implementation by focusing on less BIM-mature regions; it contributed to previous studies of influencing factors to BIM practice-based perceptions by introducing factors related to organization type and sizes; and it would lead to future research in establishing BIM climate and culture which address perceptions and behaviors in BIM adoption at both individual and organizational levels.

This paper presents an algorithm that can elicitate all or any combination of parameters for the ELECTRE II, III or IV, methods. The algorithm takes some steps of a machine learning ensemble technique, the random forest, and for that, the authors named the approach as Ranking Trees Algorithm.

First, for a given method, the authors generate a set of ELECTRE models, where each model solves a random sample of criteria and actions (alternatives). Second, for each generated model, all actions are projected in a 1D space; in general, the best actions have higher values in a 1D space than the worst ones; therefore, they can be used to guide the genetic algorithm in the final step, the optimization phase. Finally, in the optimization phase, each model has its parameters optimized.

The results can be used in two different ways; the authors can merge all models, to find the elicitated parameters in this way, or the authors can ensemble the models, and the median of all ranks represents the final rank. The numerical examples achieved a Kendall Tau correlation rank over 0.85, and these results could perform as well as the results obtained by a group of specialists.

For the first time, the elicitation of ELECTRE parameters is made by an ensemble technique composed of a set of uncorrelated multicriteria models that can generate robust solutions.

The “Internet of Things (IoT)” is a platform for involving smart devices via the Internet at a worldwide scale. It supports the “supply chain (SC)” and “information and communication technology (ICT)” infrastructure to be well integrated into an organization and externally with customers and suppliers. The “sustainable supply chain (SSC)” is currently unavoidable if a company seeks to satisfy the aggressive change in its customers' requirements. Numerous studies have confirmed that manufacturing firms have to accelerate the shift of their focus toward sustainability and the implementation of novel technologies, such as IoT, to accomplish their organizational goals most effectively. Although the literature consists of many theoretical approaches to IoT and numerous studies that have extremely concentrated upon the IoT technology and its potential applications, it lacks research with a focus on the challenges that arise when applying IoT to the “sustainable supply chain management (SSCM)”.

The present study proposes an integrated framework using the “Criteria Importance Through Intercriteria Correlation (CRITIC)” and “VlseKriterijumska optimizcija I kaompromisno resenje in Serbian (VIKOR)” models and employs to evaluate the IoT challenges to implement the SSCM. For estimating the criteria weights, the CRITIC tool is utilized. The organization's prioritization is obtained by the VIKOR procedure, which delivers simple mathematical procedures with precise and consistent outcomes.

To exhibit the practicality of the introduced model, a case study is taken to evaluate the IoT challenges to implement the SSCM within the “q-Rung Orthopair Fuzzy Sets (q-ROFSs)” environment. Moreover, the authors exhibit a sensitivity investigation over given parameter values, examining the stability of developed approach. Finally, the authors draw attention to a comparison between developed q-ROF-CRITIC-VIKOR decision-making approach with an existing q-ROF-TOPSIS method to show its superiority and potency.

The outcome of the study lies in observing the top benefits of individual businesses, and their entire SSCs can be found by implementing IoT. This paper investigates the most important challenges that individual firms and entire SSCs might while applying IoT. It provides a deep insight regarding the effects of IoT upon SSCM and the issues every firm need to contemplate when it is to apply IoT solutions.

Under the guidance of the concept of openness and development, the paper grasps the mechanism of technology spillover in developed countries and analyzes how to better absorb advanced manufacturing technology based on empirical analysis so as to point out the path for the transformation and development of China’s digital manufacturing industry.

The paper constructs the panel data model and further analyzes the impact of international technology spillovers on the transformation and development of the digital manufacturing industry.

This paper measures the level of technology spillover in the Yangtze River Delta region and finds that foreign direct investment (FDI) technology spillover and import trade technology spillover among four provinces and cities show a growth trend from 2010 to 2017. But after 2017, there is a certain degree of decline.

With the advent of industry 4.0, the digital manufacturing industry of all countries in the world is developing with a new attitude, the global technology spillover methods are diverse and the spillover channels have changed greatly, which will affect the transformation and upgrading of China's digital manufacturing industry.

The digital media recording and broadcasting classroom using Internet real-time intelligent image positioning and opinion monitoring in communication teaching is researched and analyzed.

First, spatial grid positioning and monitoring and image intelligent recognition technologies were used to extract and analyze teaching images by mastering Internet of Things (IoT) technology and establishing an intelligent image positioning and opinion monitoring digital media recording and broadcasting system framework. Next, a positioning node algorithm was utilized to measure the image distance, and then a moving node location model under the IoT was established. In addition, a radial basis function (RBF) neural network was used to realize the signal transmission function. The experimental data of the adopted RBF based on the optimization of the adaptive cuckoo search (ACS-RBF) neural network, particle swarm algorithm neural network, and method of least squares optimization were compared and analyzed. In addition, a more efficient RBF neural network was adopted. Finally, the digital media recording and broadcasting classroom scheme of real-time intelligent image positioning and opinion monitoring was designed. In addition, the application environment of digital media actual teacher teaching was detected, and recording and broadcasting pictures were analyzed and researched.

The actual value, predicted value, and the number of predicted samples of the ACS-RBF model were all better than those of the two other neural networks. According to the analysis and comparison of the sampling optimization Monte Carlo localization (SOMCL), Monte Carlo, and genetic algorithm optimization-based Monte Carlo positioning algorithms, the SOMCL algorithm showed better robustness, and its positioning efficiency was superior to that of the two other algorithms. In addition, the SOMCL algorithm greatly reduced the positioning and monitoring energy consumption.

The application of real-time intelligent image positioning and monitoring technology in actual communication teaching was realized in the study.

This study aims to analyze how bed and breakfast (B&B) experience influences customer value cocreation (CVCC) through emotional psychological factors under the social servicescape (SSC).

A moderated chain mediation model was constructed based on the SSC framework. This study collected 722 valid questionnaires through convenience sampling in Xiamen, China, and tourists with B&B experiences were taken as samples. A structural equation model analysis was used to test relevant hypotheses.

Results reveal that B&B experience is the core factor to stimulate CVCC. In this process, the individual emotional psychological factors [pleasant arousal (PAL) and place attachment (PAT)] play the critical chain mediating role. In addition, localness positively moderates the reinforcing effect of B&B experience on PAL and strengthens the positive effect of PAL on PAT.

The findings can provide useful CVCC strategies for B&B operators. They can achieve CVCC by enhancing customer experiences, strengthening emotional interactions and building local culture, thereby improving the competitiveness of B&Bs.

Current research lacks an in-depth analysis on the internal relationship and logic between B&B experience and CVCC, especially from emotional psychological perspectives. To the best of the authors’ knowledge, this study is one of the first studies to reveal the mechanism of the CVCC process of B&Bs under the SSC from an emotional psychological perspective. It provides a new theoretical model for research on the CVCC of experience-dominant logic.

本研究旨在分析社会服务场景下, 民宿体验如何通过情感心理影响顾客的价值共创。

基于社会服务场景框架, 本研究构建了一个有调节的链式中介模型。研究者针对具有民宿住宿体验的游客进行调查, 在中国厦门采用便利抽样技术收集了722份有效问卷, 并采用结构方程模型检验提出的相关假设。

在社会服务场景下, 民宿体验是激发顾客价值共创的核心因素。在此过程中, 个体情感心理因素（愉悦唤醒和地方依恋）发挥了重要的中介作用, 有效衔接了民宿体验到顾客价值共创的实现过程。此外, 地方性是独特的地方文化体验因子, 正向调节了民宿体验对愉悦唤醒的强化作用, 也增强了愉悦唤醒对地方依恋的积极作用。

研究结论为民宿管理者如何提升顾客价值共创贡献了经营策略。民宿管理者可以通过提升顾客体验、加强情感互动和打造地方文化来实现价值共创, 进而提升民宿竞争力。

当前关于民宿体验与顾客价值共创之间的内在关系及逻辑缺乏深入分析, 仍缺乏情感心理视角的探索。本研究首次从情感心理视角揭示了社会服务场景下民宿顾客价值共创的过程机理, 为以顾客体验为主导逻辑的价值共创研究提供了新的理论模型。

Este estudio pretende analizar cómo la experiencia en un B&B influye en la cocreación de valor para el cliente (CVCC) a través de factores psicológicos emocionales en el marco social del servicescape.

Se construyó un modelo de mediación en cadena moderado basado en el marco social del servicescape. En este estudio se recogieron 722 cuestionarios válidos mediante un muestreo de conveniencia en Xiamen, China, y se tomaron como muestra turistas con experiencias en establecimientos Bed and Breakfast (B&B). Se utilizó un análisis de modelo de ecuaciones estructurales (SEM) para poner a prueba las hipótesis pertinentes.

Los resultados revelan que la experiencia en el B&B es el factor central para estimular la CVCC. En este proceso, los factores psicológicos emocionales individuales (excitación placentera y apego al lugar) desempeñan un papel mediador en cadena. Además, el carácter local modera positivamente el efecto de refuerzo de la experiencia de B&B sobre la excitación placentera y refuerza el efecto positivo de la excitación placentera sobre el apego al lugar.

Los resultados pueden proporcionar estrategias de CVCC útiles para los operadores de B&B. Pueden lograr la CVCC mejorando las experiencias de los clientes, reforzando las interacciones emocionales y construyendo la cultura local, mejorando así la competitividad de los B&B.

La investigación actual carece de un análisis en profundidad sobre la relación interna y la lógica entre la experiencia de los B&B y la CVCC, especialmente desde las perspectivas psicológicas emocionales. Este estudio es uno de los primeros que revela el mecanismo del proceso de CVCC de los B&B bajo el modelo social del servicescape desde una perspectiva psicológica emocional. Proporciona un nuevo modelo teórico para la investigación sobre la CVCC en la lógica dominante de la experiencia.

The purpose of this paper is to explore the possibility of an enhanced continuous liquid interface production (CLIP) with a porous track-etched membrane as the oxygen-permeable window, which is prepared by irradiating polyethylene terephthalate membranes with accelerated heavy ions.

Experimental approaches are carried out to characterize printing parameters of resins with different photo-initiator concentrations by a photo-polymerization matrix, to experimentally observe and theoretically fit the oxygen inhibition layer thickness during printing under conditions of pure oxygen and air, respectively, and to demonstrate the enhanced CLIP processes by using pure oxygen and air, respectively.

Owing to the high permeability of track-etched membrane, CLIP process is demonstrated with printing speed up to 800 mm/h in the condition of pure oxygen, which matches well with the theoretically predicted maximum printing speed at difference light expose. Making a trade-off between printing speed and surface quality, maximum printing speed of 470 mm/h is also obtained even using air. As the oxygen inhibition layer created by air is thinner than that by pure oxygen, maximum speed cannot be simply increased by intensifying the light exposure as the case with pure oxygen.

CLIP process is capable of building objects continuously instead of the traditional layer-by-layer manner, which enables tens of times improvement in printing speed. This work presents an enhanced CLIP process by first using a porous track-etched membrane to serve as the oxygen permeable window, in which a record printing speed up to 800 mm/h using pure oxygen is demonstrated. Owing to the high permeability of track-etched membrane, continuous process at a speed of 470 mm/h is also achieved even using air instead of pure oxygen, which is of significance for a compact robust high-speed 3D printer.

This study aims to investigate the role of work–family conflict (WFC) and work engagement (WE) and its influence on role stressors and turnover intention among medical doctors in Malaysian public hospitals. Doctors who experience higher work stress will inevitably experience WFC, consequently triggering their intention to quit.

A total of 202 structured questionnaire responses were collected from medical doctors in four Malaysian public hospitals. The study used partial least squares structural equation modeling (SmartPLS 3.0) for hypotheses testing.

As hypothesized, WFC encourages turnover intention while WE mitigate the relationship between role ambiguity (RA)-TI. RA is also observed to reduce WE, which, in turn, increases the intention to quit. Findings showed that both role conflict and WFC share a positive relationship with TI while WE and TI are negatively related. Furthermore, it was found that WE and WFC are significant mediators in the RA and TI relationship. WFC is also reported to be a significant mediator between the RC and TI relationship.

The causality effects remain limited due to the nature of the cross-sectional design. Future studies should use a longitudinal approach to gauge a better understanding of these relationships.

This study provides insights for policymakers in resolving the increase of turnover issues by providing support and relieving medical doctors’ stress levels. Health directors should be encouraged to focus on the key aspects that may directly affect the well-being of medical doctors and eventually reduced staff turnover.

The study contributes to existing knowledge by measuring variables such as job demand (RS and WFC), personal resources (WE) and job outcomes (TI) in the public health care sector. Additionally, research involving COR theory in Asian countries like Malaysia remains relatively underexplored.