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In view of the rapid growth of micro vacation trend in post-pandemic era, this study aims to identify the underlying motivational factors for micro vacation by developing and validating a measurement scale, while explore the influence of micro vacation motivation on travel intention.

This research adopts mixed methods. Nine dimensions with 38 items are initially yielded through extensive literature review and in-depth interview (n = 22). Expert panel review filters the scale into eight dimensions with 35 items. Principal component analysis (n = 376) purifies the measures into a 35-item and seven-dimension scale, further confirmed by confirmatory factor analysis (n = 616). Nomological validity test (n = 694) proved the positive effect of micro vacation motivation on travel intention.

The results present a measurement scale of micro vacation motivation and reveals its seven dimensions: self-presentation, spiritual satisfaction, bonding, convenience, sense of rituals, place attachment and perceived risk. All the motivational factors positively influence travel intention for a micro vacation.

Through profound comprehension of micro vacationers’ travel motivation, destination marketers and tourism providers can better design their products based on vacationers’ needs while stimulate potential market’s visiting intention by diverse marketing activities.

This study enriches the literature of micro vacation tourism and deepens the knowledge of travel motivation, filling the research gap of tourists’ motivation in micro vacation market.

鉴于疫情后时代微度假趋势的快速增长, 本研究旨在通过开发和验证测量量表来探索微度假的潜在动机因素, 同时探讨微度假动机对旅游意向的影响。

本研究采用混合方法。通过广泛的文献回顾和深度访谈（n = 22）, 初步得出九个维度 38 个题项。专家小组评审将量表筛选为八个维度, 共 35 个题项。主成分分析（n = 376）将其提纯为 35 个题项、七个维度的量表, 并通过确认性因子分析（n = 616）进一步确认。法则效度测试（n = 694）证明了微观度假动机对旅游意向的积极影响。

研究结果提出了微度假动机的测量量表, 并揭示了其七个维度：自我展示、精神满足、联系、便利、仪式感、地方依恋和感知风险。所有动机因素都会对微型度假的旅行意向产生积极影响。

本研究丰富了微度假旅游的文献, 加深了对旅游动机的认识, 填补了微度假市场中游客旅游动机的研究空白。

通过对微型度假者旅游动机的深刻理解, 旅游目的地营销者和旅游服务提供者可以更好地根据度假者的需求设计产品, 同时通过多样化的营销活动激发潜在市场的旅游意向。

Frente al rápido crecimiento de la tendencia a las microvacaciones en la era post pandemia, esta investigación pretende identificar los factores motivacionales subyacentes de las microvacaciones mediante el desarrollo y la validación de una escala de medición, así como analizar la influencia de la motivación de las microvacaciones en la intención de viajar.

Esta investigación adopta un método mixto. En primer lugar, se obtienen nueve dimensiones con 38 ítems a través de una amplia revisión bibliográfica y una entrevista en profundidad (n = 22). Un panel de expertos filtró la escala en ocho dimensiones con 35 ítems. El análisis de componentes principales (n = 376) depuró las medidas en una escala de 35 ítems y siete dimensiones, confirmada además por el análisis factorial confirmatorio (n = 616). La prueba de validez nomológica (n = 694) demostró el efecto positivo de la motivación microvacacional en la intención de viajar.

Los resultados presentan una escala de medición de la motivación para las microvacaciones y muestran sus siete dimensiones: autopresentación, satisfacción espiritual, vinculación, conveniencia, sentido de los rituales, apego al lugar y riesgo percibido. Todos los factores motivacionales influyen positivamente en la intención de viajar en microvacaciones.

Este estudio enriquece la literatura del turismo de microvacaciones y profundiza en el conocimiento de la motivación para viajar, llenando la laguna existente en la investigación de la motivación de los turistas en el mercado de las microvacaciones.

Mediante una comprensión profunda de la motivación de viaje de los microvacacionistas, los comercializadores de destinos y los proveedores turísticos pueden diseñar mejor sus productos basándose en las necesidades de los turistas, así como estimular la intención de visita del mercado potencial mediante diversas actividades de marketing.

Research focusing on psychological capital (PsyCap) has been mainly conducted at the individual level. However, recent research has expanded investigations to the collective level with a greater focus on team-level PsyCap. Although, as demonstrated by recent systematic reviews and meta-analyses, the relationships between individual-level PsyCap and the desirable/undesirable outcomes are fairly established in the literature, less is known about such relationships for team-level PsyCap. One of these important, yet least investigated, research areas is the research stream that focuses on the relationship between team-level PsyCap and the outcomes of health, Well-Being, and safety. This chapter aims to highlight the role of individual-level PsyCap as an important predictor of employees’ health, Well-Being, and safety outcomes, but also to go beyond that to provide insights into the potential role of team-level PsyCap in predicting such outcomes at both individual and team levels. To do so, the chapter first draws upon relevant theories to discuss the empirical research findings focusing on the relationship between individual-level PsyCap and the outcomes of health, Well-Being, and safety. It then focuses on team-level PsyCap from theoretical, conceptualization, and operationalization perspectives and provides insights into how team-level PsyCap might be related to health, Well-Being, and safety outcomes at both individual and team levels. Thus, this chapter proposes new research directions in an area of PsyCap that has been left unexplored.

The net power delivered to the surface of parts (i.e. the actual heat flux) is a key parameter in the laser melting process and its exact control has a great impact on the numerical solutions. In this paper, the impact of laser additive manufacturing parameters including laser power, scanning speed and powder injection rate on thermal efficiency, net power delivered to the part and power loss due to powder flow has been investigated.

The response surface method was applied to measure the net laser power in laser deposited Inconel 718 using k-type thermocouples. The temperature history obtained by thermocouples was used to calculate the net power delivered by inverse analysis method. The applied model is Rosenthal's optimized model, in which all the thermal properties of the material are considered to vary with temperature.

The results indicated that the thermal efficiency, power delivered to the part and power loss can be optimized simultaneously at laser power of 400 W, scanning speed of 2 mm/s and powder injection rate of 200 mg/s. The microstructure analysis indicated that a high-quality sample without microstructural defects was formed under optimal condition of parameters. Moreover, the primary dendrite arm spacing for the optimal sample was higher than that obtained for other samples.

The novelty of this research summarized as follows: Prediction of the thermal efficiency and power loss during the laser metal deposition of Inconel 718 superalloy using the inverse analysis. Finding the optimal values of thermal efficiency, power delivered to the surface and power loss in the laser metal deposition of Inconel 718 superalloy. Investigating the effect of laser power, powder injection rate and scanning speed on the thermal efficiency and power loss of Inconel 718 superalloy during the laser metal deposition.

The purpose of this study is to develop a new numerical algorithm to simulate the phase-field model.

First, the derivative of the temporal direction is discretized by a second-order linearized finite difference scheme where it conserves the energy stability of the mathematical model. Then, the isogeometric collocation (IGC) method is used to approximate the derivative of spacial direction. The IGC procedure can be applied on irregular physical domains. The IGC method is constructed based upon the nonuniform rational B-splines (NURBS). Each curve and surface can be approximated by the NURBS. Also, a map will be defined to project the physical domain to a simple computational domain. In this procedure, the partial derivatives will be transformed to the new domain by the Jacobian and Hessian matrices. According to the mentioned procedure, the first- and second-order differential matrices are built. Furthermore, the pseudo-spectral algorithm is used to derive the first- and second-order nodal differential matrices. In the end, the Greville Abscissae points are used to the collocation method.

In the numerical experiments, the efficiency and accuracy of the proposed method are assessed through two examples, demonstrating its performance on both rectangular and nonrectangular domains.

This research work introduces the IGC method as a simulation technique for the phase-field crystal model.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

This chapter focuses on cycle tourism using Bambike (Bamboo Bike) as sustainable transportation in the heritage site of Intramuros to promote cultural awareness and environmental preservation. Bambike is a bicycle where parts are made from natural bamboo and abaca with aircraft grade alloys tested for durability that passed the standards in the industry. The purpose of this chapter is to determine the value of cycle tourism using Bambike to promote green tourism in Intramuros and preserve its attractions. Its significance and benefits as to economic, environmental, and sociocultural impacts have been analyzed. The information source and data collection for this research was from the selected local and international tourists in Intramuros who have experienced and booked a trip with Bambike. An interview with structure questionnaire was done for the tourists and Bambike staff. It was concluded that Bambike can contribute to create site awareness leading to desire to preserve the heritage sites of Intramuros.

This study used an indentation-based mechanical testing framework for the mechanical characterization of laser powder bed fusion (LPBF) processed Inconel 718 on a wrought Inconel 718 substrate. The purpose of the paper is to investigate the effectiveness of the indentation-based approach for localized mechanical evaluation.

The LPBF-processed wrought substrate was sectioned into three sections for microstructural and mechanical characterization. A 3D heat source model was used for the thermal analysis of the interface region. The developed interface region is probed using the Knoop hardness indenter in different orientations to determine the textural anisotropy and mechanical behavior of the region.

LPBF process develops a melted interface zone (MIZ) at the deposition-substrate interface. The MIZ exhibited a coarse grain structure region along with a larger primary dendritic arm spacing (PDAS), signifying a slower cooling rate. FE modeling of the LPBF process reveals heat accumulation in the substrate along with intrinsic heat treatment (IHT) induced due to layer-wise processing. The obtained yield locus shows strong anisotropy in the deposition region, whereas reduced anisotropy with a nearly uniform ellipse locus for the MIZ regions. This reduced anisotropy is attributable to IHT and heat accumulation in the substrate.

An alternative localized mechanical characterization tool has been investigated in this work. The approach proved sensitive to thermal variations during LPBF processing in an isolated region which extends its suitability to variable geometry parts. Moreover, the approach could serve as a screening tool for parts made from dissimilar metals.

In typical model-based calibration, linearization errors are derived inevitably, and non-negligible negative impact will be induced on the identification results if the rotational kinematic errors are not small enough or the lengths of links are too long, which is common in the industrial cases. Thus, an accurate two-step kinematic calibration method minimizing the linearization errors is presented for a six-DoF serial robot to improve the calibration accuracy.

The negative impact of linearization on identification accuracy is minimized by removing the responsible linearized kinematic errors from the complete kinematic error model. Accordingly, the identification results of the dimension-reduced new model are accurate but not complete, so the complete kinematic error model, which achieves high identification accuracy of the rest of the error parameters, is combined with this new model to create a two-step calibration procedure capable of highly accurate identification of all the kinematic errors.

The proportions of linearization errors in measured pose errors are quantified and found to be non-negligible with the increase of rotational kinematic errors. Thus, negative impacts of linearization errors are analyzed quantitatively in different cases, providing the basis for allowed kinematic errors in the new model. Much more accurate results were obtained by using the new two-step calibration method, according to a comparison with the typical methods.

This new method achieves high accuracy with no compromise on completeness, is easy to operate and is consistent with the typical method because the second step with the new model is conveniently combined without changing the sensors or measurement instrument setup.

This study aims to examine the impact of the decision makers’ risk preference on logistics routing problem, contributing to logistics behavior analysis and route integration optimization under uncertain environment. Due to the unexpected events and complex environment in modern logistics operations, the logistics process is full of uncertainty. Based on the chance function of satisfying the transportation time and cost requirements, this paper focuses on the fourth party logistics routing integrated optimization problem considering the chance preference of decision makers from the perspective of satisfaction.

This study used the quantitative method to investigate the relationship between route decision making and human behavior. The cumulative prospect theory is used to describe the loss, gain and utility function based on confidence levels. A mathematical model and an improved ant colony algorithm are employed to solve the problems. Numerical examples show the effectiveness of the proposed model and algorithm.

The study’s findings reveal that the dual-population improvement strategy enhances the algorithm’s global search capability and the improved algorithm can solve the risk model quickly, verifying the effectiveness of the improvement method. Moreover, the decision-maker is more sensitive to losses, and the utility obtained when considering decision-makers' risk attitudes is greater than that obtained when the decision-maker exhibits risk neutrality.

In an uncertain environment, the logistics decision maker’s risk preference directly affects decision making. Different parameter combinations in the proposed model could be set for decision-makers with different risk attitudes to fit their needs more accurately. This could help managers design effective transportation plans and improve service levels. In addition, the improved algorithm can solve the proposed problem quickly, stably and effectively, so as to help the decision maker to make the logistics path decision quickly according to the required confidence level.

Considering the uncertainty in logistics and the risk behavior of decision makers, this paper studies integrated routing problem from the perspective of opportunity preference. Based on the chance function of satisfying the transportation time and cost requirements, a fourth party logistics routing integrated optimization problem model considering the chance preference of decision makers is established. According to the characteristics of the problem, an improved dual-population ant colony algorithm is designed to solve the proposed model. Numerical examples show the effectiveness the proposed methods.