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Production and transportation of precast components, as two continuous service stages of a precast plant, play an important role in meeting customer needs and controlling costs. However, there is still a lack of production and transportation scheduling methods that comprehensively consider delivery timeliness and transportation economy. This article aims to study the integrated scheduling optimization problem of in-plant flowshop production and off-plant transportation under the consideration of practical constraints of customer order delivery time window, and seek an optimal scheduling method that balances delivery timeliness and transportation economy.

In this study, an integrated scheduling optimization model of flowshop production and transportation for precast components with delivery time windows is established, which describes the relationship between production and transportation and handles transportation constraints under the premise of balancing delivery timeliness and transportation economy. Then a genetic algorithm is designed to solve this model. It realizes the integrated scheduling of production and transportation through double-layer chromosome coding. A program is designed to realize the solution process. Finally, the validity of the model is proved by the calculation of actual enterprise data.

The optimized scheduling scheme can not only meet the on-time delivery, but also improve the truck loading rate and reduce the total cost, composed of early cost in plant, delivery penalty cost and transportation cost. In the model validation, the optimal scheduling scheme uses one less truck than the traditional EDD scheme (saving 20% of the transportation cost), and the total cost can be saved by 17.22%.

This study clarifies the relationship between the production and transportation of precast components and establishes the integrated scheduling optimization model and its solution algorithm. Different from previous studies, the proposed optimization model can balance the timeliness and economy of production and transportation for precast components.

This study examines the effect of social media marketing on voting intention applying a combination of fuzzy logic methodology and a multidimensional panel data model.

The study adopts a multidimensional panel data method that includes several fixed effects. The dependent variable is a multifaceted construct that measures the participants’ intention to vote. The independent variables are electronic word of mouth (eWOM), customisation (CUS), entertainment (ENT), interaction (INT), trendiness (TRD), candidate’s perceived image (CPI), religious beliefs (RB), gender and age. The grouping variables that signify fixed effects are employment status, level of education, mostly used social media and religion. First, the significance of said fixed effects was tested through an ANOVA process. Then, the main model was estimated, including the significant grouping variables as fixed effects.

Employment status and level of education were significant fixed effects. Also, eWOM, ENT, INT, CPI, RB and gender significantly affected participants’ voting intention.

Being based on a questionnaire that asked participants about how they perceive different aspects of social media, the present study is limited to their perceptions. Therefore, further studies covering the voters’ behaviour in action could be efficient complements to the present study.

The findings could guide the political parties into prioritizing the aspects of social media in forming an effective campaign resulting in being elected.

The findings have the potential to help the public in making better informed decisions when voting. Furthermore, the results of this study indicate applications for social media which are beyond leisure time fillers.

Fuzzy logic and multidimensional panel data estimates are this study’s novelty and originality. Structural equation modelling and crisp linguistic values have been used in previous studies on social media’s effect on voting intent. The former refines the data gathered from a questionnaire, and the latter considers the possibility of including different grouping factors to achieve a more efficient and less biased estimation.

The main aim of this study is to highlight the significance of fostering social capital and improving the quality of work life (QWL) for the well-being of healthcare workers. The second objective of this research is to address a notable gap in the current knowledge by examining the mediating influence of QWL on the relationship between work-related social capital and life satisfaction within the healthcare profession.

This study used a cross-sectional research methodology to examine the complex relationships among the variables and included a sample of 330 individuals who are employed full-time in the healthcare profession in the North Indian Region.

The study confirms all research hypotheses, showing that social capital improves work life. Thus, work-life quality improves life satisfaction significantly. The mediation analysis in this study used bootstrapping to show that work-life quality mediates the association between social capital and life satisfaction.

Addressing social support issues and using effective human resource management tactics can improve employees’ work life and satisfaction. The findings are essential in collectivistic cultures because strong workplace relationships improve professional welfare.

This study differentiates itself by analysing social capital and QWL as multi-dimensional constructs inside the workplace, ensuring the results’ correctness and validity. This study provides a distinct viewpoint for scholars and practitioners, enhancing comprehension of the correlation between life satisfaction and work-related social capital within the healthcare industry.

The study examines how the three dimensions of homophily (attitude, background, and value) influence the perceived usefulness, credibility, and enjoyability of travel content and follower behavior (i.e. willingness to search for more information and intention to visit the destination and purchase the tourism product). Likewise, the study investigates how content perception influences follower behavior.

A sample of 621 Instagram users from generations Y and Z who follow at least one travel influencer and intend to travel in the next twelve months was collected through an online survey. Partial least squares structural equation modeling was adopted to examine the data.

Attitudinal homophily influences follower behavior, value homophily impacts content perception, and background homophily has a counterproductive effect. Likewise, content perceived as useful and credible induces the intention to visit and purchase the tourism product.

The generalization of the results must be performed with care, as the context of analysis is limited to a social platform and only includes Portuguese individuals.

The findings help managers better understand which homophily cues influence content perception and maximize influencer persuasion. Based on the results, they can better decide which travel influencers should endorse their tourism products.

Research on homophily has neglected the multidimensionality of the concept and its analysis in the tourism context. By using a consolidated approach to homophily, content perception, and follower behavior, this study contributes to the tourism marketing literature and expands influencer marketing research.

The main objective of this study is to examine the relationship between person-organization fit (P-O fit), job satisfaction (JS), workplace spirituality (WS) and turnover intentions in small and medium-sized enterprises (SMEs) and the moderate role of WS in these relationships.

Research data were collected by cross-sectional data collection methods. The sample contains 242 employees of SMEs in Indonesia. The analytical method used to test research hypotheses is moderate regression analysis.

The results show that P-O fit is an antecedent that can reduce turnover intention. JS has a negative effect on turnover intention and WS has a negative effect on turnover intention. WS moderates the relationship between P-O fit and turnover intention and the relationship between JS and turnover intention.

This study enhances the understanding of the importance of WS in reducing employee turnover intentions. This research also contributes to the research model based on fit theory and social exchange theory.

The practical implication of this research is to improve P-O fit in employees. Managers can manage the right people for the environment and the right environment for the individual. In other words, the organization must choose both. The most basic way to create a P-O fit for employees is to recruit employees suitable to organizational goals because, in general, SMEs rarely have a written vision and mission.

Through the of spirituality in the workplace, employees will experience a sense of meaning and purpose in their work, foster a sense of unity through positive relationships and achieve alignment between personal and organizational values. Consequently, this will diminish the inclination to seek employment elsewhere.

Although turnover intention in employees is considered necessary, there is still minimal research that discusses turnover intention and WS in SMEs. To the authors' knowledge, no one has tested WS on the relationship between PO fit and JS with turnover intention in SMEs.

The process of redesigning is one of the essential steps in upcycling, which comprises ideation, reconstruction and fitting. This paper aims to study the best practice of upcycling in the clothing industry. This study is an attempt to standardise upcycling/redesign process.

An exploratory approach was adopted to perform the research. This study draws on the multiple organisations involved in the upcycling of clothes. The organisations chosen for this study are located in Sweden and Romania using the snowball technique. Semi-structured interviews, direct and participatory observation approaches were used to collect information. The collected data are systematically analysed using NVivo 10 software.

This paper provides empirical insights into the diverse practices of upcycling. Process, product and demand-based were three fundamental approaches to performing the redesigning process. The fabric quality and durability, variations in size, colour and pattern, skills and efforts required in the extraction of parts and environmental consciousness and awareness were the main factors influencing upcycling process.

The use of the European case may miss best practices from the other region. This study may help scholars to understand the method of upcycling. A practitioner of upcycling can use the findings to improve and standardise the existing process. This research is beneficial for society, as this leads to the reduction of textile wastage.

This paper conceptualises some of the best practices of clothes redesign. This provides a good insight for the organisation for the improvement in the redesign business.

The purpose of this study is to investigate the factors affecting the cost of concrete component prefabrication using the moderating role of organizational readiness, compatibility and competitive pressure.

The information collected in this study was obtained from 188 questionnaires filled out online by civil engineers active in the Iranian construction industry. Data analysis was performed by partial least squares structural equation modeling.

The results reveal that perceived risk has the greatest impact on cost of using precast concrete components (PCC). Furthermore, the organizational readiness, competitive pressure and compatibility variables have moderating role in the relationship between perceived risk and perceived usefulness. The results can help policymakers and managers to apply the appropriate perspective and strategy to promote this method by illustrating the factors affecting the cost of using PCC in the building construction.

Using the variables of perceived risk, perceived usefulness, and perceived ease of use to predict factors affecting the cost of using PCC is considered as an innovation in this research. In addition to identifying the most important factors affecting the cost of PCC prefabrication in the construction industry, this research tries to identify the impact of environmental factors on the model by examining the moderating role of organizational readiness, competitive pressure and compatibility.

This study aims to explore factors that affect gendered consumption (male and female), willingness to pay (economic attributes) and the socio-cultural context of Gen-Z consumers towards specialty coffee as compared to other types in Taiwan.

Samoggia and Riedel’s (2018) theoretical framework is adopted to examine the concepts of interest. A mixed method approach comprising interviews and experimental taste tests was used to collect data from Gen-Z specialty coffee consumers in a purposive sampling manner.

The findings suggested the effect of price elasticity of demand where specialty coffee was perceived as an expensive commodity by young consumers, and hence, not a regularly purchased item. Nevertheless, specialty coffee was linked to health benefits, and a signal for conspicuous consumption – where café experiences facilitated self-promotion on sites like Instagram and Facebook. Finally, the findings alluded to a potential gender effect, with more female young consumers likely to consume specialty coffee as compared to their male counterparts.

This study is located within the context of Taiwan, which has been a tea-dominated consumption landscape for numerous decades. The use of an experimental design also presents a unique angle to elucidate sensory elements surrounding specialty coffee as a research design for Gen-Z research projects. The study points to the relevance of social context in the consumers’ behavioural patterns, which has been largely implicit within consumer behaviour scholarship.

Given the regional heterogeneity of economic development, electricity consumption in various regions exhibits a discrepant growth pattern. The purpose of this study is to construct a grey system forecasting model with intelligent parameters for predicting provincial electricity consumption in China.

First, parameter optimization and structural expansion are simultaneously integrated into a unified grey system prediction framework, enhancing its adaptive capabilities. Second, by setting the minimum simulation percentage error as the optimization goal, the authors apply the particle swarm optimization (PSO) algorithm to search for the optimal grey generation order and background value coefficient. Third, to assess the performance across diverse power consumption systems, the authors use two electricity consumption cases and select eight other benchmark models to analyze the simulation and prediction errors. Further, the authors conduct simulations and trend predictions using data from all 31 provinces in China, analyzing and predicting the development trends in electricity consumption for each province from 2021 to 2026.

The study identifies significant heterogeneity in the development trends of electricity consumption systems among diverse provinces in China. The grey prediction model, optimized with multiple intelligent parameters, demonstrates superior adaptability and dynamic adjustment capabilities compared to traditional fixed-parameter models. Outperforming benchmark models across various evaluation indicators such as root mean square error (RMSE), average percentage error and Theil’s index, the new model establishes its robustness in predicting electricity system behavior.

Acknowledging the limitations of traditional grey prediction models in capturing diverse growth patterns under fixed-generation orders, single structures and unadjustable background values, this study proposes a fractional grey intelligent prediction model with multiple parameter optimization. By incorporating multiple parameter optimizations and structure expansion, it substantiates the model’s superiority in forecasting provincial electricity consumption.

The success and long-term survival of service organizations depend on employee behavior such as work engagement and creativity. In this study, The authors intend to investigate employee engagement and creativity in the hospitality industry based on the theory of social exchange. In addition, The authors explore the mediating role of employee ambidexterity between ethical leadership and employee work engagement and between ethical leadership and employee creativity.

Through an online survey questionnaire, data were collected from 246 workers in the hospitality industry in Pakistan. Smart-PLS version 3 was used to analyze the data.

The results of the structural equation modeling reveal that ethical leadership has a positive association with work engagement and employee creativity in the hospitality industry. Results further reveal that employee ambidexterity significantly mediates the relationships between ethical leadership and work engagement and between ethical leadership and employee creativity.

This study not only makes an important contribution to the literature on the role of employee ambidexterity in the hospitality industry but will also help service businesses in managing their employees more effectively.