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The purpose of this paper is to investigate whether employees' understanding of their organization's strategic objectives could be used by business organizations to develop a desired type of organizational culture that will improve business performance.

Structural equation modeling (SEM) was conducted on the data collected in 2018 from professionals working in the healthcare industry in the USA.

SEM revealed the positive effect of employee understanding of their organization's strategic objectives on the development of a serving culture, and the mediating effect of serving culture on the relationship between employee understanding of strategic objectives and performance.

This study emphasizes that having a well-defined mission and strategic goals may not be sufficient. Business organizations must also ensure that all employees clearly understand the meaning of such objectives. Employee understanding can become instrumental, as it could allow business organizations to develop a desired type of organizational culture that will support the implementation of the firm's strategic objectives.

The study is a valuable addition to past research. First, it advances the literature on strategy by exploring the critical role of employee understanding of their organization's strategic objectives in the context of culture and performance. Thus, it allows scholars to better explain how business organizations could more effectively utilize their process of strategic planning. In the domain of organizational culture, the paper contributes by identifying a new antecedent of serving culture. Furthermore, the paper also contributes to the literature on service management by identifying a mechanism that service organizations could use to increase their performance.

Although social distancing measures enacted during COVID-19 prevented the spread of the virus and acted as important coping mechanisms during this stressful time, they also contributed to loneliness and anxiety. The pros and cons of social distancing measures were especially relevant among people with disabilities and chronic health conditions – a high-risk group concerned about infection through contact with non-household members and visiting public places like school, healthcare providers, and work.

Drawing on data from a national online survey (N = 1,027) and in-depth virtual interviews (N = 50) with Canadians with disabilities and chronic health conditions, we examine the positive and negative effects of three types of social distancing measures – avoiding public places, transitioning to remote work or school, and avoiding contact with non-household members – on perceptions of increases in anxiety and loneliness during the pandemic.

We find that the relationships between engaging with social distancing measures and anxiety and loneliness could be positive or negative, with measures acting as both adaptive and maladaptive coping mechanisms. Although avoiding public places or non-household members and transitioning to remote work or school often resulted in increased anxiety and loneliness, respondents also described situations where these measures helped them cope with concerns about catching COVID-19.

Our findings highlight potential implications for public health policy in allocating different coping resources among marginalized groups during times of crisis and demonstrate the importance of using a social model of stress, coping mechanisms, and mental health.

A new coupled model is developed to simulate the interaction between fluid droplet collisions on discrete particles (DPs) by using mathematic function.

In this model, the smoothed particle hydrodynamics (SPH) is used based on the kernel function and the time step which takes into consideration to the fluid domain in accordance with the discrete element method (DEM) with resistance function. The interaction between fluid and DPs consists of three parts, which are repulsive force, viscous shear force and attractive force caused by the capillary action. The numerical simulation of droplet collision on DPs presents the whole process of droplet motion. Otherwise, an experimental data were conducted to record the realistic process for verification.

The comparison result indicated that the numerical simulation is capable of capturing the entire process for droplet collision on DPs.

However, based on the difference of experimental environment, type of the DP and setups, the maximum spreading dimeters of could not fit the experimental data exactly.

In sum, the coupled SPH-DEM method simulation shows that the coupled model of SPH-DEM developed an entire effectiveness process for fluid–solid interaction problem.

In recent years patents have become a very popular data source for forecasting technological changes. However, since a vast amount of patents are “worthless” (Moore, 2005), there is a need to identify the promising ones. For this purpose, previous approaches have mainly used bibliographic data, thus neglecting the benefits of textual data, such as instant accessibility at patent disclosure. To leverage these benefits, this study aims to develop an approach that uses textual patent data for predicting promising patents.

For the identification of promising patents, the authors propose a novel approach which combines link prediction with textual patent data. Thereby the authors are able to predict the emergence of hitherto unmentioned bigrams. By mapping these future bigrams to recent patents, the authors are able to distinguish between promising and nonpromising patents. To validate this approach, the authors apply the methodology to the case example of camera technology.

The authors identify stochastic gradient descent as a suitable algorithm with both a receiver operating characteristic area under curve score and a positive predictive value of 78%, which outperforms chance by a factor of two. In addition, the authors present promising camera patents for diverse application fields, such as cameras for surgical systems, cameras for rearview vision systems in vehicles or light amplification by stimulated emission of radiation detection and ranging cameras for three-dimensional imaging.

This study contributes in at least three directions to scholarship. First, the authors introduce a novel approach by combining link prediction with textual patent analysis and, in this way, leverage the benefits of both worlds. Second, the authors add to all theories that regard novel technologies as a recombination of existing technologies in presenting word combinations from textual data as a suitable instrument for revealing recombination in patents. And third, the approach can be used by scholars as a complementary or even integrative tool with conventional forecasting methods like the Delphi technique or Scenario planning.

At least three practical implications arise from the study. First, incumbent firms of a technology branch can use this approach as an early-warning system to identify technological change and to identify opportunities related to their company’s technological competence and provide inspiration for new ideas. Second, companies seeking to tap into new markets may also be interested in the approach as managers could anticipate whether their company’s technological competences are in line with upcoming trends. Third, the approach may be used as a supportive tool for various purposes, such as investment decisions or technology life cycle analysis.

The approach introduces textual patent data as suitable means for forecasting activities. As the statistical validation reveals, the promising patents identified by the approach are cited significantly more often than patents with less promising prospects.

Construction projects usually suffer delays, and the causes of these delays and its cost overruns have been widely discussed, the weather being one of the most recurrent. The purpose of this paper is to analyze the influence of climate on standard construction work activities through a case study.

By studying the extent at which some weather variables impede outdoor work from being effectively executed, new maps and tables for planning for delays are presented. In addition, a real case regarding the construction of several bridges in southern Chile is analyzed.

Few studies have thoroughly addressed the influences of major climatic agents on the most common outdoor construction activities. The method detailed here provides a first approximation for construction planners to assess to what extent construction productivity will be influenced by the climate.

Although this study was performed in Chile, the simplified method proposed is entirely transferable to any other country, however, other weather or combinations of weather variables could be needed in other environments or countries.

The implications will help reducing the negative social, economic and environmental outcomes that usually emerge from project delays.

Climatic data were processed using extremely simple calculations to create a series of quantitative maps and tables that would be useful for any construction planner to decide the best moment of the year to start a project and, if possible, where to build it.

This paper aims to introduce a two-dimensional smoothed particle hydrodynamics (SPH) framework for simulating the evaporation and combustion process of fuel droplets.

To solve the gas–liquid two-phase flow problem, a multiphase SPH method capable of handling high density-ratio problems is established. Based on the Fourier heat conduction equation and Fick’s law of diffusion, the SPH discrete equations are derived. To effectively characterize the phase transition problem, inspired by volume of fluid method, the concept of liquid phase mass fraction of the SPH particles is proposed. The one-step global reaction model of n-hexane is used for the vapor combustion.

The evaporation and combustion process of single droplet conforms to the law. The framework works out well when the evaporation of multiple droplets involves coalescence process. Three different kinds of flames are observed in succession in the combustion process of a single droplet at different inflow velocity, which agree well with the results of the experiment.

To the best of the authors’ knowledge, this is the first computational framework that has the capability to simulate evaporation and combustion with SPH method. Based on the particle nature of SPH method, the framework has natural advantages in interface tracking.

The purpose of this paper is to enhance the compatibility of titanium dioxide in epoxy resins and thus the corrosion resistance of the coatings.

In this work, TiO₂ was modified by the mechanochemistry method where mechanical energy was combined with thermal energy to complete the modification. The stability of modified TiO₂ in epoxy was analyzed by sedimentation experiment. The modified TiO₂-epoxy coating was prepared, and the corrosion resistance of the coating was analyzed by open circuit potential, electrochemical impedance spectroscopy and neutral salt spray test.

High-temperature mechanical modification can improve the compatibility of TiO₂ in epoxy resin. At the same time, the modified TiO₂-epoxy coating showed better corrosion resistance. Compared to the unmodified TiO₂-epoxy coating, the coating improved the dry adhesion force by 61.7% and the adhesion drop by 33.3%. After 2,300 h of immersion in 3.5 Wt.% NaCl solution, the coating resistance of the modified TiO₂ coating was enhanced by nearly two orders of magnitude compared to the unmodified coating.

The authors have grafted epoxy molecules onto TiO₂ surfaces using a high-temperature mechanical force modification method. The compatibility of TiO₂ with epoxy resin is enhanced, resulting in improved adhesion of the coating to the substrate and corrosion resistance of the coating.

The customer enquiry management (CEM) process is of strategic importance in engineer‐to‐order contexts but existing literature does not adequately describe how firms support delivery date setting and order acceptance decisions in practice. This paper seeks to explore how and why the CEM process varies between companies in the capital goods sector, thereby taking a contingency theory approach.

Multi‐case study research involving 18 Italian capital goods manufacturers in four industrial sectors. Face‐to‐face interviews with senior representatives have been conducted. Companies have been grouped into five clusters, based on similarities in their CEM decision‐making modes, to aid analysis.

Three contingency factors were found to be particularly relevant in determining CEM modes: degree of product customization, flexibility of the production system, and uncertainty of the context. These factors affect the choice of specific CEM decision‐making modes. However, a high level of cross‐functional coordination and formalization of the process were found to constitute best practices whatever the contingency factors.

The research focuses on companies belonging to the Italian capital goods sector – findings may differ in other countries and sectors.

The results indicate that all firms, including small and medium‐sized companies, should implement high levels of cross‐functional coordination and formalization in their CEM practices, in order to improve their performance. For other aspects of the CEM process, including supplier and subcontractor monitoring, the company context will indicate whether these aspects are required, according to a need of matching the approach to CEM with specific sets of contingency factors.

This paper provides a rare insight into the CEM processes found in practice.

Design-Build (DB) is known as the alternative for Design-Bid-Build in the Malaysian construction industry. For DB projects, it is critical to adopt effective decision support tool to ensure the execution of a systematic decision-making technique. This study aimed to examine the impact of a decision support tool for novice decision makers to reject or adopt DB for their construction projects.

Literature review and qualitative input from experts identified several key-selection factors pertaining to critical success factors and design-build drivers. This resulted in the development of Decision Support Tool for Design-Build (DST-DB). A quasi-experiment, which involved 382 novice decision makers in the construction industry, was conducted to test the DST-DB quantitatively. The participants were required to compare two construction projects using DST-DB and traditional decision-making methods. Multivariate analysis was performed to analyse all collected data.

The quasi-experiment data suggests that DST-DB enables significantly higher usability, likelihood, precision, confidence and satisfaction rate when compared to the traditional decision-making process. The pre- and post-surveys indicated that the DST-DB is effective in improving decision-making performance through selection factors of client-briefing, maximised resources and sharing expertise. The participants also agreed that DST-DB is easy to use and helps them to gain better understanding of the decision-making process for construction projects.

This research contributes to the existing body of knowledge through the impact of DST on the decisions of novices. The novice decision makers found that DST-DB is practically adaptable and comparatively effective for decision-making process than traditional decision-making methods. This contributes to the practical application of construction companies to provide DST-DB training to the fresh graduate employees to enhance their competencies in the decision-making process.

Dynamic planning and scheduling forms a widely adopted smart strategy for solving real-world problems in diverse business systems. This paper uses deductive content analysis to explore secondary data from previous studies in dynamic planning and scheduling to draw conclusions on its current status, forward action and research needs in construction management.

The authors searched academic databases using planning and scheduling keywords without a periodic setting. This research collected secondary data from the database to draw an objective comparison of categories and conclusions about how the data relates to planning and scheduling to avoid the subjective responses from questionnaires and interviews. Then, applying inclusion and exclusion criteria, we selected one hundred and four articles. Finally, the study used a seven-step deductive content analysis to develop the categorisation matrix and sub-themes for describing the dynamic planning and scheduling categories. The authors used deductive analysis because of the secondary data and categories comparison. Using the event types represented in a quadrant mapping, authors delve into where, when, application and benefits of the classes.

The content analysis showed that all the accounts and descriptions of dynamic planning and scheduling are identifiable in an extensive research database. The content analysis reveals the need for multi-hybrid (4D BIM-Agent based-discrete event-discrete rate-system dynamics) simulation modelling and optimisation method for proffering solutions to scheduling and planning problems, its current status, tools and obstacles.

This research reveals the deductive content analysis talent in construction research. It also draws direction, focuses and raises a question on dynamic planning and scheduling research concerning the five-integrated model, an opportunity for their integration, models combined attributes and insight into its solution viability in construction.