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Paint path planning for industrial robots is critical for uniform paint distribution, process cycle time and material waste, etc. However, paint path planning is still a costly and time‐consuming process. Currently paint path planning has always caused a bottle‐neck for manufacturing automation because typical manual teaching methods are tedious, error‐prone and skill‐dependent. Hence, it is essential to develop automated tool path‐planning methods to replace manual paint path planning. The purpose of this paper is to review the existing automated tool path‐planning methods, and investigate their advantages and disadvantages.

The approach takes the form of a review of automated tool path‐planning methods, to investigate the advantages and disadvantages of the current technologies.

Paint path planning is a very complicated task considering complex parts, paint process requirements and complicated spraying tools. There are some research and development efforts in this area. Based on the review of the methods used for paint path planning and simulation, the paper concludes that: the tessellated CAD model formats have many advantages in paint path planning and paint deposition simulation. However, the tessellated CAD model formats lack edge and connection information. Hence, it may not be suitable for some applications requiring edge following, such as welding. For the spray gun model, more complicated models, such as 2D models, should be used for both path planning and paint distribution simulation. Paint path generation methods should be able to generate a paint path for complex automotive parts without assumptions, such as presupposing a part with a continuous surface.

The paper makes possible automated path generation for spray‐painting process using industrial robots such that the path‐planning time can be reduced, the product quality improved, etc.

The paper provides a useful review of current paint path‐planning methodologies based on the CAD models of parts.

This article deals with how to test for and evaluate interdependence among control practices in a management control system using structural equation modeling. Empirical research on the levers of control (LOC) framework is used as an example. In LOC research, a path model approach to interdependence has been developed. The appropriateness of this approach is evaluated, developed, and compared with the correlation of residuals approach (seemingly unrelated regression) implemented in the wider complementarity literature. Empirical examples of the different models are shown and compared by using a data set on LOC of 120 SBUs in Sweden. The empirical results show that modeling interdependence among control practices in a management control system as non-recursive (bi-directional) paths or as residual correlations evidently affects the conclusions drawn about interdependence in terms of both presence and magnitude. The two models imply different views on how to conceptualize interdependence and are not statistically and empirically comparable. If using non-recursive path models, several model specification issues appear. To be able to identify such models, this needs to be carefully considered in the theory and research design prior to data collection.

This paper attempts to demystify the technique of causal path modeling for the non‐specialists by presenting aspects of its value for social science and management research and by illustrating common misunderstandings about its attributes. Special emphasis is placed on the real world validity of causal relationships depicted in causal path models and on the information that the data‐fitting properties of causal path models provide regarding this issue. Causal path models that are based on research in antecedents of career success are used to illustrate the points that are made. It is stressed that the validity of causal relationships depicted in causal path models is subject to exactly the same methodological restrictions as the validity of causality claims that are made without the use of causal path modeling; and that the purpose of using quantitative techniques in causal path modeling is not to improve certainty on causality direction.

In order to determine the status quo of PLS path modeling in international marketing research, we conducted an exhaustive literature review. An evaluation of double-blind reviewed journals through important academic publishing databases (e.g., ABI/Inform, Elsevier ScienceDirect, Emerald Insight, Google Scholar, PsycINFO, Swetswise) revealed that more than 30 academic articles in the domain of international marketing (in a broad sense) used PLS path modeling as means of statistical analysis. We assessed what the main motivation for the use of PLS was in respect of each article. Moreover, we checked for applications of PLS in combination with one or more additional methods, and whether the main reason for conducting any additional method(s) was mentioned.

Enterprises often face a wide variety of adverse events. Adverse events can have negative effects on organizations like failures of resources. In case resources fail, they are not available and cannot perform the assigned work. Enterprises are therefore especially interested in how resilient processes and workflows are in case adverse events occur and resources may fail. For this purpose, process resilience measurement approaches are needed.

To measure the resilience of processes and workflows, a life cycle and five quantitative metrics have been developed. The metrics have been validated using five real-world production and logistics cases to show their applicability on process models and paths. Furthermore, workshops have been conducted with professionals to get additional feedback on the contributions.

Based on the results obtained from applying the metrics to five real-world cases, view-based resilience improvements can be derived. Overall, only one of the five real-world cases can be considered as completely resilient. Furthermore, the metrics and life cycle have been especially valued by professionals with respect to transparency, independency, comparability as well as the ability to determine critical process paths.

Several authors have dealt with different aspects related to the measurement of business processes, resilience or a combination thereof. However, a life cycle or metrics to quantitatively measure the resilience of processes by considering resources has not been found yet. The life cycle and metrics are therefore novel. As a future research direction, they can be applied in different domains for further validation purposes.

The purpose of this paper is to propose a novel curvilinear path estimation model employing multivariate adaptive regression splines (MARS) for mid vehicle collision avoidance. The two-phase path estimation scheme initially uses the offset (position) value of the front and the mid (host) vehicle to build the crisp model. The resulting crisp model is MARS regressed to deliver a closely aligned actual model in the second phase. This arrangement significantly narrows the gap between the estimated and the true path analyzed using the mean square error (MSE) for different offsets on Next Generation Simulation Interstate 80 (NGSIM I-80) data set. The presented model also covers parallel parking by encompassing the reverse motion of the host vehicle in the path estimation, thereby, making it amicable for real-road scenarios.

The two-phase path estimation scheme initially uses the offset (position) value of the front and the mid (host) vehicle to build the crisp model. The resulting crisp model is MARS regressed to deliver a closely aligned actual model in the second phase.

This arrangement significantly narrows the gap between the estimated and the true path studied using MSE for different offsets on real (Next Generation Simulation-NGSIM) data. The presented model also covers parallel parking by encompassing the reverse motion of the host vehicle in the path estimation. Thereby, making it amicable for real-road scenarios.

This paper builds a mathematical model that considers the offset and host (mid) vehicles for appropriate path fitting.

This study examined a mediating model of income and pay satisfaction with a direct path (income → pay satisfaction) and an indirect path with two mediators (income → the love of money → pay equity comparison → pay satisfaction). Results of the whole sample showed that the indirect path was significant and the direct path was insignificant. When the indirect path was eliminated, income contributed positively to pay satisfaction. We then tested the model across two moderators: culture (the United States versus Spain) and gender. This study provides the following theoretical and empirical contributions: the direct relationship between income and pay satisfaction depends on the indirect path and the extent to which (1) income enhances the love of money and (2) the love of money is applied to evaluate pay equity comparison satisfaction. If both conditions exist, income leads to pay dissatisfaction. If the second condition does not exist, income does not lead to pay dissatisfaction. Pay satisfaction depends on (1) one’s love of money and (2) how one compares. The role of the love of money in pay satisfaction is “not”universal across cultures and gender.

Wireless communication channel provides a wide area of applications in the field of communication, distributed sensor network and so on. The prominence of the wireless communication channel is because of its robust nature and the sustainability for the precise ranging and the localization. The precision and accuracy of the wireless communication channel largely depend on the localization. The development of the wireless communication channel with improved benefits needs the accurate channel model.

This paper characterizes the tangential path loss model in the WINNER based wireless communication channel model. The measurements taken in the WINNER channel model are compared with the tangential path loss characterized WINNER Channel model.

The model operates well over the varying antenna orientations, measurement condition and the propagation condition. The proposed tangential path loss model is performing well over the various outdoor scenarios.

The proposed characterization shows change in the small-scale parameters (SSP), such as power, delay, angle of arrival and angle of departure as well as the large-scale parameters (LSP), such as RMS delay spread, shadowing, path loss and Ricean factor associated with the model.

Network coverage is crucial for the adoption of advanced Smart Home applications. The commonly used log-based path loss model is not able to accurately estimate WiFi signal strength in different houses, as it does not fully consider the impact of building morphology. To better describe the propagation of WiFi signals and achieve higher estimation accuracy, this paper studies the basic building morphology characteristics of houses.

A new path loss model based on a decision tree was proposed after measuring the WiFi signal strength passing through multiple housing units. Three types of regression models were tested and compared.

The findings demonstrate that the log-based path loss model fits small houses well, while the newly proposed nonlinear path loss model performs better in large houses (area larger than 125 m2 and area-to-perimeter ratio larger than 2.5). The impact of building design on path loss has been proven and specifically quantified in the model.

Proposed an improved model to estimate indoor network coverage. Quantify the impacts of building morphology on indoor WiFi signal strength. Improve WiFi signal strength estimation to support Smart Home applications.