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Allocation of the marketing budget has become increasingly challenging due to the diverse channel exposure to customers. This study aims to enhance global marketing knowledge by introducing an ensemble attribution model to optimize marketing budget allocation for online marketing channels. As empirical research, this study demonstrates the supremacy of the ensemble model over standalone models.

The transactional data set for car insurance from an Indian insurance aggregator is used in this empirical study. The data set contains information from more than three million platform visitors. A robust ensemble model is created by combining results from two probabilistic models, namely, the Markov chain model and the Shapley value. These results are compared and validated with heuristic models. Also, the performances of online marketing channels and attribution models are evaluated based on the devices used (i.e. desktop vs mobile).

Channel importance charts for desktop and mobile devices are analyzed to understand the top contributing online marketing channels. Customer relationship management-emailers and Google cost per click a paid advertising is identified as the top two marketing channels for desktop and mobile channels. The research reveals that ensemble model accuracy is better than the standalone model, that is, the Markov chain model and the Shapley value.

To the best of the authors’ knowledge, the current research is the first of its kind to introduce ensemble modeling for solving attribution problems in online marketing. A comparison with heuristic models using different devices (desktop and mobile) offers insights into the results with heuristic models.

This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.

We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.

Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.

The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.

ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.

The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.

This paper focuses on the application of a robotic technique for modeling a three-wheeled mobile robot (WMR), considering it as a multibody polyarticulated system. Then the dynamic behavior of the developed model is verified using a physical model obtained by Simscape Multibody.

Firstly, a geometric model is developed using the modified Denavit–Hartenberg method. Then the dynamic model is derived using the algorithm of Newton–Euler. The developed model is performed for a three-wheeled differentially driven robot, which incorporates the slippage of wheels by including the Kiencke tire model to take into account the interaction of wheels with the ground. For the physical model, the mobile robot is designed using Solidworks. Then it is exported to Matlab using Simscape Multibody. The control of the WMR for both models is realized using Matlab/Simulink and aims to ensure efficient tracking of the desired trajectory.

Simulation results show a good similarity between the two models and verify both longitudinal and lateral behaviors of the WMR. This demonstrates the effectiveness of the developed model using the robotic approach and proves that it is sufficiently precise for the design of control schemes.

The motivation to adopt this robotic approach compared to conventional methods is the fact that it makes it possible to obtain models with a reduced number of operations. Furthermore, it allows the facility of implementation by numerical or symbolical programming. This work serves as a reference link for extending this methodology to other types of mobile robots.

This paper aims to introduce an alternative for modeling levitation forces between NdFeB magnets and bulks of high-temperature superconductors (HTS). The presented approach should be evaluated through two different formulations and compared with experimental results.

The T-A and H-ϕ formulations are among the most efficient approaches for modeling superconducting materials. COMSOL Multiphysics was used to apply them to magnetic levitation models and predict the forces involved.The permanent magnet movement is modeled by combining moving meshes and magnetic field identity pairs in both 2D and 3D studies.

It is shown that it is possible to use the homogenization technique for the T-A formulation in 3D models combined with mixed formulation boundaries and moving meshes to simulate the whole device’s geometry.

The case studies are limited to the formulations’ implementation and a brief assessment regarding degrees of freedom. The intent is to make the simulation straightforward rather than establish a benchmark.

The H-ϕ formulation considers the HTS bulk domain as isotropic, whereas the T-A formulation homogenization approach treats it as anisotropic. The originality of the paper lies in contrasting these different modeling approaches while incorporating the external magnetic field movement by means of the Lagrangian–Eulerian method.

Building permitting is mostly a manual, labor intensive and time-consuming process. Initiatives for streamlining the process are not always helpful since they often fail to address the core problems within the process. A framework for modeling the permitting process can be useful to identify bottlenecks, core challenges and best practices. Hence, the authors aim to demonstrate and validate a previously suggested workflow for permit process modeling using the permitting process in Israel as a test case.

The authors implement qualitative expert interviews for data acquisition. The collected data are then processed for a qualitative data analysis. The results of the analysis are then validated using a focus group workshop in the field of building permits. In the test case the focus group consisted of Israeli experts.

The authors present a detailed overview of the as-is building permit process in Israel and the existing challenges. Through this test case, the authors found that the framework is applicable in different countries and that it can provide valuable insights into the core problems within the process. In addition, application of the same framework in different countries can provide comparable results that would allow the authors to identify best practices.

The major contribution of this work is the development and validation of a framework for building permitting process modeling which can be used to identify existing challenges and bottlenecks in the process. Implementing a structured and unified approach provides an opportunity to easily compare processes in different countries to identify best practices.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

The purpose of this paper is to introduce a novel cross (+) type yoke with hybrid electromagnets and new reluctance modeling to precisely calculate attraction force is given.

The comparison of attraction force and torque analyses between the proposed formulation and the existing formulation in the literature is comparatively presented. For the correctness of the force and torque values calculated in the model created, the system was created in ANSYS Maxwell and its accuracy was proved by making analyses. The maglev carrier system is inherently unstable from the point of view of control engineering. For that, it needs an active controller to eliminate this instability. For the levitation of the carrier system, it is necessary to design a controller in three axes (z, α and β). I-PD controller was designed for the air gap control of the carrier system in three axes and the controller parameters were determined by the canonical method.

While the new formulation proposed in the modeling of the carrier system has a maximum error of 1.03%, the existing formula in the literature has an error of 16.83% in the levitation distance point.

A novel cross-type hybrid carrier system has been proposed in the literature. With the double integral used in modeling the system, it takes a long time to solve symbolically, and it is difficult to simulate dynamic behavior in control validation. To solve this problem, attraction force and inclination torque values are easily characterized by new formulation and besides the simulations are conducted easily. The experimental setup was manufactured and assembled, and the carrier system was successfully levitated, and reference tracking was performed without overshoot.

The purpose of this paper is to model a process for moving toward sustainable ecosystem service decisions in a Coastal Biodiversity and discuss the directions of the process for decision-makers to apply in ocean ecosystem services.

After the development of theoretical approaches to understand their prospects for the future development of ecosystem services, the authors worked on a process for developing factors for sustainable decision-making. It uses the Delphi method to develop all the factors supported by six dimensions in two specific moments: deductive-inductive and inductive-deductive.

This process of modeling the factors expands the possibility of adaptive governance to make prior and subsequent decisions using factors related to dimensions, stakeholders and benefits, risks, opportunities and costs.

Considering the limitations, future studies could use another database to widen the view in terms of the studies, factors, dimensions and other additional information to maintain the evolution of this process in ocean ecosystem services decision-making. Another limitation arose in the number of projects and experts defining the factors. This may prevent the opportunity to have more impact in terms of future decisions if more sources are used in the market. In addition, time and the access to experts during this modeling process demonstrate a limitation, as does the time for feedback.

This set of factors developed for adaptive governance decision-making can be applied to develop a prior alignment of stakeholder interests with sustainable practices.

This set of factors developed with the intervention of experts reinforces the importance of sustainable collective decisions on ocean ecosystem services. This is a joint approach with participants in the NextOcean project, sponsored by the European Commissions (EC)’s Horizon 2020 program. An Earth Observation-based Consortia aims to create sustainable value for Space, Land and Oceans.

This modeling process generated dimensions and factors to support adaptive governance stakeholders in making sustainable decisions in a coastal biodiversity zone.

Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable competitive advantage and cope with uncertainties as well as disruptions. Although a wide range of studies exists on supply chain agility (SCA) from the perspective of antecedents or consequences, there is little research on the investigation of enablers of SCA and their relations among them. Furthermore, the literature has investigated proactive and reactive enablers for enhancing SCA, but most studies have not sufficiently framed their analysis of both aspects synchronically. This paper aims to find out the interrelationships among the proactive and reactive enablers for enhancing SCA.

An extensive literature review has been conducted to identify SCA enablers and a Delphi study has been performed to elucidate SCA enablers in the manufacturing industry in Turkey. Interpretive structural modeling (ISM) has been used to identify the contextual relationship among the SCA enablers, and the model has been validated based on Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC) analysis.

On theoretical and practical levels, the proposed ISM model in this study can help organizations analyze and interpret interrelationships among enablers of SCA. For managers, it can provide better insights and understanding of the facilitators of SCA to enhance the effectiveness of the supply chain and cope with uncertainties and turbulence. According to results, enhancing “supply and demand side competency”, “delivery speed” and “strategic sourcing” are the most significant enablers of SCA.

The study extends the existing literature related to the enablers of SCA by modeling the proactive and reactive enablers of SCA based on the Al Humdan et al. (2020) classification. Arranging the enablers of SCA in a hierarchy and classifying the enablers into different levels with the help of the ISM-MICMAC approach is an exclusive effort to achieve successful management of the supply chain.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.