Search results

This paper aims to determine the relationship between dynamic marketing capabilities (DMCs) and the integration of distribution channels of exporting companies from Latin American (LATAM) countries and how this relationship will impact the international development of a company.

This qualitative study uses the explanatory multiple case approach of Yin (2011) to test the research questions, revise existing theories and establish causal relationships from semi-structured interviews that were applied to 15 Peruvian and Colombian companies. To analyze qualitative data and ensure credibility, the authors applied six stages of Sinkovics and Alfoldi’s (2012) methodology. For analysis, computer-based qualitative software was used.

The study reveals the following: a set of specific DMCs that effectively help agro-food companies generate synergy with their intermediaries to launch their first international ventures; a better understanding of how the market orientation as a DMC is, rather than a multi-dimensional organization which mediates other marketing processes; the impact of DMCs in channel integration that changes with respect to agents and distributors. Producers and distributors developed networking, market adaptation and innovation capabilities. At the same time, agents also developed market orientation capabilities to provide relevant product information, manage transactions and fulfill orders without regard to market adaptation capabilities.

Qualitative methodology was applied, limiting the generalization of the findings. The authors also emphasized the initial stages of internationalization without considering other advanced processes that could be useful for larger LATAM companies, which operate in different foreign countries and manage multiple channels. As a result, this study lays the foundation for establishing a model that will enhance a quantitative measurement to support the findings.

This study illustrates specific marketing techniques that are useful to better identify and coordinate intermediaries, especially agents and distributors to ease their internationalization processes. The research also provides a framework for marketing managers to leverage the DMCs developed by the different actors of the distribution channel, as well as, obtaining positive outcomes in communication, information on products and services, transactions and customer service functions. Finally, managers and professionals can find a methodology to evaluate how DMCs can be developed to optimize their internationalization processes through the integration of the main channel functions. This will broaden their vision on the usefulness and scalability of this type of dynamic capabilities in key business processes for the generation and sustainability of competitive advantages.

If producers identify DMCs, they will promote ethical business practices that may reduce their vulnerability and risk with more experienced international intermediaries. This leads to favoring the socio-economic equity of the territories with traditional economies in which they operate.

The study provides a set of DMCs that influence the functions of distribution channels and favors international processes in small and medium enterprises which then offer a better understanding of the definition and applicability of this construct in the agro-food sector in LATAM. This study also gives a structural perspective to determine which functions of the distribution channel should be integrated and how depending on the type of intermediary (agents and distributors).

The purpose of this review paper is to provide a review of the most recent advances in the field of manufacturing composite sandwich panels along with their advantages and limitations. The other purpose of this paper is to familiarize the researchers with the available developments in manufacturing sandwich structures.

The most recent research articles in the field of manufacturing various composite sandwich structures were reviewed. The review process started by categorizing the available sandwich manufacturing techniques into nine main categories according to the method of production and the equipment used. The review is followed by outlining some automatic production concepts toward composite sandwich automated manufacturing. A brief summary of the sandwich manufacturing techniques is given at the end of this article, with recommendations for future work.

It has been found that several composite sandwich manufacturing techniques were proposed in the literature. The diversity of the manufacturing techniques arises from the variety of the materials as well as the configurations of the final product. Additive manufacturing techniques represent the most recent trend in composite sandwich manufacturing.

This work is valuable for all researchers in the field of composite sandwich structures to keep up with the most recent advancements in this field. Furthermore, this review paper can be considered as a guideline for researchers who are intended to perform further research on composite sandwich structures.

The lightning phenomenon is one of the main threats in photovoltaic (PV) applications. Suitable protection systems avoid major damages from direct strikes but also nearby strikes may induce overvoltage transients in the module itself and in the power conditioning circuitry, which can permanently damage the system. The effects on the PV system sensibly depend on the converter topology and on the adopted power switch. In the present study, a comparative analysis of the transient response due to a nearby lightning strike (LS) is carried out for three PV systems, each equipped with a different converter, namely, boost, buck and buck–boost, based on either silicon carbide metal oxide semiconductor field effect transistors (SiC MOSFET) or insulated gate bipolar transistors controlled power switch devices, allowing in this way an analysis at different switching frequencies. The purpose of this paper is to present the results of the numerical analysis to help the design of suited protection systems.

Using a recently introduced three-dimensional semi-analytical method to simulate the electromagnetic transients caused in PV modules by nearby LSs, we investigate numerically the effect of a LS on the electronic circuits connecting the module to the alternate current (AC) power systems. This study adopts numerical simulations because experimental analyses are not easy to perform and does not grant a sufficient coverage of all statistically relevant aspects. The approach was validated in a previous paper against available experimental data.

It is found that the load voltage is not severely interested by the strike effects, thanks to the low pass filters present at the converter output, whereas a relatively high overvoltage develops between the negative pin of the inner circuitry and the “ground” voltage reference. The overcurrent present in the active switches is hardly comparable because of the different topologies and working frequencies; however, the highest overcurrent is observed in the buck converter topology, with SiC MOSFET technology, although it shows the fastest decay.

This research proposes, to the best of the authors’ knowledge, a comprehensive comparison of the indirect lighting strike effects on the converter connected to PV panels. A proper design of the lightning and surge protection system should take into account such aspects to reduce the risk of induced overvoltage and overcurrent transients.

The problem of direct measurement of magnetic fields is in several cases not trivial when the region of interest is not directly accessible, or when conventional probes could be of disturbance. There are several “indirect” schemes, based on different physical effects, proposed as alternative to direct probing. We discuss here a novel technique for the identification of 1‐D and 2‐D magnetic fields, based on the analysis of trajectories of charged projectiles crossing the region under analysis. The magnetic field map is obtained through an inverse formulation of the motion problem of charged particles in the field. The inverse problem is solved by minimization procedures that identify the coefficients of suitable representations for the field. In this way we are able to identify typical magnetic field configurations with great accuracy even in presence of noisy data. We give an overview on the method for the 1‐D and 2‐D cases, with reference to the field representation and the used optimization algorithms; moreover, the robustness of the technique in presence of noisy data is assessed via a numerical analysis.

Inverse problems in electromagnetism, namely, the recovery of sources (currents or charges) or system data from measured effects, are usually ill-posed or, in the numerical formulation, ill-conditioned and require suitable regularization to provide meaningful results. To test new regularization methods, there is the need of benchmark problems, which numerical properties and solutions should be well known. Hence, this study aims to define a benchmark problem, suitable to test new regularization approaches and solves with different methods.

To assess reliability and performance of different solving strategies for inverse source problems, a benchmark problem of current synthesis is defined and solved by means of several regularization methods in a comparative way; subsequently, an approach in terms of an artificial neural network (ANN) is considered as a viable alternative to classical regularization schemes. The solution of the underlying forward problem is based on a finite element analysis.

The paper provides a very detailed analysis of the proposed inverse problem in terms of numerical properties of the lead field matrix. The solutions found by different regularization approaches and an ANN method are provided, showing the performance of the applied methods and the numerical issues of the benchmark problem.

The value of the paper is to provide the numerical characteristics and issues of the proposed benchmark problem in a comprehensive way, by means of a wide variety of regularization methods and an ANN approach.

While many see the 1960s as the era of a “rights revolution” in American law, this article looks back from the present moment of conservative legal dominance to better understand the ways in which conservative ideas began to grow during the heyday of legal liberalism. Using recent histories of post-1945 grassroots conservatism, the author argues that conservative rights claims – while often legally questionable – constituted for many a powerful and persuasive understanding of the Constitution. Due to this popular conservative jurisprudence's endurance and influence, its existence in the 1960s forces reconsideration of understandings of the 1960s as the era of the “rights revolution.”

This study aims to investigate the possible use of a deep neural network (DNN) as an inverse solver.

Different models based on DNNs are designed and proposed for the resolution of inverse electromagnetic problems either as fast solvers for the direct problem or as straightforward inverse problem solvers, with reference to the TEAM 25 benchmark problem for the sake of exemplification.

Using DNNs as straightforward inverse problem solvers has relevant advantages in terms of promptness but requires a careful treatment of the underlying problem ill-posedness.

This work is one of the first attempts to exploit DNNs for inverse problem resolution in low-frequency electromagnetism. Results on the TEAM 25 test problem show the potential effectiveness of the approach but also highlight the need for a careful choice of the training data set.

This paper aims to develop a methodology for progressive finite element (FE) modeling of transformers, from simple to complex models of both magnetic cores and windings.

The progressive modeling of transformers is performed via a subproblem (SP) FE method. A complete problem is split into SPs with different adapted overlapping meshes. Model refinements are performed from ideal to real flux tubes, one-dimensional to two-dimensional to three-dimensional models, linear to nonlinear materials, perfect to real materials, single wire to volume conductor windings and homogenized to fine models of cores and coils, with any coupling of these changes.

The proposed unified procedure efficiently feeds each SP via interface conditions (ICs), which lightens mesh-to-mesh sources transfers and quantifies the gain given by each refinement on both local fields and global quantities, with a clear view on its significance to justify its usefulness, if any. It can also help in education with a progressive understanding of the various aspects of transformer designs.

Models of different accuracy levels are sequenced with successive additive corrections supported by different adapted meshes. The way the sources act at each correction step, up to the full models with their actual geometries, is given a particular care and generalized, allowing the proposed unified procedure. For all the considered corrections, the sources are always of IC type, thus only needed in layers of FE along boundaries, which lightens the required mesh-to-mesh projections between subproblems.

The identification of magnetic field profiles is crucial in many applications where a direct measurement is difficult. We discuss here a technique, based on the injection of charged particles in the region under examination, which promises to be an innovative and effective tool in the analysis of 1‐D field profiles in high current plasma discharges. After the decription of the inverse problem related to the field construction, we consider a suitable discrete identification scheme, and analyze some properties of the latter. The field map in the interest region is reconstructed via a minimization procedure, which identifies the coefficient of a well‐suited expansion for the field. In particular, we discuss the precision and robustness of the identification procedure, with respect to the chosen optimization scheme, the amount of data, the order in the field expansion, and the influence of noise on the data.

This study, a theoretical article, aims to introduce new institutionalism as a framework through which business and management researchers can explore the significance of artificial intelligence (AI) in organizations. Although the new institutional theory is a fully established research program, the neo-institutional literature on AI is almost non-existent. There is, therefore, a need to develop a deeper understanding of AI as both the product of institutional forces and as an institutional force in its own right.

The authors follow the top-down approach. Accordingly, the authors first briefly describe the new institutionalism, trace its historical development and introduce its fundamental concepts: institutional legitimacy, environment and isomorphism. Then, the authors use those as the basis for the queries to perform a scoping review on the institutional role of AI in organizations.

The findings reveal that a comprehensive theory on AI is largely absent from business and management literature. The new institutionalism is only one of many possible theoretical perspectives (both contextually novel and insightful) from which researchers can study AI in organizational settings.

The authors use the insights from new institutionalism to illustrate how a particular social theory can fit into the larger theoretical framework for AI in organizations. The authors also formulate four broad research questions to guide researchers interested in studying the institutional significance of AI. Finally, the authors include a section providing concrete examples of how to study AI-related institutional dynamics in business and management.