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Although service research typically asserts that institutions coordinate actors’ value creation processes, institutions and resources are not necessarily transparent, aligned, or pre-existing. This paper aims to develop a more granular perspective on how actors coordinate for value.

Drawing on the established concepts of signaling and screening theory, this paper adopts a service marketing perspective to explore how independent heterogeneous actors coordinate for value creation at the individual level. Illustrative cases of corporate startup collaborations are presented in support of the proposed conceptual framework.

Actors share and acquire information through signaling and screening activities in a coordinative dialogue with other actors. These resource integration activities (for resource creation and matching) affect actors’ valuations and future actions.

The one-sided explanations of coordination in the existing literature reflect the dominance of the institutional theory. By contrast, the proposed agency-oriented perspective based on the integration of signaling and screening functions offers a more granular conceptualization of the resource integration process. As well as capturing how actors use coordinating dialogue to match resources and institutions, this account also shows that matching is a core element of resource integration rather than an antecedent. The findings indicate paths for future research that focus on the actor.

The authors investigate whether matchings in equity crowdfunding are more likely to happen if homophily exists between investors and investees. They focus on gender, age and geographical proximity as crucial dimensions of similarity among individuals and thus of homophily. Furthermore, they investigate whether the effect of homophily depends on the risk of opportunism, which investors allegedly attribute to proponents basing on their area of residence.

The authors analyze a hand-collected database of 13 equity crowdfunding campaigns launched by Italian innovative start-ups from January 2013 to June 2016, which includes information about 384 equity crowdfunding investments carried out by 361 different investors.

The authors find a significant effect of geographical proximity and age similarity in explaining the probability that an investor finances a campaign. Moreover, these effects are particularly relevant if the proponent is located in areas characterized by a high risk of opportunistic behavior. Interestingly enough, they do not detect any significant effect related to gender.

In this paper, the authors have the unique opportunity to analyze a whole market (the Italian market) during three years, from inception (2013–2016), and to collect the identities of the investors in all successful campaigns.

The purpose of the work is to provide a comprehensive review of the digital image correlation (DIC) technique for those who are interested in performing the DIC technique in the area of manufacturing.

No methodology was used because the paper is a review article.

no fundings.

Herein, the historical development, main strengths and measurement setup of DIC are introduced. Subsequently, the basic principles of the DIC technique are outlined in detail. The analysis of measurement accuracy associated with experimental factors and correlation algorithms is discussed and some useful recommendations for reducing measurement errors are also offered. Then, the utilization of DIC in different manufacturing fields (e.g. cutting, welding, forming and additive manufacturing) is summarized. Finally, the current challenges and prospects of DIC in intelligent manufacturing are discussed.

This study aims to develop an experimentally validated three-dimensional numerical model for predicting different flow patterns produced with a gas dynamic virtual nozzle (GDVN).

The physical model is posed in the mixture formulation and copes with the unsteady, incompressible, isothermal, Newtonian, low turbulent two-phase flow. The computational fluid dynamics numerical solution is based on the half-space finite volume discretisation. The geo-reconstruct volume-of-fluid scheme tracks the interphase boundary between the gas and the liquid. To ensure numerical stability in the transition regime and adequately account for turbulent behaviour, the k-ω shear stress transport turbulence model is used. The model is validated by comparison with the experimental measurements on a vertical, downward-positioned GDVN configuration. Three different combinations of air and water volumetric flow rates have been solved numerically in the range of Reynolds numbers for airflow 1,009–2,596 and water 61–133, respectively, at Weber numbers 1.2–6.2.

The half-space symmetry allows the numerical reconstruction of the dripping, jetting and indication of the whipping mode. The kinetic energy transfer from the gas to the liquid is analysed, and locations with locally increased gas kinetic energy are observed. The calculated jet shapes reasonably well match the experimentally obtained high-speed camera videos.

The model is used for the virtual studies of new GDVN nozzle designs and optimisation of their operation.

To the best of the authors’ knowledge, the developed model numerically reconstructs all three GDVN flow regimes for the first time.

This study aims to investigate whether and how strongly cultural (mis)matches influence immigrant customers’ satisfaction, as well as if this relationship is mediated by cultural or service employee performance attributions. In addition, the authors test whether attributions differ depending on the service delivery outcome (success vs failure).

The 2 (origin of service employee: Austria or Turkey) × 2 (service delivery outcome: success or failure) scenario-based experiment includes 120 Turkish immigrant customers in Austria.

Contrary to previous research, the results indicate that in an immigrant customer context, cultural (mis)match does not influence customer satisfaction. The service delivery outcome is a boundary condition. With a positive service delivery outcome, immigrant customers attribute the results to the cultural background of the employee if it is the same as their own, but they attribute success to employees’ performance if they belong to the immigration destination culture. For negative service delivery outcomes, neither cultural nor performance attributions arise.

This study is the first to focus specifically on immigrant customer behavior in a high-involvement service context. The results challenge the predictions of social identity theory and the similarity-attraction paradigm and highlight that the immigrant context is unique. In this context, attributions play a key role in determining customer satisfaction.

The purpose is to develop search and detection strategies that maximize the probability of detection of mine-like objects.

The author have developed a methodology that incorporates variational calculus, number theory and algebra to derive a globally optimal strategy that maximizes the expected probability of detection.

The author found a set of look angles that globally maximize the probability of detection for a general class of mirror symmetric targets.

The optimal strategies only maximize the probability of detection and not the probability of identification.

In the context of a search and detection operation, there is only a limited time to find the target before life is lost; hence, improving the chance of detection will in real terms be translated into the difference between success or failure, life or death. This rich field of study can be applied to mine countermeasure operations to make sure that the areas of operations are free of mines so that naval operations can be conducted safely.

There are two novel elements in this paper. First, the author determine the set of globally optimal look angles that maximize the probability of detection. Second, the author introduce the phenomenon of concordance between sensor images.

This paper estimates and forecasts yield curve of korea bond market using a three factor term structure model based on the Nelson-Siegel model. The Nelson-Siegel model is in-terpreted as a model of level, slope and curvature and has the flexibility required to match the changing shape of the yield curve. To estimate this model, we use the two-step estima-tion procedure as in Diebold and Li. Estimation results show our model is Quite flexible and gives a very good fit to data.

To see the forecasting ability of our model, we compare the RMSEs (root mean square error) of our model to random walk (RW) model and principal component model for out-of sample period as well as in-sample period. we find that our model has better forecasting performances over principal component model but shows slight edge over RW model especially for long run forecasting period. Considering that it is difficult for any model to show better forecasting ability over the RW model in out-of-sample period, results suggest that our model is useful for practitioners to forecast yields curve dynamics.