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This paper aims to present a method of color three-dimensional (3D) printing based on color adherence.

First, experiments of the color effects of 3D printings using different carriers and different printing methods were performed. Second, the color of a specific point could be calculated through a theory of dimension-reducing, and the color distribution of 3D model was transformed from 3D to 1D color line corresponding with 3D print sequence. At last, the color lines, which were printed on a PE film by silk-screen printing, was carried by a filament and then printed through a fused deposition modeling 3D printer.

The printing ink and PE film are suitable as the pigment and carrier under this investigation, respectively. Based on an idea of reducing dimension, the method of 3D color printing through adhering color to a filament is realized. The color saturation of the sample was relatively high through the method.

It is hard to avoid that there may be some residual color in the nozzle through this method, and the purity of following color will be affected. As a result, continuous improvements should be made to perfect the method.

An approach of 3D color printing is described in detail, and what kind of model is more applicable is discussed particularly.

This approach is implemented to print color 3D objects with just one nozzle by means of color adherence. That is, printing the 3D objects using the filament is carried out with 1D color line, which is printed by a traditional printing method.

The aim of this article is to investigate how the use of financial instruments influences the development of Regional Development Funds (RFR) in Poland and to assess the maturity and coherence of the regional development financing system in this country.

The methodology is based on the multilevel governance literature and on data collected during 26 in-depth interviews in regional, national and international institutions.

The authors demonstrate that the use of financial instruments stimulates new kinds of cooperation between several institutions and contributes to the establishment of RFR. The authors also show that the Polish regional financing system is still developing and formulate recommendations about necessary improvements.

The main contribution of this article, in addition to taking up a new, relevant topic for the regional development policy in countries benefiting from European Union (EU) cohesion policy, is the application of the multilevel governance (MLG) concept to explain the development of the Polish regional development financing system. Moreover, the significant added value of this study comes from the use of data collected during 26 in-depth interviews (IDI) in regional, national and international institutions on the use of repayable instruments in regional development policy.

As companies grow and evolve, they inevitably face an influx of new personnel and changing responsibilities of existing staff members, often resulting in an increasingly complex organizational design. During periods of rapid organic growth, new layers of management and labor may be created as a reactionary, rather than a planned activity. This often results in redundancy of responsibility and confusing communication channels within the company, ultimately impacting financial performance. The purpose of this paper is to describe a case study of significant organizational change that was accomplished using assessment center philosophy, combined with web‐based technology.

Concurrent Technologies Corporation (CTC), a research and development professional services organization that rapidly grew its workforce to over 1,400 was faced with these challenges, resulting in direct labor billings losses. Upon strategically designing a new organizational structure, CTC was faced with making critically important staffing changes. A modified assessment center approach using web‐based technology was employed to rapidly select the best candidates for these new positions.

It is the authors' contention in this paper and practice in the implementation of this organizational realignment that practicing managers who have extensive experience with middle managers can effectively evaluate them on assessment center dimensions without observing them in assessment center simulations. These enlightened assessments leveraged web‐based technology, while avoiding the costly and time‐intensive simulation and exercise phases of the traditional assessment center.

Based on the authors' experience with CTC, combining this modified assessment center approach (evaluating managers on competencies without using simulations and exercises) with web‐based technology can provide organizations with a powerful tool for implementing fast and effective organizational change. This new and original approach can support executives in evaluating managerial talent and realigning organizational structure.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

The results indicate that a firm's market globalization orientation influences the deployment of specific organizational practices and capabilities. The effective implementation of these practices impacts firm outcomes.

The briefing saves busy executives, strategists, and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Content‐based image retrieval (CBIR) is an important research area for automatically retrieving images of user interest from a large database. Due to many potential applications, facial image retrieval has received much attention in recent years. Similar to face recognition, finding appropriate image representation is a vital step for a successful facial image retrieval system. Recently, many efficient image feature descriptors have been proposed and some of them have been applied to face recognition. It is valuable to have comparative studies of different feature descriptors in facial image retrieval. And more importantly, how to fuse multiple features is a significant task which can have a substantial impact on the overall performance of the CBIR system. The purpose of this paper is to propose an efficient face image retrieval strategy.

In this paper, three different feature description methods have been investigated for facial image retrieval, including local binary pattern, curvelet transform and pyramid histogram of oriented gradient. The problem of large dimensionalities of the extracted features is addressed by employing a manifold learning method called spectral regression. A decision level fusion scheme fuzzy aggregation is applied by combining the distance metrics from the respective dimension reduced feature spaces.

Empirical evaluations on several face databases illustrate that dimension reduced features are more efficient for facial retrieval and the fuzzy aggregation fusion scheme can offer much enhanced performance. A 98 per cent rank 1 retrieval accuracy was obtained for the AR faces and 91 per cent for the FERET faces, showing that the method is robust against different variations like pose and occlusion.

The proposed method for facial image retrieval has a promising potential of designing a real‐world system for many applications, particularly in forensics and biometrics.

This paper explores the orchestration of digital innovation in Industry 4.0 organisations.

The study applies the activity theory to explorative multiple case studies. Observations of innovation activities in five business cases take place at two large international organisations.

The results underline five logics of action that drive digital innovation: (1) digital transformation, (2) technology translation, (3) catalyst agents, (4) digital thread and (5) empowerment. Further, the case study organisations highlight the importance of developing a sustainable culture capable of continuously adopting new technologies, processes and infrastructure that will allow the management of digital innovations.

The study empirically shows the motivations and challenges in orchestrating digital innovation in Industry 4.0 organisations.

The aim of this paper is to empirically investigate whether social contacts can mediate the way in which current unemployment impacts future unemployment.

We use 2006–2017 data from the Household Income and Labour Dynamics in Australia (HILDA) survey and a dynamic random-effects model to describe the evolution of individual unemployment status over time.

Once controlled for the local context where individuals live and create friendships, we find that above-average social contacts reduce unemployment persistence. However, social contacts seem to be slightly less effective in deprived neighborhoods. These findings are consistent with the idea that individuals obtain information about job opportunities through a network of social contacts, and unemployment may lead to a decay of social capital, making it more difficult to find employment in future periods. Our results also show that neighborhood deprivation increases individual unemployment risk, while above-average neighborhood cohesion reduces the probability of unemployment in deprived neighborhoods.

Although many studies have been published on unemployment persistence, to the best of the author's knowledge, this is the first study quantifying the impact of social contacts on unemployment persistence. The study also offers fresh empirical evidence on the impact of neighborhood characteristics on unemployment risk.

Generational theory research suggests that the arrival of the Millennial generation into adulthood will have significant effects on society because of their differing values and attitudes. We examine whether this generation has differing perceptions of tax fairness as well as their attitudes towards tax compliance as compared to other generations by administering an instrument to a sample of 303 taxpayers, distributed approximately equally across three generational groups: Baby Boomers, Generation X, and Millennials. The results suggest that there are significant differences in the viewpoints toward vertical equity and progressive taxation among the three generations. More specifically, the Millennial generation was less likely to recommend progressive taxation than the other two generations. In addition, there were significant differences between the groups on an exchange equity question as well. However, in this situation, it was the Baby Boomers that were significantly different from the other two generations. The results also suggest that the Millennials have attitudes that are more accepting of noncompliance than both the Generation X participants and the Baby Boomer participants. However, a significant difference does not exist between the Baby Boomer participants and Generation X participants on their attitudes towards compliance.

We study the informational content of factor structures in discrete triangular systems. Factor structures have been employed in a variety of settings in cross-sectional and panel data models, and in this chapter we formally quantify their identifying power in a bivariate system often employed in the treatment effects literature. Our main findings are that imposing a factor structure yields point-identification of parameters of interest, such as the coefficient associated with the endogenous regressor in the outcome equation, under weaker assumptions than usually required in these models. In particular, we show that a “non-standard” exclusion restriction that requires an explanatory variable in the outcome equation to be excluded from the treatment equation is no longer necessary for identification, even in cases where all of the regressors from the outcome equation are discrete. We also establish identification of the coefficient of the endogenous regressor in models with more general factor structures, in situations where one has access to at least two continuous measurements of the common factor.