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This study aims to introduce a novel approach in form of a comprehensive software suite to help understanding and optimizing the build orientation toward maximizing the fatigue lifetime of complex geometries. The objective is to find an optimized build orientation under a given in-service loading state, which brings on smoother surfaces in stressed regions, mitigated roughness-induced stress concentration and deferred crack initiation stage. The solution addresses scenarios that no post-build surface treatment can be applied.

To account for the surface topography, the staircase induced surface roughness is registered as a function of build angle using the white light interferometry characterization, based on which the stress concentration factor (k_t) is calculated. Thereafter, the developed module in “Fatlab toolbox” is used to find the optimum build angle, considering the integrated surface orientations and stress analysis under a given loading condition.

Surface topography creates local stress concentrations upon loading, directly influencing the fatigue lifetime. It is a well-established fact that the conditions of the staircase geometry and surface roughness affect the magnitude of the stress concentration upon loading, which is influenced by the build orientation of the component. The proposed solution suggests the best build orientation that mitigates staircase-related surface roughness.

The suggested numerical approach assists the designers with positioning of the part on the build plate to minimize the build orientation-induced surface roughness and improve the as-built fatigue lifetime of the component.

This chapter argues that the primary reason for the underdeveloped state of microfoundations research in language and communications studies is methodological. It asserts that the long-standing methodological division between micro and macro analyses (traditionally small-scale and large-scale, respectively) has led to their continued theoretical separation. The paper draws from Giddens’ theory of structuration and newly developed computational methods to outline an alternative, mixed-methods framework for discourse analysis that the author calls Recursive Analysis (RA). The author demonstrates the application of the RA framework through a case study of the electric vehicle industry that aligns small-scale and large-scale textual analysis to generate theoretical insights.

Although business incubators are widely used support mechanisms for innovative entrepreneurship, the literature still lacks theoretically based explanations of how the incubation process creates value for stakeholders. This study aims to address this gap by developing a conceptual model, and related research propositions, that explains how the entrepreneurial logic in use by an incubator influences the incubation process (selection criteria and service offering) and performance.

Integrating the effectuation and entrepreneurial opportunities literature, which shares common conceptualizations about how the predictability of the future affects entrepreneurial action, the authors posit two archetypes of entrepreneurial logic that are associated with different incubation processes (causal or effectual) and two archetypes of opportunity attributes (discovery- or creation-based) that affect the incubation process needed to support their development.

Juxtaposing these archetypes, the proposed cross-level conceptual model specifies four levels of fit (ideal, surplus, deficit and mismatch) between the incubation process and the opportunity attributes of individual ventures, which directly influence venture performance (high, moderate and low). In turn, an incubator's performance is largely shaped by the overall performance of ventures in its portfolio.

This paper responds to the call for theory-building that links the antecedents and outcomes of the incubation process across levels of analysis. In addition to developing a conceptual model and research agenda at the intersection of entrepreneurship and business incubation, the proposed model also has implications for incubator directors deciding how to allocate limited resources, and for public/private sector administrators interested in leveraging investment in business incubators.

This paper reviews the synergy of Industry 4.0 and additive manufacturing (AM) and discusses the integration of data-driven manufacturing systems and product service systems as a key component of the Industry 4.0 revolution. This paper aims to highlight the potential effects of Industry 4.0 on AM via tools such as digitalisation, data transfer, tagging technology, information in Industry 4.0 and intelligent features.

In successive phases of industrialisation, there has been a rise in the use of, and dependence on, data in manufacturing. In this review of Industry 4.0 and AM, the five pillars of success that could see the Internet of Things (IoT), artificial intelligence, robotics and materials science enabling new levels of interactivity and interdependence between suppliers, producers and users are discussed. The unique effects of AM capabilities, in particular mass customisation and light-weighting, combined with the integration of data and IoT in Industry 4.0, are studied for their potential to support higher efficiencies, greater utility and more ecologically friendly production. This research also illustrates how the digitalisation of manufacturing for Industry 4.0, through the use of IoT and AM, enables new business models and production practices.

The discussion illustrates the potential of combining IoT and AM to provide an escape from the constraints and limitations of conventional mass production whilst achieving economic and ecological savings. It should also be noted that this extends to the agile design and fabrication of increasingly complex parts enabled by simulations of complex production processes and operating systems. This paper also discusses the relationship between Industry 4.0 and AM with respect to improving the quality and robustness of product outcomes, based on real-time data/feedback.

This research shows how a combined approach to research into IoT and AM can create a step change in practice that alters the production and supply paradigm, potentially reducing the ecological impact of industrial systems and product life cycle. This paper demonstrates how the integration of Industry 4.0 and AM could reshape the future of manufacturing and discusses the challenges involved.

This study investigated the relationship between last-mile distribution or delivery (LMD) and commodity access through the mediating role of commodity availability and commodity security and the moderating effect of supply chain integration (SCI).

The study adopted the survey research design and employed the questionnaire instrument in collecting primary data from respondents in Eastern Regional Health Institutions in Ghana. The total number of valid responses received was 204. The partial least squares structural equation modeling (PLS-SEM) approach was adopted to analyze the relationship between the study variables.

The findings showed that there is a positive and significant relationship between LMD and commodity availability as well as LMD and commodity security. Moreover, while the relationship between commodity availability and commodity access is positive and significant, that between commodity security and commodity access is positive but insignificant. Furthermore, there is a positive and statistically significant relationship between LMD and commodity access. The study discovered that the interaction between LMD and commodity access is insignificant and negatively affected by SCI.

To the best of the authors' knowledge, no previous studies have empirically verified the effect of LMD on commodity access in the presence of mediating factors such as commodity availability and commodity security and SCI as the moderating factors.

Gene term variation is a shortcoming in text‐mining applications based on biomedical literature‐based knowledge discovery. The purpose of this paper is to propose a technique for normalizing gene names in biomedical literature.

Under this proposal, the normalized forms can be characterized as a unique gene symbol, defined as the official symbol or normalized name. The unification method involves five stages: collection of the gene term, using the resources provided by the Entrez Gene database; encoding of gene‐naming terms in a table or binary matrix; design of a parametrized finite‐state graph (P‐FSG); automatic generation of a dictionary; and matching based on dictionary look‐up to transform the gene mentions into the corresponding unified form.

The findings show that the approach yields a high percentage of recall. Precision is only moderately high, basically due to ambiguity problems between gene‐naming terms and words and abbreviations in general English.

The major limitation of this study is that biomedical abstracts were analyzed instead of full‐text documents. The number of under‐normalization and over‐normalization errors is reduced considerably by limiting the realm of application to biomedical abstracts in a well‐defined domain.

The system can be used for practical tasks in biomedical literature mining. Normalized gene terms can be used as input to literature‐based gene clustering algorithms, for identifying hidden gene‐to‐disease, gene‐to‐gene and gene‐to‐literature relationships.

Few systems for gene term variation handling have been developed to date. The technique described performs gene name normalization by dictionary look‐up.

The recent financial crisis has restarted the debate of the value of both shareholder and stakeholder theories. This paper aims to continue this discussion.

The paper reviews existing literature and examines the benefits and problems associated with these frameworks through the lens of the recent events which have taken place during the financial crisis.

The main assertion of this paper is that shareholder theory is in itself a sound theory. Yet, some executives following this theory could have brought disrepute to it. In contrast, the stakeholder theoretical framework has yet to assert its influence because the concept is not yet unambiguously defined, which makes it difficult for the framework to become operational in practical business settings.

Future research should seek consensus on the scope and definition of the stakeholder model, as well as who the stakeholders should include. It should also focus on developing the tools and techniques necessary for the incorporation of stakeholder theory into business operations.

Policy makers could work with industry bodies and business leaders to encourage them to place greater emphasis on the interests of non‐shareholders and encourage collaboration between various groups of stakeholders to achieve corporate goals.

The paper continues the shareholder and stakeholder theory debate in light of the recent economic crisis.

Technology business incubators (TBIs) form an indispensable part of an entrepreneurial ecosystem for the promotion of tech start-ups across the global economy. However, they have evolved in varied forms over a period of time, in terms of typologies, sponsors and stakeholders, goals and objectives, functions and services offered, process of incubation support provided through hard and soft infrastructure, outcomes and achievements and even in terms of theoretical bases. The purpose of this paper, therefore, is to review the extant literature on TBIs to arrive at a framework that explains how TBIs contribute to start-up generation.

This paper reviews extant empirical literature for a systematic evaluation to throw light on the various dimensions of TBIs: typology, goals and objectives, functions and services, process and provision of incubation support, outcomes and achievements. Further, after critically reviewing some of the theoretical propositions, it develops a conceptual framework combining pre-incubation, incubation and post-incubation processes of TBIs.

Based on literature understanding and some of the key theoretical constructs, a conceptual framework is developed comprising pre-incubation, incubation and post-incubation stages of start-up formation and graduation. The paper also identifies some prospective areas for future research.

Any empirical research on technology business incubation must focus on pre-incubation and post-incubation processes as much as on the incubation process, to derive meaningful implications and enhance the productivity of TBIs.

The conceptual framework derived out of the systematic literature review will enable further research and exploration of micro-aspects of pre-incubation, incubation and post-incubation phases across multiple dimensions.

The purpose of this study is to identify the problems and possibilities for development of innovative start-ups in Latvia.

To achieve the aim of this study, a survey of Latvia’s high school students in 2015 (n = 5,910) was undertaken by an online questionnaire within a financial skill built-up contest “New Financial Expert 2016” held by the Financial Institute of Swedbank (Swedbank survey, 2016). Further, Latvia University of Agriculture master students (n = 97) were interviewed in the year 2016 to identify master students opinion about necessary support for entrepreneurship, future services or goods with potentially high added value and find out their readiness for innovative action.

A comparative analysis of data of the master student interviews and the survey of Latvia’s high school students showed that most of the youth associated their entrepreneurship prospects with innovative ideas, new technologies and new skills. The results of the research indicated that the foundation of start-up enterprises in Latvia led to positive results and gave an impulse to increasing economic activities as there were the necessary preconditions for their development.

The studies are mostly dedicated to start-ups that are less likely to innovate and have linked the concept of the start-up with business incubation. Unlike other studies, this is a specific research that provides insights into the situation in Latvia and is directed toward building innovative start-up enterprises that should be linked with the growth-oriented new technology, globalization and global market with a focus on innovation. Thus, research findings contribute to extant research on the possibilities of development of innovative start-up enterprises in Latvia and advance the present understanding of the main problems in the creation of new innovative start-ups.

Data sharing is widely thought to help research quality and efficiency. Data sharing mandates are increasingly being adopted by journals and the purpose of this paper is to assess whether they work.

This study examines two evolutionary biology journals, Evolution and Heredity, that have data sharing mandates and make extensive use of Dryad. It uses a quantitative analysis of presence in Dryad, downloads and citations.

Within both journals, data sharing seems to be complete, showing that the mandates work on a technical level. Low correlations (0.15-0.18) between data downloads and article citation counts for articles published in 2012 within these journals indicate a weak relationship between data sharing and research impact. An average of 40-55 data downloads per article after a few years suggests that some use is found for shared life sciences data.

The value of shared data uses is unclear.

Data sharing mandates should be encouraged as an effective strategy.

This is the first analysis of the effectiveness of data sharing mandates.