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This study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.

The authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.

The results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.

The findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.

Destinations have in the scholarly literature been labeled as communities of interdependent organizations that collectively coproduce a variety of products and services. The paradigm comes close to describing destinations as firms which are embedded in interfirm networks. Recent studies provide crucial insights into an understanding of destinations' orchestration and structuration as coproducing interfirm networks. However, systematic knowledge about how these systems evolve and develop is lacking. This chapter addresses this issue and elaborates how the concepts of scale-free and small-world networks together can explain the process of destination evolution. The discussion also suggests how such theorizing can spur avenues for future research.

The importance of Carbon dioxide (CO₂) gas detection as a greenhouse and exhale breathe gas is an undeniable issue. This study aims to propose a new miniaturized, low cost and portable no dispersive infrared (NDIR) system for detecting CO₂ gas.

Poly(methyl methacrylate) (PMMA)-based channels with Au coating because of its high reflection properties in IR region were used in this work. The optical windows were fabricated using PDMS polymer which is cost effective and novel in comparison to other conventional methods. The effects of channel dimensions, lengths and entrance angle of light on optical path length and losses were analyzed with four types of channel using both simulation and experimental tests.

The simulation results indicate that the 0 degree light entrance angle is the most efficient angle among different investigated conditions. The experimental data are in agreement with the simulation results regarding the loss and optical path length in different types of channel. The experimental tests were performed for the 0.5% up to 20% of CO₂ concentration under constant temperature and humidity condition. The results show that the device with 5  and 2 cm channels length were saturated in 4% and 8% concentration of CO₂ gas, respectively. Response and recovery times were depending on gas concentration and channels specifications that in average found to be 10 S and 14 S, respectively, for the largest size channel. Moreover, the environment humidity effect on detection system performance was investigated which had no considerable influence. Also, the saturation fraction absorbance value for devices with various dimensions were 0.62 and 0.8, respectively.

According to the performed curve fitting for practical situation and selected CO₂ concentration range for experimental tests, the device is useful for medical and environmental applications.

PMMA with Au deposition layer was used as a basic material for this NDIR system. Besides, a novel PDMS optical window helps to have a low cost device. The effects of channel dimensions, lengths and entrance angle of light on optical path length and losses were analyzed using both simulation and experimental tests. Using narrowband optical filter (100 nm bandwidth) helps to have a system with good CO₂ selectivity. In addition, experimental tests with different channel dimensions and lengths covered a considerable range of CO₂ concentration useful for medical and environmental applications. Finally, curve fitting was adopted for a modified Beer–Lambert law as a practical situation.

The research on social media-based academic communication has made great progress with the development of the mobile Internet era, and while a large number of research results have emerged, clarifying the topology of the knowledge label network (KLN) in this field and showing the development of its knowledge labels and related concepts is one of the issues that must be faced. This study aims to discuss the aforementioned issue.

From a bibliometric perspective, 5,217 research papers in this field from CNKI from 2011 to 2021 are selected, and the title and abstract of each paper are subjected to subword processing and topic model analysis, and the extended labels are obtained by taking the merged set with the original keywords, so as to construct a conceptually expanded KLN. At the same time, appropriate time window slicing is performed to observe the temporal evolution of the network topology. Specifically, the basic network topological parameters and the complex modal structure are analyzed empirically to explore the evolution pattern and inner mechanism of the KLN in this domain. In addition, the ARIMA time series prediction model is used to further predict and compare the changing trend of network structure among different disciplines, so as to compare the differences among different disciplines.

The results show that the degree sequence distribution of the KLN is power-law distributed during the growth process, and it performs better in the mature stage of network development, and the network shows more stable scale-free characteristics. At the same time, the network has the characteristics of “short path and high clustering” throughout the time series, which is a typical small-world network. The KLN consists of a small number of hub nodes occupying the core position of the network, while a large number of label nodes are distributed at the periphery of the network and formed around these hub nodes, and its knowledge expansion pattern has a certain retrospective nature. More knowledge label nodes expand from the center to the periphery and have a gradual and stable trend. In addition, there are certain differences between different disciplines, and the research direction or topic of library and information science (LIS) is more refined and deeper than that of journalism and media and computer science. The LIS discipline has shown better development momentum in this field.

KLN is constructed by using extended labels and empirically analyzed by using network frontier conceptual motifs, which reflects the innovation of the study to a certain extent. In future research, the influence of larger-scale network motifs on the structural features and evolutionary mechanisms of KLNs will be further explored.

In this chapter we investigate the ownership and control of UK firms using contemporary methods from computational graph theory. Specifically, we analyze a ‘small-world’ model of ownership and control. A small-world is a network whose actors are linked by a short chain of acquaintances (short path lengths), but at the same time have a strongly overlapping circle of friends (high clustering). We simulate a set of corporate worlds using an ensemble of random graphs introduced by Chung and Lu (2002a, 2002b). We find that the corporate governance network structures analyzed here are more clustered (‘clubby’) than would be predicted by the random-graph model. Path lengths, though, are generally not shorter than expected. In addition, we investigate the role of financial institutions: potentially important conduits creating connectivity in corporate networks. We find such institutions give rise to systematically different network topologies.

Nodes in sensor networks do not have enough topology information to make efficient routing decisions. To relay messages through intermediate sensors, geographic routing has been proposed as such a solution. Its greedy nature, however, makes routing inefficient especially in the presence of topology voids or holes. In this paper we present GRAViTy (Geographic Routing Around Voids In any TopologY of sensor networks), a simple greedy forwarding algorithm that combines compass routing along with a mechanism that allows packets to explore the area around voids and bypass them without significant communication overhead. Using extended simulation results we show that our mechanism outperforms the right‐hand rule for bypassing voids and that the resulting paths found well approximate the corresponding shortest paths. GRAViTy uses a cross‐layered approach to improve routing paths for subsequent packets based on experience gained by former routing decisions. Furthermore, our protocol responds to topology changes, i.e. failure of nodes, and efficiently adjusts routing paths towards the destination.

There are many complex networks like World-Wide Web, internet and social networks have been reported to be scale-free. The major property of scale-free networks is their degree distributions are in power law form. Generally, the degree exponents of scale-free networks fall into the range of (2, 3). The purpose of this paper is to investigate other situations where the degree exponents may lie outside the range.

In this paper, analysis has been carried out by varying the degree exponents in the range of (0.5, 4.5). In total, 243 scenarios have been generated with varying network size of 1,000, 2,000 and 4,000, and degree exponents in the range of (0.5, 4.5) using interval of 0.05.

The following five indicators have been investigated: average density, average clustering coefficient, average path length, average diameter and average node degree. These indicators vary with the network size and degree exponent. If certain indicators do not satisfy with the user requirement using degree exponents of (2, 3), one can further increase or decrease the value with tradeoff. Results recommend that for degree exponents in (0.5, 2), 26 possible scale-free networks can be selected whereas for (3, 4.5), 41 possible scale-free networks can be selected, assuming a 100 percent deviation on the network parameters.

A tolerance analysis is given for the tradeoff and guideline is drawn to help better design of scale-free network for degree exponents in range of (0.5, 2) and (3, 4.5) using network size 1,000, 2,000 and 4,000. The methodology is applicable to any network size.

The objective of this research is to systematically compare two methods of wicking test for evaluating the quality of the non-medical-mask fabric, i.e. its absorbency property at various conditions, using a design of experiment approach. This research also evaluates the suitability of several fabrics to be used for non-medical masks.

Horizontal and vertical wicking tests were selected to evaluate the absorbency property of five fabrics commonly used for the non-medical mask. The tests were performed at three temperatures and using two types of liquid. The design of experiment approach was employed to determine the relationship between the path length of liquid movement in fabric and type of test method, temperature and type of liquid.

Both vertical and horizontal wicking tests show the same order of fabrics according to their absorbency. The order is cotton twill, local cotton, Japanese cotton, Oxford and Scuba, where the first in the order has the lowest absorbency and the last has the highest absorbency. Based on the analysis of variance (ANOVA), the range of temperature and types of liquid employed in this research do not affect the path length of the liquid movement in the fabric.

This research proposes horizontal and vertical wicking tests as a practical tool to evaluate absorbency property of fabric for the non-medical mask. This research also presents a design of experiment approach to evaluate the effect of the test method, temperature and type of liquid on the path length of the liquid movement in the fabric.

The purpose of this paper is to improve the traditional bug algorithms for the navigation of mobile robots in unknown environments by considering the limitations in previous works such as generating long path, limited to static environments as well as ignoring implementation issues. With this purpose, a new bug‐type algorithm termed Distance Histogram Bug (DH‐Bug) is proposed for overcoming these limitations.

DH‐Bug redefines the traditional motion modes and switching criteria to shorten the path length. In order to extend the framework of the traditional bug algorithms to tackle the navigation problem in dynamic environments, a new mode and the related switching conditions are designed for dealing with moving obstacles. Moreover, a realization method termed the Distance Histogram (DH) method which takes many implementation issues into full account is proposed for implementing DH‐Bug on real robots.

DH‐Bug is convergent in static environments and it also guarantees “approximate” convergence based on several reasonable assumptions when there are moving obstacles. Simulations results show that DH‐Bug generates shorter average path length than some classical Bug algorithms in static environments and it also performs well in most simulations that contain moving obstacles except for some extremely adverse scenarios which have been discussed in the paper. Experiments on real robots further verify its applicability in both static environments and dynamic environments containing moving obstacles.

Compared with previous works, DH‐Bug has three main contributions. First, in static environments, it can shorten the average path length than many classical bug algorithms in the premise of guaranteeing convergence. Second, it can be applied in dynamic environments containing moving obstacles. Third, unlike the previous bug algorithms that always ignore the practical implementation issues, DH‐Bug presents not only an abstract concept, but also a realization approach for realizing this concept on real robots.

Many networks take a small-world structure, with a high degree of clustering and shortcut ties that reduce the path-length between the clusters. It can be argued that small-world networks have benefits that are simultaneously related to network closures and the spanning of structural holes, but research on the network members’ performance is nonetheless inconclusive. The purpose of this paper is to argue that the concept of resource idiosyncrasy can explain the mixed findings. Firm idiosyncratic resources are not easily generalizable across enterprises.

Industries may vary in terms of resource idiosyncrasy, and the paper elaborates how this can moderate shortcut ties’ effect on performance in an inter-firm network.

If resource idiosyncrasy predominates in an industry, the paper proposes that inter-firm shortcut ties may increase performance, whereas shortcut ties may decrease performance if non-idiosyncratic resources predominate.

Applying the concept of resource idiosyncrasy as a moderating variable, the paper aims to explain shortcut ties’ effect on performance in an inter-firm network. The theory advanced here can have practical implications and also motivate future empirical studies to gain further knowledge about small-world networks’ effect on performance.