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The Hurst exponent has been very important in telling the difference between fractal signals and explaining their significance. For estimators of the Hurst exponent, accuracy and efficiency are two inevitable considerations. The main purpose of this study is to raise the execution efficiency of the existing estimators, especially the fast maximum likelihood estimator (MLE), which has optimal accuracy.

A two-stage procedure combining a quicker method and a more accurate one to estimate the Hurst exponent from a large to small range will be developed. For the best possible accuracy, the data-induction method is currently ideal for the first-stage estimator and the fast MLE is the best candidate for the second-stage estimator.

For signals modeled as discrete-time fractional Gaussian noise, the proposed two-stage estimator can save up to 41.18 per cent the computational time of the fast MLE while remaining almost as accurate as the fast MLE, and even for signals modeled as discrete-time fractional Brownian motion, it can also save about 35.29 per cent except for smaller data sizes.

The proposed two-stage estimation procedure is a novel idea. It can be expected that other fields of parameter estimation can apply the concept of the two-stage estimation procedure to raise computational performance while remaining almost as accurate as the more accurate of two estimators.

Gender swapping – when gamers choose avatars of the opposite gender to their own – is a common feature of online gaming behavior, and recent studies have explored the reasons for it. However, no study has yet examined the role gender swapping plays in determining gamers’ continual engagement with communication via online games, i.e., online gamer loyalty. Therefore, the purpose of this paper is to examine this issue and develop hypotheses based on interdependence theory in the online gaming context.

Responses from a survey of 255 online gamers were used for the analysis.

Analytical results using structural equation modeling indicate that gender-swapping behavior is negatively related to social intelligence, which in turn is negatively related to network convergence (the extent of sharing a common social circle), thus contributing to relational switching costs and online gamer loyalty.

This study is the first to examine how gender swapping affects online gamer loyalty.

By the end of this session, students should be able to: explain what a business model is; summarize the case firm’s business strategy using the elements of business model canvas proposed by Alexander Osterwalder and practice how to apply the business model canvas to analyze the business model of a firm; understand how a firm can seize an opportunity for innovation; and discuss how the case firm navigated through problems that came up as it grew.

Creative Design was a start-up company in Taiwan. To fulfill a course requirement while she was still in school, the founder had formed a team and entered an entrepreneurship competition. They won the second runner up award in that competition and impressed some firms who enquired if they would be interested in doing corporate identity system (CIS) design. They discovered that without establishing a corporate structure their prospective clients would be unable to pay an invoice. As a consequence, the founder and one of the team members established Creative Design Ltd. This case discusses the challenge Creative Design faced at the end of 2012. Wonderland farmers’ association (WFA) wanted to market locally grown jasmine but did not know how to go about it. They reached out to the founder and her company for assistance. The case of WFA was uncharted territory. Creative Design already had extensive experience in CIS design, but it did not have any experience in handling agriculture products. In this case, they had to deal with the full supply chain from production to exhibition. The risk for this project was high but Creative Design accepted the case and became the first design firm offering a “total solution.” Currently, Creative Design works with all kinds of cases, from simple CIS designs to more complicated total solutions of various scales. The founder now has to contemplate if the design house should develop more total solution cases. Doing so would require recruiting more staff and the dilemma of balancing revenue and costs.

The case study is designed for the undergraduate and graduate students of the College of Management; the case can be adopted for the courses of management, innovation and entrepreneurship, etc.

Teaching Notes are available for educators only.

CSS: 3 Entrepreneurship.

This paper aims to investigate emerging trends in data analytics and knowledge management (KM) job market by using the knowledge, skills and abilities (KSA) framework. The findings from the study provide insights into curriculum development and academic program design.

This study traced and retrieved job ads on LinkedIn to understand how data analytics and KM interplay in terms of job functions, knowledge, skills and abilities required for jobs, as well as career progression. Conducting content analysis using text analytics and multiple correspondence analysis, this paper extends the framework of KSA proposed by Cegielski and Jones‐Farmer to the field of data analytics and KM.

Using content analysis, the study analyzes the requisite KSA that connect analytics to KM from the job demand perspective. While Kruskal–Wallis tests assist in examining the relationships between different types of KSA and company’s characteristics, multiple correspondence analysis (MCA) aids in reducing dimensions and representing the KSA data points in two-dimensional space to identify potential associations between levels of categorical variables. The results from the Kruskal–Wallis tests indicate a significant relationship between job experience levels and KSA. The MCA diagrams illustrate key distinctions between hard and soft skills in data across different experience levels.

The practical implications of the study are two-fold. First, the extended KSA framework can guide KM professionals with their career planning toward data analytics. Second, the findings can inform academic institutions with regard to broadening and refining their data analytics or KM curricula.

This paper is one of the first studies to investigate the connection between data analytics and KM from the job demand perspective. It contributes to the ongoing discussion and provides insights into curriculum development and academic program design.

The purpose of this paper is to use personal fuzzy demand, assisted by system computing to find a job, using job search systems to achieve this goal.

The search system uses the fuzzy goal programming (FGP) method by setting personal preferences as property values and screening the data for comparison and calculation. By presenting information sorted by the inputted property values, the methodology suggests the best job options.

FGP algorithms make job-searching systems meet the needs of users better, which can really affect jobseekers’ approaches to pursuing work.

As it has only considered the local cultural environment, this paper’s findings are limited by being confined to Taiwanese samples.

The experimental results of the proposed method have been compared with other websites to show their effectiveness.

This paper has assisted personal decision making using FGP applied to the internet which has seldom been studied previously.

The development of urban underground complexes (UUCs) has great positive significance for improving urban safety. Therefore, it is necessary to identify the key factors of the people's behavior of evacuation route selection (BERS) for fire emergencies and UUCs’ development. This study aims to find out the factors affecting people's BERS in the evacuation process of UUCs.

This study aims to find out the factors affecting people's BERS in the evacuation process of UUCs. To achieve this goal, the authors conducted a field experiment in F City. Furthermore, the people's BERS are obtained by using a structural equation model and compared with the field test results.

The authors found that the key factors for people's BERS are lighting conditions, route distance, flow direction guidance and indication. The results of this study contribute to the safety field by providing key factors for fire emergencies. It can also be used to improve fire safety management, evacuation strategies and assist in the development of intelligent evacuation systems.

The results of this study contribute to the safety field by providing key factors for fire emergencies. It can also be used to improve fire safety management, evacuation strategies and assist in the development of intelligent evacuation systems.

The purpose of this paper is to investigate the effects of dipentaerythritol hexaacrylate (DPHA) and 3-(trimethoxysilyl)propyl methacrylate-modified silica nanoparticles (MSiO₂) contents on the performances of the Disperse Red 1 (DR1)-grafted-silica/poly(acrylate) color hard coatings.

The organic dye DR1 was silylated by reaction with the coupling agent 3-isocyanatopropyltriethoxysilane in methyl ethyl ketone. The silylated-DR1 thus obtained was grafted on MSiO₂ to form dye-grafted silica (GSiO₂). This hybrid dye was then UV-cured with the cross-linking agent, DPHA, to yield color coatings. Thermal durability of the coatings was evaluated based on their CIE (international commission on illumination) chromaticity coordinates and UV/Vis transmittances.

The results indicated that GSiO₂-coatings could tolerate thermal attack better than pristine DR1-coatings or dye-absorbed silica (DSiO₂)-coatings because of the fact that DR1 was more finely dispersed in the polymer binder when covalently bonded to the silica particles. Under optimal conditions, coatings with very small change of saturation and hue after high-temperature treatments were obtainable. These coatings appeared transparent, had 3H-6H pencil hardness and adhered perfectly onto the poly(methyl methacrylate) substrates.

Dye-grafted color coatings may find applications such as color filter photoresists for displays, microelectronics, printed circuit boards, etc.

The performances of the coatings were evaluated in terms of mechanical strength, adherence to the substrate, transmittance and color stability against heat treatments, which have not been disclosed. Also, using a newly developed triangular composition diagram, suitable ranges for preparing useful color coatings were accessed. The present method deserves further research studies on green and blue dyes.

The purpose of this paper is to investigate dynamics of causal interactions and financial risk contagion among BRICS stock markets under rare events.

Two methods are adopted: The new causal inference technique, namely, the Liang causality analysis based on information flow theory and the dynamic causal index (DCI) are used to measure the financial risk contagion.

The causal relationships among the BRICS stock markets estimated by the Liang causality analysis are significantly stronger in the mid-periods of rare events than in the pre- and post-periods. Moreover, different rare events have heterogeneous effects on the causal relationships. Notably, under rare events, there is almost no significant Liang's causality between the Chinese and other four stock markets, except for a few moments, indicating that the former can provide a relatively safe haven within the BRICS. According to the DCIs, the causal linkages have significantly increased during rare events, implying that their connectivity becomes stronger under extreme conditions.

The obtained results not only provide important implications for investors to reasonably allocate regional financial assets, but also yield some suggestions for policymakers and financial regulators in effective supervision, especially in extreme environments.

This paper uses the Liang causality analysis to construct the causal networks among BRICS stock indices and characterize their causal linkages. Furthermore, the DCI derived from the causal networks is applied to measure the financial risk contagion of the BRICS countries under three rare events.

The tremendous market growth of mobile platforms for esports underscores the need to understand players' psychological states and consumption behavior. Based on flow theory, this study examines players' psychological states (flow and clutch experiences) and consumption behavior based on the interaction effects of playing frequency, playing duration and players' levels on the PC (LOL – League of Legends) and mobile (LOLWR – League of Legends: Wild Rift) versions of the same esports title.

Data were collected from 930 valid responses and analyzed with confirmatory factor analysis and multiple regression (PROCESS macro, Model 3).

There are two main findings. First, across PC and mobile participants, casual gamers (low playing frequency and duration) have firm purchase intention when they have a clutch experience, but flow experience hinders their purchasing intention. Second, hardcore gamers' (high playing frequency and duration) psychological states are clearly distinguished according to technological platforms. Flow experience is the most effective for their purchase intention in the PC platform, but both flow and clutch states are important in the mobile platform. Flow experience is essential overall for hardcore gamers to intend their in-game item purchasing.

This study has two primary originality/values. First, this study explores flow and clutch together to measure psychological states and the impact on the purchase intention of in-game items. Second, the interacting effects of playing frequency, duration, and skill level with technical platforms (i.e. PC and mobile) for esports gaming.

The purpose of this paper is to investigate alliance partner diversity (APD) as a driving force that potentially enhances firms’ innovation generation (IG) in interfirm open alliance contexts. The authors propose that APD enhances IG but that the effects depend on both alliance network position and the double-edged external knowledge search strategy. Building on the knowledge-based view and social capital theory, the authors formally model how external knowledge search strategies can lead to productive or destructive acquisitions of external knowledge in interfirm open alliance networks. The authors theorize that when an individual firm adopts a central position in a complex interfirm open alliance network, its propensity toward beneficial IG depends on its knowledge search strategy (i.e. its breadth and depth) due to the joint influence of network position and knowledge search strategy on innovation.

Using an original large-scale survey of high-tech firms, this study shows that the relationship between partner diversity and IG is contingent on a firm’s network position and knowledge search strategy. The authors also offer an original analysis of how knowledge search strategy (i.e. its breadth and depth) in network centrality (NC) affects the efficacy of knowledge acquisition in interfirm open alliance networks. Empirically, the authors provide an original contribution to the open innovation literature by integrating social capital and knowledge-based theory to rigorously measure firm IG.

Overall, our findings suggest that the knowledge search strategy imparts a double-edged effect that may promote or interfere with external knowledge in IG in the context of the diversity of alliance partners.

The work has important limitations, such as its analysis of a single industry in the empirical models. Therefore, further studies should consider multiple industries that may provide useful insights into innovation decisions.

External knowledge search is valuable, particularly in the high-tech industry, as external knowledge acquisition generates innovation output. This study serves to raise managers’ awareness of various approaches to external knowledge searches and highlights the importance of network position in knowledge acquisition from interfirm open alliance collaborations.

This paper is the first to investigate the double-edged effect of knowledge search on interfirm open alliance networks. It also contributes to the theoretical and practical literature on interfirm open alliance networks by reflecting on external knowledge search and underlying network centrality and APD factors.