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The purpose of this article is to explore the impact of the firm's entrepreneurship for the transformation of circular economy (CE). The role of entrepreneurship is thought to be important for the process of four Rs in the CE, and the authors have tried to study the role and impact path of entrepreneurship in CE.

Empirical data from Chinese listed firms are collected, and a measure of digital technology is constructed by text mining method. Mediation analysis method is used to test the proposed hypothesis.

The results show that the innovation entrepreneurship has a significant positive impact upon the CE and digital technology is playing a mediating role in the impact path. However, the business entrepreneurship is negatively affecting the CE adoption. Also, the proportion of shares hold by the institution has a heterogenous influence for the innovation entrepreneurship.

This study guides policy makers about the role of entrepreneurship and the mediating effect of digital technology and to encourage the adoption of CE for firms.

This study reveals the mediation effect of digital technology in the impact of entrepreneurship on CE in the emerging market. The heterogeneity of the proportion of shares hold by the institutions is also analyzed in the empirical study.

The purpose of this paper is to reveal the co-editing mechanism aiming at content creation, and an entry of online encyclopedia is taken as a case, for the purpose of promoting and enhancing the development of wiki-based digital humanities projects (WDHPs), specifically, the projects that focus on gathering contextual information in the culture heritage domain.

An exploratory study was conducted by three steps. A representative entry’s editorial records were reorganized to obtain a data set of discussion statements (n=608), based on which linked-structures were built, and PageRank algorithm was used to analyze the co-editing process. Skewness statistic was applied to measure the consensus of co-editing, and consensus evolution over time was explored. Linear or curve fitting was performed to analyze the correlation between consensus evolution and its influential factors.

In WDHPs, co-editing activity of content creation can be considered as a large-scale group discussion, consensus can evaluate the efficiency of co-editing, which evolves with time and is influenced by the number of statements, breadth and depth of argumentation structure. Taking “Mogao Grottoes” as an example, group discussions around 15 key issues dominate the content creating process, consensus is on a rise with time, finally reaches a relatively high level, and consensus evolution is more influenced by breadth than by depth of argumentation structure, which indicates that co-editing efficiency of “Mogao Grottoes” is fine and more argumentation in a depth manner should be guided.

For researchers of WDHPs, it is beneficial to apply online encyclopedia platform combining with consensus analysis to develop WDHPs. For designers of WDHPs, the elements related to argumentation structure can be absorbed into the design to promote co-editing in an effective manner. For DH researchers, the analytic procedure can be beneficial of revealing the interest of contributors in a specific DH field.

This research is novel in comprehensively understanding co-editing mechanism of content creation in WDHPs, resulting in a three-step analytic procedure of presenting co-editing process, evaluating and improving co-editing efficiency.

Building upon the framework of glocalization, the purpose of this paper is to summarize the development of National Basketball Association (NBA) in Chinese market, explore its successful and unsuccessful places, and propose strategies of glocalization for the NBA as well as other overseas sport leagues.

The current case study was organized by summarizing the developmental history of NBA in China, analyzing its current promotional practices, investigating into its marketing strategies, and extrapolating practical references for other sport leagues aiming to penetrating into the Chinese marketplace.

The current case study concluded that when facing the current challenges, the NBA needs to bring authentic American cultural commodities while adding Chinese characteristics to accommodate local fans. Meanwhile, the NBA management needs to continue seeking ways to work out and through the differences in government models and cultural contexts between China and USA. In addition, this study suggested that the research framework of glocalization would be an ever intriguing inquiry needed for other sport organizations or leagues seeking expansion to overseas markets.

A thorough case study with the NBA that has achieved huge successes in Chinese markets will provide valuable implications for sport leagues to broaden their overseas markets.

The purpose of this paper is to introduce a novel personal scientific document retrieval system. The most common approach taken for the storage of personal documents is to construct a hierarchical folder structure. Most users prefer searching for documents by manually traversing their organizational hierarchy until reaching the location where the target item is stored, then locating the specific documents within its directory or folder. However, this is very time-consuming, especially when the number of personal scientific documents is very large. Unfortunately, related personal information management (PIM) systems, which provide solutions for managing various types of personal information, have thus far made little progress at managing personal scientific documents.

In this paper, we introduce the design of a personal scientific document retrieval system, namely, LocalContent. It is composed of database indexing and retrieval stages. During indexing, term feature extraction from scientific documents is performed by the natural language processing technique. The extracted terms are stored in the inverted index for later retrieval. For retrieval, a graphical user interface is provided by LocalContent, which allows users to search their personal scientific documents.

The evaluation results based on 20 different personal archives taken from 20 graduate students show that LocalContent is simple to use and can facilitate the search for relevant scientific documents. Moreover, these users were willing to have a system which provides specialized search functions like LocalContent to explore their personal scientific documents in the future.

LocalContent is a novel scientific document retrieval system and provides several particular functions of LocalContent including displaying the content summary of the query term frequency in each specific section of the retrieved documents, querying by local section specification and providing a number of recommended keywords related to the query terms.

This paper provides a quantitative review of the literature on the repercussions of idiosyncratic information on firms’ cost of equity (CoE) capital. In total, I review the results of 113 unique studies examining the CoE effects of information Quantity, Precision and Asymmetry. My results suggest that the association between firm-specific information and CoE is subject to moderate effects. First, the link between Quantity and CoE is moderated by disclosure types and country-level factors in that firms in comparatively weakly regulated countries tend to enjoy up to four times greater CoE benefits from more expansive disclosure—depending on the type of disclosure—than firms in strongly regulated markets. Second, a negative relationship between Precision and CoE is only significant in studies using non-accrual quality proxies for Precision and risk factor-based (RFB)/valuation model-based (VMB) proxies for CoE. Third, almost all VMB studies confirm the positive association between Asymmetry and CoE, but there is notable variation in the conclusions reached when ex post CoE measurers are used.

This research examines the role of a therapist’s attributes, namely, expertise, sociability, likability and mind-set similarity, in building trust, satisfaction and commitment amongst visitors in Indian wellness resorts and hotels.

The text mining approach was adopted to collect a large corpus of 3,94,373 online reviews from TripAdvisor, Google Reviews and hotels.com. Reviews were taken from 1,677 resorts and hotels that deal in spa and wellness care across India. This study uses unsupervised Naïve Bayes classification and n-gram lexical TF-IDF vectorizer method to classify and find the sentiment of the reviews shared by the visitors of the wellness resorts. Additionally, multiple linear regression is performed to understand the impact of the therapist’s identified attributes on the visitor’s relationship quality.

The research found positive sentiment towards the therapist’s likability, and visitors seemed satisfied with the overall wellness service. The sentiment towards trust and commitment is low. The study also found significant links between likability and expertise in building the relationship quality between the therapist and the visitors. The expertise of the therapist enhances visitors’ trust and willingness to return. The therapist’s likability nature helps in increasing visitor satisfaction.

This study helps to understand the service personnel's level of relationship with the customer in hospitality services. Further, the study empirically verifies the important factors that build relationship quality in Indian wellness services.

The present study argues the need for greater clarity in understanding the customer perception of the services provided by wellness therapists in Indian wellness resorts and hotels. The study guides hotel managers to perform training of wellness therapists to improve customer satisfaction. Using the findings of the current study, managers can prioritize therapists’ attributes and realign their core strategies and provide satisfying wellness services to customers.

This study demonstrates the essential qualities a therapist should develop to enhance the relationship with the resort visitors and foster trust, commitment and satisfaction. The study goes a step further by using a vast database of online data for deep insights into the visitor’s view and the use of machine learning for amplifying results.

The purpose of this paper is to present a new human dynamics model to explain the process of verified users' (VUs) posting on Sina micro-blog.

A common human dynamics research method with three steps is applied. Firstly, a large-scale behavioral dataset is collected involving 495 VUs and five topics on Sina micro-blog. Second, five important indicators that reveal the characteristics of posting behavior are analyzed. Then, a quantitative model is constructed to describe the process of posting behavior, and its validity is verified by simulations.

Three important characteristics of VUs' micro-blog posting behavior are observed: fat-tailed distribution, fluctuation and periodicity. These characteristics do not fit the assumption of interest-driven models proposed by previous literature. An optimized task-driven model is introduced to describe this complex phenomenon mathematically. The model is verified on empirical data, confirming that task-driven models can be optimized to explore information behavior on social media.

Being different from previous studies that mainly describe common users' posting behavior on social media by applying interest-driven models, this paper customizes an optimized task-driven model for VUs, who mainly treat social media as a platform for work and play a crucial role in information creation on social media.

The environment in which users acquire medical and health information has changed dramatically, with online health communities (OHCs) emerging as an essential means for accessing health information. It is imperative to comprehend the factors that shape the users' compliance willingness (UCW) to health information in OHCs.

This study adopted the information adoption model (IAM) and theory of planned behavior (TPB) to investigate the influence of argument quality (AQ), source credibility (SC) and subjective norms (SN) on UCW while considering the two types of online health information – mature and emerging treatments. The authors conducted an explanatory-predictive study based on a 2 (treatment types: mature vs. emerging) * 2 (AQ: high vs. low) * 2 (SC: high vs. low) scenario-based experiment, using the partial least squares structural equation modeling (PLS-SEM).

SC positively influences AQ. AQ, SC and SN contribute to information usefulness (IU). These factors positively affect UCW through the mediation of IU. SN were found to improve UCW directly. Moreover, the moderating effect of SC on AQ and IU was more substantial for emerging treatments.

The research model integrates IAM and TPB, considering information types as an additional variable. The approach and findings provide a valuable explanation for UCW to health information in OHCs.

Facing the competition pressure of internationalization and diversification, the semiconductor industry of Taiwan has to increase the activation/utilization rate of machines, enhance flow speed and values, cut down delivery and reduce costs in an efficient way in reaction to a shortening product life cycle and the global market requirements. As a result, introduction of ERP has become a critical factor of enhancing competitiveness. The purpose of this study is establish a systematic evaluation and improvement mechanism to locate the risk priority number (RPN) of implementation items via failure mode and effects analysis (FMEA) for semiconductor related industries in Taiwan while introducing ERP.

A standardized system introduced performance matrix based on the performance evaluation matrix (PEM) will be established in accordance with the locations of severity (S), occurrence (O) and detection (D) and the three RPN indices, in the PEM. Performance levels will be assessed and the performance improvement strategy introduced by the system will be formulated. Finally, items falling within the non‐appropriate performance zone will be specified through the quality function development (QFD) method.

From the results of the case study, the proposed systematic evaluation and improvement on the performance of introducing ERP for the semiconductor industry in Taiwan can be conducted in an efficient way.

All that the management needs to do is to correspond to the positions of these RPN indices of implementation items on the performance matrix. Performance levels will be assessed and the performance improvement strategy introduced by the system will be formulated.

The PEM is demonstrated to be suitable to define the best countermeasure can be sought to serve as a reference for the semiconductor related industries in Taiwan to introduce ERP.

Electricity demand forecasting has always been a key issue, and inaccurate forecasts may mislead policymakers. To accurately predict China’s electricity demand up to 2030, this paper aims to establish a cross-validation-based linear model selection system, which can consider many factors to avoid missing useful information and select the best model according to estimated out-of-sample forecast performances.

With the nine identified influencing factors of electricity demand, this system first determines the parameters in four alternative fitting procedures, where for each procedure a lot of cross-validation is performed and the most frequently selected value is determined. Then, through comparing the out-of-sample performances of the traditional multiple linear regression and the four selected alternative fitting procedures, the best model is selected in view of forecast accuracy and stability and used for forecasting under four scenarios. Besides the baseline scenario, this paper investigates lower and higher economic growth and higher consumption share.

The results show the following: China will consume 7,120.49 TWh, 9,080.38 TWh and 11,649.73 TWh of electricity in 2020, 2025 and 2030, respectively; there is hardly any possibility of decoupling between economic development level and electricity demand; and shifting China from an investment-driven economy to a consumption-driven economy is greatly beneficial to save electricity.

Following insights are obtained: reasonable infrastructure construction plans should be made for increasing electricity demand; increasing electricity demand further challenges China’s greenhouse gas reduction target; and the fact of increasing electricity demand should be taken into account for China’s prompting electrification policies.