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Constructing a fuzzy control chart with interval-valued fuzzy data is an important topic in the fields of medical, sociological, economics, service and management. In particular, when the data illustrates uncertainty, inconsistency and is incomplete which is often the. case of real data. Traditionally, we use variable control chart to detect the process shift with real value. However, when the real data is composed of interval-valued fuzzy, it is not feasible to use such an approach of traditional statistical process control (SPC) to monitor the fuzzy control chart. The purpose of this paper is to propose the designed standardized fuzzy control chart for interval-valued fuzzy data set.

The general statistical principles used on the standardized control chart are applied to fuzzy control chart for interval-valued fuzzy data.

When the real data is composed of interval-valued fuzzy, it is not feasible to use such an approach of traditional SPC to monitor the fuzzy control chart. This study proposes the designed standardized fuzzy control chart for interval-valued fuzzy data set of vegetable price from January 2009 to September 2010 in Taiwan obtained from Council of Agriculture, Executive Yuan. Empirical studies are used to illustrate the application for designing standardized fuzzy control chart. More related practical phenomena can be explained by this appropriate definition of fuzzy control chart.

This paper uses a simpler approach to construct the standardized interval-valued chart for fuzzy data based on traditional standardized control chart which is easy and straightforward. Moreover, the control limit of the designed standardized fuzzy control chart is an interval with (LCL, UCL), which consists of the conventional range of classical standardized control chart.

This study aims to examine the relationship between green technology implementation (GTI), knowledge management (KM) process and knowledge workers' operational performance (KWOP). The research postulates that a specific combination of GTI and KM processes can lead to improving KWOP.

The sample data (304) were taken from those manufacturing firms that are utilizing green technology. The examination was conducted by Smart PLS-SEM and fuzzy set qualitative comparative analysis (fsQCA). The Smart PLS 3.29 is used to verify certain variable relationships. Moreover, fsQCA is used to investigate multiple configuration paths to enhance KWOP.

The study's outcome indicated that GTI positively influences the KM process in manufacturing firms, and the KM process enormously improves KWOP. The fsQCA analysis result explores various integrations (communication, collaboration, supporting role and improved performance) with the KM (acquisition, sharing and utilization) process identified to enhance the performance of KWOP. The current study supports two merging methods to deepen understanding of employee operational performance.

The study methodologically contributes by integrating direct and configuration approaches to develop firms' operational performance. This study contributes to bridging research gaps in the prior literature and advances insight into the association between GTI, KM process and KWOP.

Constructed upon knowledge-based view, the study examines the influence of internal marketing on knowledge management processes and the indirect association of knowledge management processes with organizational performance through mediating role of knowledge worker satisfaction.

This study used a sample frame of 536 academic and administrative employees from higher education institutions in China; structural equation modeling was performed using Smart PLS 3.2.8.

The outcome reveals that internal marketing has a significant impact on knowledge management processes. The results revealed a direct insignificant impact of knowledge management processes on organizational performance; the study found full mediation of knowledge worker satisfaction on the linkage between knowledge management processes and organizational performance.

Outcomes of this research strengthen the universities’ experience of knowledge management and recommend how academics and administrators of higher education institute can value knowledge worker satisfaction, which in turn improves organizational performance.

Although, there is an increased significance of knowledge management in higher education institutions, there is a lack of research that examines the enabling factors and outcomes of knowledge management practices. The present study is one of the first studies to ascertain the relationship of internal marketing, knowledge management processes, knowledge worker satisfaction and organizational performance. This is one of the initial research studies that not only empirically examines the interrelationships among these variables but also enlightens insights into the current literature by instantaneous investigation of the mediating role of knowledge worker satisfaction.

Constructed upon knowledge-based view theory, this study investigates the influence of internal marketing (IM) on knowledge management (KM) processes in higher educational institutes (HEIs) in China and Pakistan. The study investigates the direct link between KM processes and organizational performance and indirect links via knowledge workers' productivity (KWP).

Data were collected from HEIs in China and Pakistan, and 784 survey responses were reported from academic and administrative staff (HEIs).

The result revealed that IM has a significant impact on KM processes, and KM processes impact organizational performance via the partial mediating effect of KWP in China, Pakistan and the overall sample. The multi-group analysis confirmed the substantial differential effect of KM processes on KWP in culturally different HEIs.

A lack of research establishes the inter-relationship between KM enabler (IM), KM processes, KWP and organizational performance in culturally diverse environments. This is one of the initial studies that examine the relationship between IM, KM processes, KWP and organizational performance in HEIs. Furthermore, this study contributes to the existing body of knowledge by conducting an in-depth empirical examination of IM, KM processes, KWP and OP in culturally diverse environments (i.e. China and Pakistan).

1. This research examines the influence of internal marketing (IM) on knowledge management (KM) processes by using knowledge workers' productivity (KWP) as a mediator between knowledge management (KM) and organizational performance.

2. Through the partly mediating effect of KWP, it was discovered that IM considerably influenced knowledge management processes and organizational performance in China, Pakistan and throughout the sample.

3. The multi-group analysis indicates that KMPs have a statistically significant influence on KWP.

This research examines the influence of internal marketing (IM) on knowledge management (KM) processes by using knowledge workers' productivity (KWP) as a mediator between knowledge management (KM) and organizational performance.

Through the partly mediating effect of KWP, it was discovered that IM considerably influenced knowledge management processes and organizational performance in China, Pakistan and throughout the sample.

The multi-group analysis indicates that KMPs have a statistically significant influence on KWP.

Higher Education Institutions (HEIs) require regular generation of information determining what employees want from their institution and their real feelings about their jobs. Internal marketing (IM) can be a significantly valuable source of generating such information for HEIs to assess perceptions about institutions’ initiatives pertinent to their staff members. However, there has been a significantly limited research to operationalize IM in HEIs. Hence, the purpose of this paper is to develop and validate a multi-dimensional instrument for measuring IM in the HEIs in China and to assess the impact of IM on university performance.

The research used methodological triangulation that involved both qualitative and quantitative methodologies. The qualitative technique was used to generate scale items to measure IM and the quantitative technique was utilized to test and validate the scale. The study sample included 576 academics and administration staff from universities in China.

The study found that IM has six dimensions, namely internal communications, training and development, interrelations, motivation, rewards and work support. The study also found a significant impact of IM on university performance.

The sample size used was taken from a single province, which can ultimately limit the generalizability of the results. The scale shall be tested in a different cultural setting to extend its generalizability. In comparison with previous studies, the results of the current study provide a more absolute coverage and understanding of various dimensions used in measuring IM in HEIs. Furthermore, this research can provide a context for the management to develop policies that could foster positive employee and organizational outcomes in HEIs.

This reliable and valid six-dimensional scale offers a practical way to measure staff perceptions of IM that are key for HEIs to be judged as staff-centered organization. Based on the knowledge, HEIs can use the information to identify the areas in which they are lacking and can further improve. IM scale can significantly help the HEIs to communicate to the staff members their service mindedness and staff orientation. IM can help foster knowledge management in organizations by utilizing IM, thereby contributing to the professional and organizational interaction.

Despite the focus on IM in existing literature, there is a significant lack of research on IM in the education sector. This study developed a simple and practical instrument to measure the IM construct in HEIs. Scholars have asked for context-specific measures of IM and with significantly limited research on IM in higher education, there is also a scarcity of research in the context of higher education in China. This is the first study to assess the multi-dimensionality of IM in HEIs and the impact of IM on organizational performance in Chinese higher education.

Constructed upon the knowledge-based view, the purpose of this study is to investigate the interrelationship between internal marketing, knowledge management processes and knowledge worker satisfaction. The study also postulates that specific combinations of internal marketing dimensions and knowledge management processes can lead to improved knowledge worker satisfaction.

The study sample is gathered from 248 personnel of Pakistan higher education institutions (HEI’s). The interrelationships are checked through Smart PLS 3.2.8. The fuzzy set qualitative comparative analysis (fsQCA) is used to examine configurational paths for improving knowledge worker satisfaction.

The results of the study show that in HEI’s, internal marketing has a substantial influence on knowledge management processes, and knowledge management processes strongly enhance knowledge worker satisfaction. The result from fsQCA reveals multiple configurational paths to improve knowledge worker satisfaction.

There is a scarcity of research that has explored the association of internal marketing, knowledge management processes and knowledge worker satisfaction. This study attempts to examine their inter-relationships in HEI’s. Methodologically, the study contributes by combining direct and configurational methods to foster the knowledge of organizational (higher education) matters. The use of fsQCA reveals multiple pathways to improve knowledge worker satisfaction and exposes asymmetric relationships between internal marketing and knowledge management processes that lead to knowledge worker satisfaction. The study identifies the interactions among variables that might not be directly obvious via conventional symmetric methods.

An increasing number of investors have begun using financial data to develop optimal investment portfolios; therefore, the public financial data shared in the capital market plays a critical role in credit ratings. These data enable investors to understand the credit levels of debtors from a bank perspective; this facilitates predicting the debtor default rate to efficiently evaluate investment risks. The paper aims to discuss these issues.

A credit rating model can be developed to reduce the risk of adverse selection and moral hazard caused by information asymmetry in the loan market. In this study, a random forest (RF) was used to evaluate financial variables and construct credit rating prediction models. Data-mining techniques, including an RF, decision tree, neural networks, and support vector machine, were used to search for suitable credit rating forecasting methods. The distance to default from the KMV model was then incorporated into the credit rating model as a research variable to increase predictive power of various data-mining techniques. In addition, four-level and nine-level classification were set to investigate the accuracy rates of various models.

The experimental results indicated that applying the RF in the variable feature selection process and developing a forecasting model was the most effective method of predicting credit ratings; the four-level and nine-level feature-selection settings achieved 95.5 and 87.8 percent accuracy rates, respectively, indicating that RF demonstrated outstanding feature selection and forecasting capacity.

The experimental cases were based on financial data from public companies in North America.

Practical implication of this study indicates the most effective financial variables were dividends common/ordinary, cash dividends, volatility assumption, and risk-free rate assumption.

The RF model can be used to perform feature selection and efficiently filter numerous financial variables to obtain crediting rating information instantly.

Social media fatigue (SMF) has been widely recognized; however, previous studies have included various concepts into a single fatigue construct. Fatigue has typically been explored from the stressor-strain-outcome (SSO) or stimulus-organism-response (SOR) perspectives. To further investigate SMF, the authors split it into the two constructs of exhaustion and disinterest. Furthermore, the authors introduced the concept of emotional labor and identified rules that may affect surface and deep acting strategies.

The authors designed and conducted a survey to collect data from social networking platform users.

Results from 364 users of social networking platforms supported most of the authors' hypotheses. First, most of the display rules affect the choice of deep or surface acting. Second, both types of acting lead to exhaustion, but only surface acting leads to disinterest. Third, discontinuance intention is affected by both types of fatigue.

This study contributes to SMF research by adding more antecedents (deep and surface acting) based on the emotional labor perspective and showing the impacts of communication rules on emotional labor. In addition, this study also distinguishes disinterest-style fatigue from exhaustion.

This study was to develop a methodology of online review analytics for hotel quality management at macro and micro levels. The macro level was for understanding the service properties critical to quality and future development. The micro level was for personalized quality diagnosis for individual hotels.

Textual reviews of superior hotels were studied using latent semantic analysis and Kano model to understand what service properties customers concern and expect. Taguchi's quality engineering was applied to establish a quality reference base using superior hotels for evaluating other hotels in the same semantic space. A decision tree algorithm was then used to identify the properties critical to quality discrimination, and the decision rules were used to diagnose individual hotels.

The service properties concerned by customers for superior hotels were identified. The market positioning and value of each property to customers were clarified. For individual hotels, the deficiencies of service properties were diagnosed. With reference to market positioning, deficient properties of priority in improvement and the strategies for enhancing competitiveness were suggested.

The proposed methodology demonstrated the potential value that review analysis can achieve a new and deeper understanding of customer voices and transform it into more specific business operation requirements. The research and application gap that most previous studies only stayed at the macro-level analytics was filled. Moreover, this study effectively applied the diagnostic techniques derived from quality engineering to online review analytics.