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Short-form health science videos have become an important medium for disseminating health knowledge and improving public health literacy. However, the factors that determine viewer engagement are not well understood. This study aims to address this research gap by investigating the association between doctor image features and viewer engagement behavior, building on the personal branding theory and information signaling theory.

A sample of 1245 health science short-form videos was collected, and key video features related to doctor images were extracted through manual labeling. Multi-variable regression analysis and SPSS process model were employed to test the hypotheses.

The results show that doctor image features are significantly associated with viewer engagement behavior. Videos featuring doctors in medical uniforms receive more viewer likes, comments and shares. Highlighting the doctor's title can increase viewer collections. Videos shot in a home, white wall, or study room setting receive more like, comments and sharing. The doctor's appearance demonstrates a positive nonlinear relationship with viewer likes and comments. Young doctors with title information tend to attract more video collections than older doctors with title information. The positive effect of the doctor's appearance and showing title information, become more significant among male doctors.

This research provides novel insights into the factors that determine viewer engagement behavior in short-form health science videos. Specific doctor image features can enhance viewer engagement by signaling doctor professionalism. The results also suggest that there may be age and gender biases in viewers' perceptions.

Seru (cell) manufacturing system has achieved huge success in production. However, related research is limited, especially, the problem of cross-trained worker assignment. The purpose of this paper is to solve this problem for two representative seru types, divisional and rotating seru, and subsequently, compare throughput performance between the two seru types under reasonable worker-task assignment.

For the cross-trained worker assignment problem, this research presents new models aiming at maximum throughput of seru and workload balance of workers under considering skill levels (SLs) and several practical constraints. Furthermore, factorial experiments that involve four factors, the number of tasks (NT), gap of task time, SL and gap of SL, are performed to compare throughput performance between divisional and rotating seru.

First, the maximum throughput of the divisional seru is better than that of the rotating seru under suitable worker assignment. Second, in the seru which has less difference of task time, throughput performance of the rotating seru is better than the divisional seru when the NT is close to the number of assigned workers. Moreover, the influence tendency of the four factors on throughput gap between the two seru types is significant.

This research addresses the worker-task assignment for divisional and rotating seru based on their characteristics. Several findings can help decision maker select more applicable seru type according to various production environments from the perspective of optimum throughput.

Research focusing on psychological capital (PsyCap) has been mainly conducted at the individual level. However, recent research has expanded investigations to the collective level with a greater focus on team-level PsyCap. Although, as demonstrated by recent systematic reviews and meta-analyses, the relationships between individual-level PsyCap and the desirable/undesirable outcomes are fairly established in the literature, less is known about such relationships for team-level PsyCap. One of these important, yet least investigated, research areas is the research stream that focuses on the relationship between team-level PsyCap and the outcomes of health, Well-Being, and safety. This chapter aims to highlight the role of individual-level PsyCap as an important predictor of employees’ health, Well-Being, and safety outcomes, but also to go beyond that to provide insights into the potential role of team-level PsyCap in predicting such outcomes at both individual and team levels. To do so, the chapter first draws upon relevant theories to discuss the empirical research findings focusing on the relationship between individual-level PsyCap and the outcomes of health, Well-Being, and safety. It then focuses on team-level PsyCap from theoretical, conceptualization, and operationalization perspectives and provides insights into how team-level PsyCap might be related to health, Well-Being, and safety outcomes at both individual and team levels. Thus, this chapter proposes new research directions in an area of PsyCap that has been left unexplored.

The purpose of this paper is to investigate the association between ownership structure and the properties of analysts’ forecasts in China’s unique corporate setting.

Multiple regression models were used to examine the influence of ownership structure mechanisms on analysts’ forecast properties for listed Chinese firms during the period 2008-2012.

The paper finds that analysts’ forecast accuracy is higher for listed firms with high levels of foreign ownership and managerial ownership. However, the complex pyramidal ownership structure could make corporate information less transparent and then increase the complexity of forecasting; hence, it results in less precise analysts’ forecasts. Interestingly, the relationship between state ownership and analysts’ forecast properties appears to be non-linear (an inverted U-shape), and the inflection point at which the relationship becomes negative occurs at state ownership over 45 per cent.

To the best of the author’s knowledge, this paper is the first to investigate the influence of ownership structure mechanisms on the properties of analysts’ forecasts in an emerging market, and the findings provide some insight on how the properties of analysts’ forecast might be shaped by certain ownership and control features in the context of concentrated state ownership and complex pyramidal ownership structure.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

The purpose of this paper is to examine how a firm’s investment behavior relates to its subsequent bank loan contracting.

Using a sample of US firms during the period 1992-2011, the authors examine the association between overinvestment (underinvestment) and three characteristics of bank loan contracts: loan spread, collateral requirement, and loan maturity.

The authors find that overinvesting firms obtain loans with higher loan spreads. Additional tests show that the effect of overinvestment on loan spreads is generally more pronounced in firms with lower reputation, weaker shareholder rights, and lower institutional ownership. The effect of overinvestment on collateral requirement is mixed, and investment efficiency has no significant relation to loan maturity.

The results are subject to the following caveats. First, while the study provides empirical evidence that investment efficiency affects bank loan contracting terms, especially the cost of bank loans, the underlying theory is not well-developed. The authors leave it up to future research to provide a theoretical framework to clearly distinguish the cash flow and credit risk effects of past investment behavior from those of existing agency conflicts. Second, due to data limitation, the sample size is small, especially when the authors control for corporate governance measured by G-index and institutional ownership.

The finding that overinvestment is costly to corporations suggests that managers should consider the potential trade-offs from such investment decisions carefully. The evidence also alerts shareholders and board members to the importance of monitoring management investment decisions. In addition, the authors find that corporate governance moderates the relationship between investment decisions and cost of bank loans, suggesting that it would be beneficial to design effective governance mechanisms to prevent management from empire building and motivate managers to pursue efficient investment strategies.

First, the findings enhance understanding of the potential economic consequences of overinvestment decisions in the context of a firm’s private debt contracting. The evidence suggests that lenders perceive higher credit risk from overinvestment than from underinvestment, likely because firms squander cash in the current period by investing in (negative net present value) projects that are likely to result in future cash flow problems. Second, the study contributes to the literature on the determinants of bank loans by identifying an observable empirical proxy for uncertainty in future cash flows that increases credit risk.

The purpose of this study is to review the literature of enterprise capability, which comprises the three dimensions of operational, dynamic and improvisational capabilities, and analyze their differences. Through this review, the authors aim to enrich the enterprise capability theory and provide some directions for entrepreneurial practice in the face of volatility, uncertainty, complexity and ambiguity (VUCA).

The study is based on a systematic review of the literature on enterprise capability as it relates to entrepreneurial firms, following the content analysis approach as described in Gaur and Kumar (2018).

The authors’ conceptual model compares the capability levels of startups and mature enterprises and presents a model for the dynamic evolution of the capability levels of enterprises. In doing so, this study enriches the enterprise capability theory and lays the theoretical foundation for the follow-up empirical research. The authors also provide guidance for entrepreneurial practice in the face of VUCA.

In recent years, scholars have begun to explore the issue of enterprise capability in the field of entrepreneurship. However, because of different research perspectives, one lacks clarity on the concept and dimensions of enterprise capability. The capability theory is relatively weak in guiding the practice of enterprises; enterprises lack effective response strategies in a changing environment, and the failure rate of startups is high. This study aims to develop a deeper understanding of enterprise capability.

Purpose – In this chapter, we expand the definition of disaster through combining the tenets of disaster studies with the literature on risks and consequences of war and conflict-related displacement and dislocation, with a focus on the challenges that drug misuse and changing drug markets present in these contexts. We conclude with policy recommendations for successful community rebuilding with relation to drugs and drug markets following various forms of disaster, gleaned from the combination of these areas of inquiry.

Design/methodology/approach – We discuss the concepts of risk, social vulnerability, and consequences as related to traditional conceptualizations of disaster, and highlight how they can also be applied to the study of veterans returning from war. We focus the on the similarities related to drugs and drug markets.

Findings – Overall, the similar vulnerabilities, potential for trauma, and drug-related consequences experienced by both disaster survivors and veterans suggest that the experience of war and return from such an event could be considered a disaster and analyzed as such.

Originality/value of power – Few scholars have examined how to expand the definition of a disaster and what is examined in the field of disaster studies. This chapter does this by examining how war could be analyzed as a disaster. It demonstrates the parallels between war and traditional disaster.

The aim of this paper is to examine how the co‐evolution of two order systems‐guanxi networks and legal system, i.e. a dual order system‐has shaped the growth of China's SMEs. From an institutional perspective, one proposition suggested has been that building guanxi networks can facilitate the growth of China's SMEs when institutions change in unpredictable ways. Another proposition claims legal institutions become guarantors of the growth of China's SMEs as a result of competition in increasingly market‐oriented environment.

Over a nine‐year period (1998‐2006), this study conducts in‐depth interviews with 18 top managers of three Chinese SMEs in Wenzhou, a city located in south of China. To identify potential research subjects, SMEs that had been operating for a period of at least five years and privately‐owned were chosen. Since institution evolution is characterized with a longitudinal nature, the authors gathered data from three different time periods in order to capture the richness of the phenomenon.

Dual order mechanisms consisting of guanxi networks (informal institutions) and codified laws (formal institutions) are both relevant in the growth of SMEs: guanxi networks are more significant at earlier stages of growth whereas legal systems are more influential in later stages. This argument is supported with data collected from three longitudinal case studies of SMEs in China.

Data were obtained from three companies in Wenzhou of China, thus findings might not be generalizable across the country.

Three longitudinal case studies are unique. According to Pettigrew, longitudinal methods may be the only way to uncover processes of institutional change. The paper investigates the role of dual order system consisting of guanxi and legal systems in the growth of China's SMEs. The research not only contributes to the guanxi literature but also enables managers and investors to better understand the guanxi practice and role of legal systems in the growth of SMEs.

This paper aims to propose an 18th-order nonlinear model for doubly fed induction generator (DFIG) wind turbines. Based on the proposed model, which is more complete than the models previously developed, an extended Kalman filter (EKF) is used to estimate the DFIG state variables.

State estimation is a popular approach in power system control and monitoring because of minimizing measurement noise level and obtaining non-measured state variables. To estimate all state variables of DFIG wind turbine, it is necessary to develop a model that considers all state variables. So, an 18th-order nonlinear model is proposed for DFIG wind turbines. EKF is used to estimate the DFIG state variables based on the proposed model.

An 18th-order nonlinear model is proposed for DFIG wind turbines. Furthermore, based on the proposed model, its state variables are estimated. Simulation studies are done in four cases to verify the ability of the proposed model in the estimation of state variables under noisy, wind speed variation and fault condition. The results demonstrate priority of the proposed model in the estimation of DFIG state variables.

Evaluating DFIG model to estimate its state variables precisely.