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Using two main research questions, the purpose of this paper is to examine well-being and preparedness among Cambodian and Laotian immigrants living near the Gulf Coast of the USA, and the ways in which indicators such as sense of community and risk perception are related to these constructs.

This study employed a cross-sectional prospective design to examine disaster preparedness and well-being among Laotian and Cambodian immigrant communities. Quantitative survey data using purposive snowball sampling were collected throughout several months in Alabama, Mississippi, Florida and Louisiana.

Results from two multiple regressions revealed that sense of community and age contributed to well-being and were significant in the model, but with a negative relationship between age and well-being. Risk perception, confidence in government, confidence in engaging household preparedness and ability to cope with a financial crisis were significant predictors and positively related to disaster preparedness.

Well-being and disaster preparedness can be bolstered through community-based planning that seeks to address urgent needs of the people residing in vulnerable coastal locations. Specifically, immigrants who speak English as a second language, elder individuals and households in the lowest income brackets should be supported in disaster planning and outreach.

Cambodian and Laotian American immigrants rely upon the Gulf Coast’s waters for fishing, crab and shrimp income. Despite on-going hazard and disasters, few studies address preparedness among immigrant populations in the USA. This study fills a gap in preparedness research as well as factors associated with well-being, an important aspect of long-term resilience.

Urban MICE competitiveness research consists of two clusters, one that is public-statistics-based and another that is questionnaire-based. Supply-side research on urban MICE competitiveness is rare. Based on the findings of Chen (2014) and other scholars, the purpose of this paper is to design counterpart statistical indicators to empirically analyze CMCA member cities.

After calculating the standardized Z value of the original statistical data for 17 CMCA member cities, the authors conducted confirmatory factor analysis for the first-level principal components, based on which hierarchical clustering was performed; then, regression analysis was conducted with the MICE profit factor as the dependent variable and the cost factor, tight support factor and facilitating factor as the independent variables to support publishing articles.

The confirmatory factor analysis showed that the urban MICE competitiveness indicators from the supply-side perspective include the profit factor, cost factor, tight support factor and facilitating factor.

On the basis of research findings from the demand perspective and the literature review, the authors constructed an urban MICE competitiveness indicator system from the perspective of the supply side and conducted principal component analysis. However, because of the inaccessibility of panel data, the current data were only sufficient to conduct the research. If panel data could be acquired, further research could be conducted to perfect the current indicator system for urban MICE competitiveness.

The findings suggest that tourism total income, tourism foreign exchange income, inbound tourist number, number of exhibitions, exhibition area, number of UFI member cities and number of ICCA member cities were the main reason for the gap between different cities’ competitiveness and the reform focus for improving urban MICE competitiveness. The cost factor had a significantly negative influence on urban MICE competitiveness, implying that the higher the average hotel room price and revenue per available room, the less competitive the MICE host city is.

The tight support factor exerts a significant positive influence on urban MICE competitiveness from the supply-side perspective, while the cost factor exerts a significant negative influence. The findings suggest that the tourism total income, tourism foreign exchange income, inbound tourist number, number of exhibitions, exhibition area, number of UFI member cities and number of ICCA member cities were the main reason for the gap between different cities’ competitiveness and the reform focus for improving urban MICE competitiveness. The cost factor had a significantly negative influence on urban MICE competitiveness, implying that the higher the average hotel room price and revenue per available room, the less competitive the MICE host city is.

The research bridge the empirical statistics and the questionnaire-based perception study on urban MICE tourism image, and advance to construct an empirical statistics based indicator system for urban MICE tourism image.

The purpose of this paper is to evaluate the possibility of rating the credit worthiness of a firm’s quarterly financial report using a dynamic anomaly detection method.

The study uses a data set containing financial statements from Quarter 1 – 2001 to Quarter 4 – 2016 of 937 Vietnamese listed firms. In sum, 24 fundamental financial indices are chosen as control variables. The study employs the Mahalanobis distance to measure the proximity of each data point from the centroid of the distribution to point out the extent of the anomaly.

The finding shows that the model is capable of ranking quarterly financial reports in terms of credit worthiness. The execution of the model on all observations also revealed that most financial statements of Vietnamese listed firms are trustworthy, while almost a quarter of them are highly anomalous and questionable.

The study faces several limitations, including the availability of genuine accounting data from stock exchanges, the strong assumptions of a simple statistical distribution, the restricted timeframe of financial data and the sensitivity of the thresholds for anomaly levels.

The study opens an avenue for ordinary users of financial information to process the data and question the validity of the numbers presented by listed firms. Furthermore, if fraud information is available, similar research can be conducted to examine the tendency for companies with anomalous financial reports to commit fraud.

This is the first paper of its kind that attempts to build an anomaly detection model for Vietnamese listed companies.

This paper aims to test the influence of external information search (EIS) on knowledge elaboration and group cognitive complexity (GCC) under the moderating effect of absorptive capacity (AC is indicated by prior knowledge base and gender diversity).

The results of three studies (one field study and two experimental studies) are reported. The first study tests the interaction between EIS and the two dimensions of AC on group knowledge elaboration in a sample of 65 organizational groups. In the second study, EIS was directly manipulated and the interaction with AC in a sample of 65 groups was tested. In the last experimental study, the AC of the boundary spanner (highest level of expertise versus lowest level of expertise) was manipulated and the effects of EIS in a sample of 37 groups were tested.

The first study reveals a significant interaction between EIS and prior knowledge base on knowledge elaboration and points toward a compensatory interplay of EIS and AC on GCC. The results of the second study indicate that EIS increases the time spent on task, as well as the efficiency of knowledge integration (GCC per unit of time). Furthermore, EIS has the strongest positive effect on GCC in groups in which at least one of the AC dimensions is average or high. The results of the last study show that the AC of the boundary spanner compensates for the lack of absorptive capacity of the group and also show that the cognitive distance between the boundary spanner and the rest of the group has a negative influence on the efficiency of knowledge integration in groups.

The limitations of Study 1, common to non-experimental research (related to causality), are dealt with in the second and third studies that establish causality between EIS and GCC.

The paper has important implications for the management of information search effort in organizational groups, in particular the groups are advised to: engage in EIS to increase their cognitive repertoire and cognitive complexity, delegate, when possible, their most competent members to engage in boundary spanning activities as they will maximize the cognitive benefits of EIS and finally minimize the cognitive dissimilarity between the boundary spanner and the rest of the group to facilitate the effective integration of novel insights into the group cognition.

This study is among the first empirical attempts to uncover the causal effect of EIS on knowledge elaboration and GCC in groups and to uncover the role of the boundary spanner in the EIS efforts.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

Literature evidences that altruism and conscientiousness are very important discretionary behaviours within the broader framework of Organizational Citizenship Behaviour (OCB) among teaching community. The present study is intended to examine the effect of role clarity, perceived cohesion and felt responsibility on altruism and conscientiousness among college teachers in Kerala.

A questionnaire-based survey was conducted among 354 college teachers, and the causal effect was examined using Partial Least Square-based structural equation modelling.

Validity and reliability of the model were established through measurement model evaluation. Explanatory power of the model was established. Cohesion and felt responsibility significantly predicted altruism, but the effect of role clarity on altruism was not significant. Effect of cohesion, felt responsibility and role clarity on conscientiousness was significant.

The study contributed to the existing theory on antecedents of OCB. The model has high levels of predictive accuracy – role clarity, cohesiveness and felt responsibility – capable of explaining the discretionary behaviour among college teachers.

This paper examines whether farmers' knowledge of the minimum support prices (MSPs) affects farm-gate prices. MSP is the minimum guaranteed price for agricultural commodities announced by the Government of India for 24 commodities. Most farmers in India prefer to sell their produce at the farm-gate due to a small marketable surplus and hence do not directly benefit from MSP. The authors test the common argument in the political discourse that if farmers have knowledge of MSP, then they can bargain with traders during the farm-gate transaction and demand a better price close to MSP.

The authors use matching methods to examine the impact of knowledge of MSP on farm-gate prices.

Using nationally representative data, the authors show that there is no empirical evidence that the knowledge of MSP of the crops leads to higher bargaining power and better farm-gate prices.

Price information (MSP in this case) alone cannot improve the bargaining power of farmers and result in a better price realization. As a safety net, MSP fails in the absence of procurement of products by the government. This also raises the question of the equitability of the price support system in India and calls for a rethink of the MSP policy.

This study is the first of its kind to examine the anchoring effect of knowledge of MSP on farm-gate prices using a nationally representative dataset.

The purpose of this paper is to accurately capture the risks which are caused by each road user in time.

The authors proposed a novel risk assessment approach based on the multi-sensor fusion algorithm in the real traffic environment. Firstly, they proposed a novel detection-level fusion approach for multi-object perception in dense traffic environment based on evidence theory. This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception. The information of object type, position and velocity was accurately obtained. Then, they conducted several experiments in real dense traffic environment on highways and urban roads, which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios. By analyzing the generation process of traffic risks between vehicles and the road environment, the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated. The prediction steering angle and trajectory were considered in the determination of traffic risk influence area.

The results of multi-object perception in the experiments showed that the proposed fusion approach achieved low false and missing tracking, and the road traffic risk was described as a field of equivalent force. The results extend the understanding of the traffic risk, which supported that the traffic risk from the front and back of the vehicle can be perceived in advance.

This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception. The information of object type, position and velocity was used to reduce erroneous data association between tracks and detections. Then, the authors conducted several experiments in real dense traffic environment on highways and urban roads, which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios. By analyzing the generation process of traffic risks between vehicles and the road environment, the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated.

This paper explores the relationships between firm absorptive capacity, novel business model design (NBMD), product differentiation strategy and performance in a transition economy.

The study uses structural equation modeling (SEM) to analyze firm-level data from a unique sample of Albanian manufacturing and service firms.

The study shows that absorptive capacity enables and shapes the NBMD that, in turn, leads to performance gains. The authors also find that the NBMD capacity mediates the impact of realized absorptive capacity on performance, whereas product differentiation strategy moderates the relationship between new business model and performance.

All variables were measured based on a self-assessed scale leading to potential method bias. Also, based on relevant literature, the study focuses on only one type of business model (BM) design.

Since dynamic capabilities are the foundation of NBMD, firms should invest carefully in developing such capabilities. Thus, the study results provide an integrative framework for understanding the role of absorptive capacity in NBMD adoption and for explaining the relationship between NBMD adoption and performance, an aspect that helps organizations in a dynamic environment.

This study strives to investigate the relationships between absorptive capacity, business model design, product strategies and performance by answering the call of Teece (2018) to “flesh out the details” of such relationships.

Drawing on the social exchange theory (SET) and the self-determination theory (SDT), the present study aims to examine the impact of green human resource management (GHRM) on three types of employee green behavior (EGB) – green in-role, innovative and extra-role – in the presence of environmental managerial support (EMS) as a conditional factor.

The research model was verified based on data from 419 respondents employed in companies operating in the energy sector in Poland (Europe’s “coal heartland”). PLS-SEM was used in the statistical analyses.

This study shows that GHRM positively impacts three types of EGB. EMS positively moderates the relationships of GHRM with both green extra-role behaviors and innovative work behaviors; however, EMS does not play a moderating role in the relationship between GHRM and green in-role behaviors.

This study, being one of a kind, enriches the literature by exploring the conditional role of EMS on the integrated relationship of GHRM practices with in-role, extra-role and innovative behaviors and offers evidence from the rarely examined energy sector, which plays a vital role in the transformation of nations toward sustainable development.