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Most of the studies in entrepreneurship depend on single-source rating methods to collect data on both predictors and criteria. The threat to effect sizes as a result of using single-source ratings is particularly relevant to psychology-based entrepreneurship research. Therefore, the purpose of this paper is to explore the prospects of applying 360-degree feedback to the field of entrepreneurship and to discuss a set of cases regarding how 360-degree feedback may boost effect sizes in entrepreneurship research.

A qualitative review of current literature was performed.

The review indicated that the effect sizes in psychology-based entrepreneurship research are mostly small and the use of single-source ratings is prevalent; some preliminary findings supported the utility of 360-degree feedback in entrepreneurship research; entrepreneurial orientation (EO) research may benefit from 360-degree feedback; and members of top management teams, employees from research and product development, sales agents, retail buying agents, store sales clerks, and consumers are all valid informants to provide ratings of EO.

The present study provided theoretical explanations and used empirical evidence to elucidate how 360-degree feedback may benefit the field of entrepreneurship. In addition, recommendations for future research using 360-degree feedback in entrepreneurship research were offered and discussed. A sample research study on EO using 360-degree feedback was delineated.

The synthetic application and interaction of/between the internet, Internet of Things, cloud computing, big data, Industry 4.0 and other new patterns and new technologies shall breed future Web-based industrial operation system and social operation management patterns, manifesting as a crowd cyber eco-system composed of multiple interconnected intelligent agents (enterprises, individuals and governmental agencies) and its dynamic behaviors. This paper aims to explore the basic principles and laws of such a system and its behavior.

The authors propose the concepts of crowd science and engineering (CSE) and expound its main content, thus forming a research framework of theories and methodologies of crowd science.

CSE is expected to substantially promote the formation and development of crowd science and thus lay a foundation for the advancement of Web-based industrial operation system and social operation management patterns.

This paper is the first one to propose the concepts of CSE, which lights the beacon for the future research in this area.

With the rapid growth of the Internet of Things (IoT) market and requirement, low power wide area (LPWA) technologies have become popular. In various LPWA technologies, Narrow Band IoT (NB-IoT) and long range (LoRa) are two main leading competitive technologies. Compared with NB-IoT networks, which are mainly built and managed by mobile network operators, LoRa wide area networks (LoRaWAN) are mainly operated by private companies or organizations, which suggests two issues: trust of the private network operators and lack of network coverage. This study aims to propose a conceptual architecture design of a blockchain built-in solution for LoRaWAN network servers to solve these two issues for LoRaWAN IoT solution.

The study proposed modeling, model analysis and architecture design.

The proposed solution uses the blockchain technology to build an open, trusted, decentralized and tamper-proof system, which provides the indisputable mechanism to verify that the data of a transaction has existed at a specific time in the network.

To the best of our knowledge, this is the first work that integrates blockchain technology and LoRaWAN IoT technology.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

Fewer researchers have investigated the climatic and economic drivers of land-use change simultaneously and the interplay between drivers. This paper aims to investigate the nonlinear and interaction effects of price and climate variables on the rice acreage in high-latitude regions of China.

This study applies a multivariate adaptive regression spline to characterize the effects of price and climate expectations on rice acreage in high-latitude regions of China from 1992 to 2017. Then, yield expectation is added into the model to investigate the mechanism of climate effects on rice area allocation.

The results of importance assessment suggest that rice price, climate and total agricultural area play an important role in rice area allocation, and the importance of temperature is always higher than that of precipitation, especially for minimum temperature. Based on the estimated hinge functions and coefficients, it is found that total agricultural area has strong nonlinear and interaction effects with climate and price as forms of third-order interaction. However, the order of interaction terms reduces to second order after absorbing the expected yield. Additionally, the marginal effects of driven factors are calculated at different quantiles. The total area shows a positive and increasing marginal effect with the increase of total area. But the positive impact of price on the rice area can only be observed when price reached 50% or higher quantiles. Climate variables also show strong nonlinear marginal effects, and most climatic effects would disappear or be weakened once absorbing the expected rice yield. Expected yield is an efficient mechanism to explain the correlation between crop area and climate variables, but the impact of minimum temperature cannot be completely modeled by the yield expectation.

To the best of the authors’ knowledge, this is the first study to examine the nonlinear response of land-use change to climate and economic in high-latitude regions of China using the machine learning method.

This study aims to offer insights into a sounder understanding of tourist behavior and travel patterns by systematically identifying psychological manifestations reflected in the basic human value system in the pandemic-induced environment.

A large random sample (49,519 respondents from 29 European countries), generated from the core module Round 9 of the European Social Survey, was used. A post-COVID-19 psychological travel behavior model was constructed by using 12 variables within two opposing value structures (openness to change versus conservatism), shaping specific personalities.

Four types of tourists were identified by using K-means cluster analysis (risk-sensitive, risk-indifferent, risk-tolerant and risk-resistant). The risk-sensibility varied across the groups and was influenced by socio-demographic characteristics, economic status and even differed geographically among nations and traveling cultures.

First, data were collected before the pandemic and did not include information on tourism participation. Second, the model was fully driven by internal factors – motivation. Investigation of additional variables, especially those related to socialization aspects, and some external factors of influence on travel behaviors during and after the crisis, will provide more precise scientific reasoning.

The model was upgraded to some current constructs of salient short-term post-COVID-19 travel behavior embedded in the core principles of universal human values. By separating specific segments of tourists who appreciate personal safety and conformity, from those sharing the extensive need for self-direction and adventure, the suggested model presents a strong background for predicting flows in the post-COVID-19 era.

This paper aims to adapt and computerize the Trail Making Test (TMT) to support long-term self-assessment of cognitive abilities.

The authors propose a divide-and-combine (DAC) approach for generating different instances of TMT that can be used in repeated assessments with nearly no discernible practice effects. In the DAC approach, partial trails are generated separately in different layers and then combined to form a complete TMT trail.

The proposed approach was implemented in a computerized test application called iTMT. A pilot study was conducted to evaluate iTMT. The results show that the instances of TMT generated by the DAC approach had an adequate level of difficulty. iTMT also achieved a stronger construct validity, higher test–retest reliability and significantly reduced practice effects than existing computerized tests.

The preliminary results suggest that iTMT is suitable for long-term monitoring of cognitive abilities. By supporting self-assessment, iTMT also can help to crowdsource the assessment processes, which need to be administered by healthcare professionals conventionally, to the patients themselves.

The purpose of this paper is to examine the relationship between dividend policy and earnings quality of Vietnamese listed firms.

The sample includes firms listed on Vietnam stock exchange during the period between 2010 and 2016. Two measures of earnings quality are the annual firm-specific absolute value of residuals from Dechow and Dichev’s (2002) model and from Dechow and Dichev (2002) as modified by McNichols’s (2002) model. The firms’ dividend policy is captured by dividend paying status. This is a dummy variable that takes the value of 1 if the firm pays dividends and 0 otherwise. In addition, dividend yield and dividend payout ratio, which are continuous variables, are also used in this paper as alternative proxies for dividend policy.

Using panel data analysis, this paper documents that dividend payers have higher earnings quality than dividend non-payers. Dividends are an indicator of earnings quality. These findings are consistent with prior studies. After controlling for variables that may be related to earnings quality as well as for the year and industry fixed effects, this relation remains unchanged. In addition, this result is also robust after controlling for firm fixed effects.

This paper offers the empirical evidence on the relation between dividend policy and earnings quality in Vietnam, which is a frontier market.

Allocation of complex crowdsourcing tasks, which typically include heterogeneous attributes such as value, difficulty, skill required, effort required and deadline, is still a challenging open problem. In recent years, agent-based crowdsourcing approaches focusing on recommendations or incentives have emerged to dynamically match workers with diverse characteristics to tasks to achieve high collective productivity. However, existing approaches are mostly designed based on expert knowledge grounded in well-established theoretical frameworks. They often fail to leverage on user-generated data to capture the complex interaction of crowdsourcing participants’ behaviours. This paper aims to address this challenge.

The paper proposes a policy network plus reputation network (PNRN) approach which combines supervised learning and reinforcement learning to imitate human task allocation strategies which beat artificial intelligence strategies in this large-scale empirical study. The proposed approach incorporates a policy network for the selection of task allocation strategies and a reputation network for calculating the trends of worker reputation fluctuations. Then, by iteratively applying the policy network and reputation network, a multi-round allocation strategy is proposed.

PNRN has been trained and evaluated using a large-scale real human task allocation strategy data set derived from the Agile Manager game with close to 500,000 decision records from 1,144 players in over 9,000 game sessions. Extensive experiments demonstrate the validity and efficiency of computational complex crowdsourcing task allocation strategy learned from human participants.

The paper can give a better task allocation strategy in the crowdsourcing systems.

The parent-child relationship is important to the solidarity of families and the emotional well-being of family members. Since people are more dependent on their close social relationships as they age, understanding the quality of relationships between aged parents and their adult children is a critical topic. Previous research shows that this relationship is complicated with both kinship and ambivalence. However, there is little research on the causes of this complexity. This paper proposes a role model to explain this complexity by studying the leadership transition within a family as the child grows.

In this paper, we proposed a novel perception to understand this transition process and explain related problems based on the analysis of the leader-follower relationship between the parents and their children.

When a child is born, his/her parents become the leader of this family because of their abilities, responsibilities and the requirements of the infant. This leader-follower role structure will last a long time in this family. Decades later, when the parents become old and the child grows up, the inter-generational contracts within the family and the requirement of each members change. This transition weakens the foundation of the traditional leader-follower role structure within the family. If either the parent or the child does not want to accept their new roles, both of them will suffer and struggle in this relationship. This role conflict will cause ambivalence in the relationship between aged parents and their adult children.

Based on the quantitative study model provided in this paper, we can moderate the relationships between aged parents and their adult children. This effort is meaningful in enhancing the quality of life and emotional wellbeing for senior citizens.