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China's economic transition is essentially the process of China's institutional changes. During the changes, the appearance of institutional innovation is not regular; instead, it is intermittent and random. The purpose of this paper is to show that the fitful appearance of institutional innovation is the root of China's economic growth and fluctuations.

This paper constructs a real business cycle (RBC) model introducing the institutional factor expressed in the quantitative form under the dynamic stochastic general equilibrium (DSGE) framework by measuring China's institutional changes quantitatively.

By comparing the characteristics of the actual economic data with those of the simulated economic data, we find that this RBC model can explain 94.44%, 66.07%, 23.46%, 21.03% and 15.45% of the cyclical fluctuations in output, investment, labor, consumption and capital, respectively.

The impulse response analysis finds that the institutional shocks have a relatively long duration, lasting about 30 years, and decline slowly over time, while technological shocks decline relatively fast, lasting approximately ten years.

The purpose of this paper is to analyze the influence of different factors on forestry production, with an aim to explore the degree of connection between forestry economic growth and influencing factors such as forestry investment, labor input, afforestation area, scientific and technologies progress, and the reform of property-rights regimes.

According to the data of China Forestry Statistical Yearbook from 1978 to 2017, this paper uses the grey correlation analysis to observe and analyze the factors influencing China’s forestry economics growth.

The results show that capital investment demonstrates the largest impact on the forestry output value, followed by property system, afforestation area, labor input and technologies progress. The correlation coefficients of the above factors are 0.874451654,0.85827468,0.835138412,0.832985604 and 0.825747493. This means that forestry capital investment plays a major role in contributing to forest economic growth; forest property system also plays a positive role in the growth of forestry economy.

This paper uses continuous data collected during 1978‒2017, which are quite extensive as compared to data used in the existing research, considering the influencing factors are comprehensive, especially the impact of property right system reform on forestry economic growth.

This paper aims to examine the influence of family involvement in TMTs on product innovation efficiency and the contingent role of technological collaborations, combining insights from the resource-based view and the behavioral agency model.

This study empirically develops and tests the hypotheses using a longitudinal sample of 3,852 firm-year observations from Spanish manufacturing firms over the period 2006–2016.

The results reveal that family involvement in TMTs positively influences product innovation efficiency. The results also show that such positive effect is weakened as technological collaborations increase, and varies according to the partner type with whom the cooperation agreement is established. Specifically, the findings indicate that collaboration with suppliers appear to be the least detrimental for product innovation efficiency in family firms, followed by collaborations with customers and research organizations.

Family firms should consider appointing family members to their TMT to improve product innovation efficiency. Moreover, to enhance the effect of family management on product innovation efficiency, family managers should carefully select their technological partners.

This study is one of the first studies to theoretically explain and empirically demonstrate that family involvement in TMTs is a critical antecedent of product innovation efficiency and that technological collaborations moderate such link. Moreover, this study goes further in revealing that distinct types of partners have a differential moderating influence on the family involvement in TMTs-product innovation efficiency relationship. The results can be used to help managers and practitioners to boost innovation performance as well as to assist policymakers to design firm-level innovation policies to improve family firms' competitiveness.

This paper aims to test the hypothesis that the effect of production slowdown on labour demand can be muted by labour hoarding.

This study adopts a production function approach, using data from Malta, a small state in the EU.

The results confirm the hypothesis and indicate that firms are normally prepared to employ and dismiss more workers in the long run than in the short run.

This finding has important implications for developed countries, including that labour hoarding can be of certain relevance in times of economic slowdown as shocks are absorbed by internal flexibility.

The results of this study add on to the existing literature in two ways. First, this study compares two industries –manufacturing and financial services– for which the former sector received support to hoard labour after the financial turmoil of 2008. Consequently, the dominance of labour hoarding in manufacturing relative to financial services is uncovered and the effect of hoarding practices on labour demand is estimated. Second, Malta is an interesting case because it is one of the smallest economies in the world and faces a high degree of vulnerability because of constraints associated with small size and insularity. As a result, firms adopt policy-induced measures to minimise adjustment costs.

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.

Over time, technological intensity has been used as a proxy for innovation capability of firms in an industrial sector. However, not only firms belonging to the stratum of high technological intensity are able to innovate. Therefore, this study aims to explore a potential association between technological intensity and innovation capability in firms from different industrial sectors, using the Organization for Economic Cooperation and Development (OECD)’s classification and the components of innovation capability proposed by Zawislak et al. (2012, 2013).

The authors conducted an exploratory research with four case studies focusing on the innovation capability of Brazilian firms.

The results show that the four firms, each belonging to one stratum of technological intensity, have innovation capability, and the differences regarding this feature can be explained by the balance and development of all firms’ capabilities (technological, operational, managerial and transactional).

In the literature, studies that relate technological intensity and innovation capability are scarce. Therefore, the originality of this research is to relate these two concepts. The most important is that firms can be innovative regardless of their stratum of technological intensity, which shows the importance of other capabilities to ensure the innovation’s success.

The purpose of this paper is to measure the high-quality development level of China's marine economy and analyze corresponding spatial and temporal distribution characteristic.

Design and optimize the index system of high-quality development level of marine economy and use entropy and TOPSIS method for comprehensive evaluation.

The research finds that from 2017 to 2019, the high-quality development tendency of China's marine economy is on the rise, but the overall level is still low. The level of each subsystem has different distribution characteristics in different provinces and cities. Guangdong, Shandong and Shanghai have a high comprehensive level. According to the comprehensive level of high-quality development of marine economy, 11 coastal provinces are divided into three types: leading, general and backward.

This paper clarifies the temporal and spatial distribution law of high-quality development level of China's marine economy, providing basis for promoting comprehensive and coordinated improvement of coastal provinces and cities.

An indicator system for the high-quality development level of the marine economy has been established, including social development guarantee, marine economic foundation, marine science and technology drive and green marine sustainability.

The purpose of this paper is to explore the economic performance of Norwegian crop farms using a stochastic frontier analysis.

The analysis was based on a translog cost function and unbalanced farm-level panel data for 1991–2013 from 455 Norwegian farms specialized in crop production in eastern and central regions of Norway.

The results of the analysis show that the mean efficiency was about 78–81 percent. Farm management practices and socioeconomic factors were shown to significantly affect the economic performance of Norwegian crop farms.

Farmers are getting different types of support from the government and the study does not account for the different effects of different kinds of subsidy on cost efficiency. Different subsidies might have different effects on farm performance. To get more informative and useful results, it would be necessary to repeat the analysis with less aggregated data on subsidy payments.

One implication for farmers (and their advisers) is that many of them are less efficient than the estimated benchmark (best performing farms). Thus, those lagging behind the best performing farms need to look at the way they are operating and to seek out ways to save costs or increase crop production. Perhaps there are things for lagging farmers to learn from their more productive farming neighbors. For instance, those farmers not practicing crop rotation might be well advised to try that practice.

For both taxpayers and consumers, one implication is that the contributions they pay that go to subsidize farmers appear to bring some benefits in terms of more efficient production that, in turn, increase the supply of some foods so possibly making food prices more affordable.

Unlike previous performance studies in the literature, the authors estimated farm-level economic performance accounting for the contribution of both an important farm management practice and selected socioeconomic factors. Good farm management practices, captured through crop rotation, land tenure, government support and off-farm activities were found to have made a positive and statistically significant contribution to reducing the cost of production on crop-producing farms in the Central and Eastern regions of Norway.

The aim of this paper is to understand if service innovation (Helkkula et al., 2018), based on artificial intelligence (AI) systems, may guarantee healthcare service ecosystem (H-SES) well-being (Frow et al., 2019; Beirão et al., 2017), taking into account that many doubts relieved in terms of transparency may compromise the patients' perceived quality of health services provided through AI systems.

A literature review on service innovation, detected in terms of value co-creation, and service ecosystem, investigated in terms of well-being, is drawn. To analyze the implications of service innovation on a H-SES well-being, through the technology acceptance degree and predisposition to use by actors, a case study based on TAM-model 3 determinants as categories is carried out.

AI-based service innovation archetypes in healthcare may be considered as antecedents of the service ecosystem well-being conditions as long as they enable actors to co-create value. To make it possible, a patient-driven service innovation is necessary in order to mitigate the risks of its inactivity due to fears in terms of transparency.

Service innovation and service ecosystem well-being may be studied in an integrated way, with a multidisciplinary approach, and are linked by value co-creation, because only thanks a patient-driven service innovation is possible to foster service ecosystem well-being in healthcare.