Zhejiang University of Finance and Economics

We conducted preregistered replications of 28 classic and contemporary published findings, with protocols that were peer reviewed in advance, to examine variation in effect magnitudes across samples and settings. Each protocol was administered to approximately half of 125 samples that comprised 15,305 participants from 36 countries and territories. Using the conventional criterion of statistical significance ( p < .05), we found that 15 (54%) of the replications provided evidence of a statistically significant effect in the same direction as the original finding. With a strict significance criterion ( p < .0001), 14 (50%) of the replications still provided such evidence, a reflection of the extremely high-powered design. Seven (25%) of the replications yielded effect sizes larger than the original ones, and 21 (75%) yielded effect sizes smaller than the original ones. The median comparable Cohen’s ds were 0.60 for the original findings and 0.15 for the replications. The effect sizes were small (< 0.20) in 16 of the replications (57%), and 9 effects (32%) were in the direction opposite the direction of the original effect. Across settings, the Q statistic indicated significant heterogeneity in 11 (39%) of the replication effects, and most of those were among the findings with the largest overall effect sizes; only 1 effect that was near zero in the aggregate showed significant heterogeneity according to this measure. Only 1 effect had a tau value greater than .20, an indication of moderate heterogeneity. Eight others had tau values near or slightly above .10, an indication of slight heterogeneity. Moderation tests indicated that very little heterogeneity was attributable to the order in which the tasks were performed or whether the tasks were administered in lab versus online. Exploratory comparisons revealed little heterogeneity between Western, educated, industrialized, rich, and democratic (WEIRD) cultures and less WEIRD cultures (i.e., cultures with relatively high and low WEIRDness scores, respectively). Cumulatively, variability in the observed effect sizes was attributable more to the effect being studied than to the sample or setting in which it was studied.

Family business researchers have devoted substantial attention to comparing family firms with nonfamily firms. Many of these comparisons rely on dichotomous variables, which implicitly treat family firms as homogeneous entities. However, recent studies have started to use moderators and mediators as well as continuous measures of family involvement in recognition of the heterogeneity of family firms. The articles and commentaries in this special issue contribute to a better understanding of that heterogeneity by examining how vision and goals, as well as the discretion engendered by family control, influence the innovation, internationalization, succession, professionalization, and proactive stakeholder engagement of family enterprises.

We add to the emerging literature on empirical asset pricing in the Chinese stock market by building and analyzing a comprehensive set of return prediction factors using various machine learning algorithms. Contrasting previous studies for the US market, liquidity emerges as the most important predictor, leading us to closely examine the impact of transaction costs. The retail investors’ dominating presence positively affects short-term predictability, particularly for small stocks. Another feature that distinguishes the Chinese market from the US market is the high predictability of large stocks and state-owned enterprises over longer horizons. The out-of-sample performance remains economically significant after transaction costs.

China has experienced the most serious habitat degradation, especially in fast-growing metropolis cities. Although increasing attentions have been brought to this issue, we still lack the understanding of the quantitative impacts of urbanization and landscape pattern on habitats. In this study, we used the “Integrated Valuation of Environmental Services and Trade-off” (InVEST) model to evaluate the habitat quality in Hangzhou city. We further employed spatial auto-correlation to analyze its spatiotemporal pattern variation characteristics. Finally, the ordinary least squares (OLS) and geographically weighted regression (GWR) models were used to explore the impacts of urbanization and landscape pattern change on habitat quality. The results show that the habitat quality index of Hangzhou decreased from 0.608 to 0.577 during 2004–2015, and these areas mainly located around the suburb decreased significantly. The spatial distribution of habitat quality showed significantly positive spatial auto-correlation, and the overall spatial auto-correlation degree of the habitat quality increased during this time. Rapid urbanization has significant negative effects on habitat quality in various areas, while the magnitude and direction of the impacts of landscape pattern on habitat quality differed in time and space. These results provide decision-making criteria for formulating differential urban development policies and landscape management measures for urban ecological sustainability.

This paper studies how a manufacturer should engage with a platform retailer and a traditional reseller. Our work is motivated by the emergence of increasingly powerful retail platforms in China’s consumer electronics and appliances markets. The manufacturer pays a slotting fee and a portion of its sales revenue to the platform retailer in exchange for the opportunity to manage its own space within the retailer’s store. The manufacturer can also sell its product to a traditional reseller thereby earning its wholesale price. We first formulate a Stackelberg game where the platform retailer leads by setting the revenue‐sharing rate while the manufacturer follows by choosing to sell through one or both channels. We derive the equilibrium channel and characterize each party’s associated sales quantities, prices, and profits. After confirming, it is always beneficial for the platform retailer to determine the slotting fee and revenue‐sharing rate simultaneously, we then formulate two bargaining models between the manufacturer and the platform retailer. In the first model, they can negotiate just the revenue‐sharing rate and in the second they negotiate both the revenue‐sharing rate and the slotting fee. In the second model, a win‐win result for the manufacturer and platform retailer is possible. We find that the slotting fee is neither always beneficial to the platform retailer nor always harmful to the manufacturer; it depends on the demand substitution effect between the two retail channels.

In this paper, we empirically investigate whether trade liberalization affects markup dispersion, a potential source of resource misallocation. The identification uses China's WTO accession at the end of 2001. We show that trade liberalization reduces markup dispersion within a narrowly defined industry. We also examine both price and cost responses to trade liberalization, as well as heterogeneous effects across firms and across locations. Our study contributes to the literature by identifying another potential channel through which free trade benefits a nation. (JEL F13, L11, O14, O19, P23, P31, P33)

This paper examines the role played by internal control and its five components (i.e. control environment, risk assessment, control activities, information and communication, and monitoring) in alleviating future stock price crash risk. Using a unique dataset from China, we find evidence that internal control is negatively associated with future stock price crash risk. Specifically, control environment, information and communication, and monitoring are significantly and negatively associated with future stock price crash risk. Moreover, the negative association between internal control and crash risk is significantly more pronounced in firms with weak internal and external governance (i.e. audited by non-Big 4 auditors, located in provinces with low market development, and less conservative in accounting) and with poor ability to mitigate impacts of extreme negative events (i.e. non-state-owned enterprises). Our study highlights the delicate role of internal control as a mechanism in preventing crash of stock price.

Purpose Artificial intelligence (AI) technology has revolutionized customers' interactive marketing experience. Although there have been a substantial number of studies exploring the application of AI in interactive marketing, personalization as an important concept remains underexplored in AI marketing research and practices. This study aims to introduce the concept of AI-enabled personalization (AIP), understand the applications of AIP throughout the customer journey and draw up a future research agenda for AIP. Design/methodology/approach Drawing upon Lemon and Verhoef's customer journey, the authors explore relevant literature and industry observations on AIP applications in interactive marketing. The authors identify the dilemmas of AIP practices in different stages of customer journeys and make important managerial recommendations in response to such dilemmas. Findings AIP manifests itself as personalized profiling, navigation, nudges and retention in the five stages of the customer journey. In response to the dilemmas throughout the customer journey, the authors developed a series of managerial recommendations. The paper is concluded by highlighting the future research directions of AIP, from the perspectives of conceptualization, contextualization, application, implication and consumer interactions. Research limitations/implications New conceptual ideas are presented in respect of how to harness AIP in the interactive marketing field. This study highlights the tensions in personalization research in the digital age and sets future research agenda. Practical implications This paper reveals the dilemmas in the practices of personalization marketing and proposes managerial implications to address such dilemmas from both the managerial and technological perspectives. Originality/value This is one of the first research papers dedicated to the application of AI in interactive marketing through the lenses of personalization. This paper pushes the boundaries of AI research in the marketing field. Drawing upon AIP research and managerial issues, the authors specify the AI–customer interactions along the touch points in the customer journey in order to inform and inspire future AIP research and practices.

Developing methods of measuring multidimensional poverty and improving the accuracy of poverty identification have been hot topics in international poverty research for decades. They are also key issues for improving the quality and effectiveness of rural poverty reduction programs in China. So far, selection and integration of poverty indicators remains the main difficult for measurement of multidimensional poverty. Guided by the sustainable livelihoods framework developed in the UK by the Department for International Development (DFID), an index system and an integration method for geographical identification of multidimensional poverty were established, and they were further used to carry out a county-level identification of poverty in rural China. Additionally, comparisons were made of the identification results with counties having single-dimension income poverty in rural areas and poor counties designated by the Chinese central government. The results showed that a total of 655 counties, with 141 million rural residents, were identified as multidimensionally poor. They are concentrated and conjointly distributed geographically, and evil natural conditions are their common features. In comparison to the income poor and the designated poor counties, the multidimensionally poor counties were not only worse in single-dimensional and composite scores, but also having multiple disadvantages and deprivations. By identifying the disadvantage and deprived dimensions, the measurement of multidimensional poverty should be very helpful for each county to work out and implement antipoverty programs accordingly, and it would make contribution to improve the sustainability of poverty reduction. Hopefully, this research may also shed light on multidimensional poverty measurement for other developing countries. (C) 2016 Elsevier Ltd. All rights reserved.

Constructed wetland systems have been used for treating a variety of household and industrial wastewater; they are a wastewater treatment technology that has high economic efficiency and environmental effectiveness, especially for sewage treatment in rural areas. Medium filler plays an important role in wetland sewage treatment processes. By carrying out a problem analysis of the ineffective operation and treatment of traditional wetlands, this paper designs different constructed wetland fillers to treat rural household sewage. Using the same plants, this paper chooses four different fillers, namely maifanite, steel slag, bamboo charcoal and limestone as substrates to build constructed wetland systems, and studies rural household sewage treatment in order to examine their effects on the degradation of pollutants. The results show the removal efficiencies obtain good effect. The theoretical maximum adsorption capacities of all these media are ordered as: maifanite > steel slag > bamboo charcoal > limestone. The effluent water quality meets the first class A standard of the “Discharge standard of pollutants for municipal wastewater treatment plant” (GB18918-2002). The selection of medium has an important significance for the operating results of constructed wetland sewage treatment systems.

As purchase power and consumption knowledge increase, consumers gradually demand safer and healthier products. In addition, consumers focus greater attention on organic food. This study investigates the relationship between environmental consciousness and organic food purchase intention with the mediating roles of perceived food quality and price sensitivity. The objective is to shed new light on our understanding of consumers' perceptions and behavioral intentions toward organic food. Using sample data of 518 consumers in different food retailers in China, empirical results show that environmental consciousness has a positive impact on organic food purchase intention. Perceived food quality has a mediating effect on the link between environmental consciousness and organic food purchase intention. Price sensitivity moderates the relationship between perceived food quality and organic food purchase intention. Furthermore, price sensitivity moderates the indirect effect of environmental consciousness on organic food purchase intention through perceived food quality.

Sustainable development is a powerful impetus to achieve the coordination between economic advancement and environmental protection. Therefore, the promotion and adoption of green consumption has attracted increasing attention from academics. As an important tool for multivariate data analyses, structural equation modelling has been extensively used in purchase intention for green products. However, most previous research has recognized green products as a general class when studying their purchase intention, which focused little attention on comparing purchase intention for different kinds of green products. This study extends and tests the theory of planned behavior (TPB) and includes another cognitive construct, that is, environmental concern, to explore purchase intention for different kinds of green products. First, the effect of TPB constructs was examined on purchase intention for utilitarian green products and hedonic green products. Second, a cognitive factor, that is, environmental concern, was used to test its different effects on these two kinds of green products. Third, the indirect effect of environmental concern on purchase intention was measured for these two kinds of green products. The study showed that extended TPB constructs, that is, attitude, perceived behavior control, and environmental concern positively and significantly affected purchase intention for both utilitarian green products and hedonic green products, while subjective norm only significantly and positively affected purchase intention for utilitarian green products. Moreover, the cognitive factor, that is, environmental concern, had a higher effect on purchase intention for utilitarian green products than purchase intention for hedonic green products, and it also had a similar indirect effect on both kinds of green products. This study provides an insight to policymakers, entrepreneurs, and marketers into how to increase purchase intention for different kinds of green products.

Bibliometric analysis is effective for evaluating the merits of a given discipline. This study provides an analysis of collaboration evolution in analytic hierarchy process (AHP) research from 1982 to 2018. As an important developed approach of AHP, analytic network process (ANP) is also considered in this review. 9859 publications are harvested from Web of Science to conduct this bibliometric analysis. Country and institution are the two primary objectives to investigate the collaboration pattern of the 9859 publications. The most prolific countries and institutions are identified based on bibliometric indicators, and the collaboration relationships between connected countries or institutions are explored based on science mapping techniques. Further, a dynamic analysis is provided to investigate the collaboration evolution of AHP publications at the levels of country and institution. This study offers a new topic on the overview research of AHP publications, and could help in developing the collaboration evolution analysis in the AHP field.

Business intelligence (BI) technologies have received much attention from both academics and practitioners, and the emerging field of business analytics (BA) is beginning to generate academic research. However, the impact of BI and the relative importance of BA on corporate performance management (CPM) have not yet been investigated. To address this gap, we modeled a CPM framework based on the Integrative model of IT business value and on information processing theory. Data were collected from a global survey of senior managers in 337 companies. Findings suggest that the more effective the BI implementation, the more effective the CPM-related planning and analytic practices. BI effectiveness is strongly related to BA, planning and to measurement. In contrast, BA effectiveness is strongly related to planning but less so to measurement. The study suggests that although both BI and BA contribute to corporate management practices, the information needs are different based on the level of uncertainty versus ambiguity characteristic of the management practice.

Abstract This paper studies the impact of economic policy uncertainty on stock price crash risk using data from China. We develop a new index to measure Chinese economic policy uncertainty and find that economic policy uncertainty has a remarkable positive effect on stock price crash risk. However, the effect reverses later. The results also indicate that the positive effect of economic policy uncertainty on stock price crash risk is more prominent for state‐owned enterprises. Moreover, this effect is more prominent for firms with higher information asymmetry and firms with greater disagreement among investors, indicating that economic policy uncertainty affects crash risk through two mechanisms: managers’ concealment of bad news and investors’ heterogeneous beliefs.

Rapid urbanization intensifies land-use transition by shrinking cropland and increasing the land development of land in China, which affects the ecosystem services value (ESV) and causes environmental degradation. To improve the quality of the ecological environment, China has launched a strategy for the construction of an ecological civilization and attempted to build an ecological compensation mechanism. In this study, combining linear optimization model with the conversion of land use and its effects at small regional extent (CLUE-S) model to optimize and quantitatively to simulate land-use change based on embedding to maximize the ESV for land use planning in 2025 in Jiangsu province, a Chinese province that has experienced the greatest land-use transition and ESV loss in China. The results showed that a total loss of 5.76 × 1010 yuan.yr−1 ESV from 2000 to 2015 was due to the conversion of a total of 17.76% of the land in Jiangsu. However, we predicted that the total area of land use will increase by 0.4% in 2025 compared to that in 2015, which will lead to an increase of the ESV by 3.79 × 1010 yuan.yr−1. Cropland and grassland will decrease the most, while woodland, water area and wetland will increase. Moreover, our spatial simulation showed that the regions around the Taihu Lake, the boundary between central and northern Jiangsu, and the inland region of northern Jiangsu will experience great ESV change caused by land-use transition in 2025. We also discussed land use and ecological protection policies. Our simulation results provide a potentially effective guide for implementing ecological compensation mechanisms among sub-regions in Jiangsu province.

BACKGROUND: Digital health is growing at a rapid pace, and digital health literacy has attracted increasing attention from the academic community. OBJECTIVE: The purposes of this study are to conduct a systematic bibliometric analysis on the field of digital health literacy and to understand the research context and trends in this field. METHODS: Methods: A total of 1955 scientific publications were collected from the Web of Science core collection. Institutional co-operation, journal co-citation, theme bursting, keyword co-occurrence, author co-operation, author co-citation, literature co-citation, and references in the field of digital health literacy were analyzed using the VOSviewer and CiteSpace knowledge mapping tools. RESULTS: The results demonstrate that the United States has the highest number of publications and citations in this field. The University of California System was first in terms of institutional contributions. The Journal of Medical Internet Research led in the number of publications, citations, and co-citations. Research areas of highly cited articles in the field of digital health literacy mainly include the definition and scale of health literacy, health literacy and health outcomes, health literacy and the digital divide, and the influencing factors of health literacy. CONCLUSIONS: We summarized research progress in the field of digital health literacy and reveal the context, trends, and trending topics of digital health literacy research through statistical analysis and network visualization. We found that digital health literacy has a significant potential to improve health outcomes, bridge the digital divide, and reduce health inequalities. Our work can serve as a fundamental reference and directional guide for future research in this field.

The rapid upward shift in ethanol demand has raised concerns about ethanol’s impact on the price level and volatility of agricultural commodities. The popular press attributes much of this volatility in commodity prices to a price bubble in ethanol fuel and recent deflation. Market economics predicts not only a softening of demand to high commodity prices but also a positive supply response. This volatility in ethanol and commodity prices are investigated using cointegration, vector error corrections (VECM), and multivariate generalized autoregressive conditional heteroskedascity (MGARCH) models. In terms of derived demand theory, results support ethanol and oil demands as derived demands from vehicle-fuel production. Gasoline prices directly influence the prices of ethanol and oil. However, of greater significance for the fuel versus food security issue, results support the effect of agricultural commodity prices as market signals which restore commodity markets to their equilibriums after a demand or supply event (shock). Such shocks may in the short-run increase agricultural commodity prices, but decentralized freely operating markets will mitigate the persistence of these shocks. Results indicate in recent years there are no long-run relations among fuel (ethanol, oil and gasoline) prices and agricultural commodity (corn and soybean) prices.

Non-English languages are widely used, but their roles in scholarly communication are relatively under-explored. By using Web of Science's Science Citation Index Expanded (SCIE, 1900–2015), Social Sciences Citation Index (SSCI, 1900–2015), and Arts and Humanities Citation Index (A&HCI, 1975–2015), this study probes the patterns and dynamics of non-English papers by year, citation index, and discipline using bibliometric analysis. The analyses show that English is increasingly being used as the dominating language from natural sciences and social sciences to arts and humanities. Around 97% of the papers in SCIE, 95% of the papers in SSCI, and 73% of the papers in A&HCI during the past decade were in English. However, other languages such as German and French were also used as important academic languages in sciences and social sciences during the first half of the 20th century, 1970s, and 1980s. Unlike natural science and social science disciplines, non-English papers have consistently played important role in arts and humanities disciplines from the beginning of 1975. Although the shares of non-English papers in SCIE and SSCI databases have been limited during the past decade, a large number of non-English papers can be found in some applied disciplines of sciences and social sciences.

The pandemic of COVID-19 has brought great challenges to the development of the world economy and has an unprecedented and inevitable impact on the logistics industry connecting various economic activities. In the context of the gradual alleviation of the COVID-19 outbreak in China, we observed five impacts on China's logistics industry, which are sharp drop in logistics demand, shortage of transportation capacity, disruption of logistics network, change of service mode, and increase in operating costs and number of loss-making enterprises. When this invited paper was written, the outbreak in China has been effectively under controlled. In the post-COVID-19 era, under the three driving forces (i.e. the market, technology and policy), China's logistics industry will develop rapidly, leading to significant changes in five aspects: logistics demand, logistics supply, logistics infrastructure, logistics informatisation, and logistics industry development. The authors of this invited paper have been actively involved in the development of China's logistics industry in various capacities, governmental and non-governmental as well as in academia, and participated in a range of studies on the development trends, plans and policies of China's logistics industry. The authors have a profound understanding of the latest situation in the China's logistics industry and government initiatives.