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Because of advantages such as multi‐scale and multi‐direction, contourlet transform is better at treating a 2‐D image than wavelet transform and the Classified Hidden Markov Tree (CHMT) model is able to analyze statistical character of coefficients, which means they can be analyzed more efficiently and effectively. So in this paper, the purpose is to use contourlet transform and CHMT model to redevelop traditional set partitioning in hierarchical trees (SPIHT) code algorithm, and by using these two methods, hope to decrease the distortion and increase the quality.

In this paper, the algorithm is divided into two parts: code part and decode part. As all processes are operated in the contourlet domain, contourlet transform is finished at the beginning of the code part. SPIHT algorithm in the contourlet domain will code these contourlet coefficients. CHMT model will be built in decode part, it will optimize decoded coefficients by calculating their statistical relationship. The decoded image will be reconstructed.

The experiment proves that this algorithm is able to reduce the distortion under the premise of not affect compression rate, meanwhile peak signal‐to‐noise ratio value is improved compared with traditional methods. Furthermore, the visual effect of the image derived from the algorithm is superior to that derived by traditional methods.

CHMT model in contourlet domain used in image code is original. As an improved code algorithm, the method is more powerful; its use could decrease the distortion of decoded images invaluable in the fields of military, medical image analysis, deep space detection and so on.

Given that women around the world face more exclusion in terms of limited access to economic and innovation activities than men do, it is understandable that some female-led start-ups in weak institutional environments engage in bribery to help reduce the difficulties they encounter in the face of intense business competition. However, the link between bribery and product innovation performance is unclear. The purpose of this study is to investigate the relationship between bribery and product innovation performance for female-led start-ups, as well as the roles of institutional support and self-control in this link.

This empirical study evaluates survey data from female-led manufacturing start-ups in China's Yangtze River Delta region to investigate the relationship between bribery and product innovation performance.

This research shows that bribery has an inverted U-shaped impact on product innovation performance in female-led manufacturing start-ups, meaning that the product innovation performance of these firms initially increases but then decreases as the bribery intensity (i.e. the frequency and amount of bribes) increases. The authors also focus on the roles of institutional support and self-control in this link, where the authors find that this relationship is steeper for firms with strong institutional support, as well as for individual female entrepreneurs who have high levels of self-control.

The findings of this study indicate that policymakers should undertake efforts to improve institutional quality (e.g. increasing clarity around decisions, providing more institutional support, etc.) and to guide female entrepreneurs to cultivate higher levels of self-control, as such efforts would reduce the appeal of, and the opportunity for, bribery.

To date, very few studies focus specifically on female-led enterprises in the field of bribery research. The research findings presented here on the effect of bribery in female-led start-ups on firm product innovation performance are useful to researchers, policymakers and businesspeople, as they provide a better understanding of bribery in female-led start-ups in China, which can also be extrapolated to encompass other transition economy contexts.

In this paper, we study a partially linear dynamic panel data model with fixed effects, where either exogenous or endogenous variables or both enter the linear part, and the lagged-dependent variable together with some other exogenous variables enter the nonparametric part. Two types of estimation methods are proposed for the first-differenced model. One is composed of a semiparametric GMM estimator for the finite-dimensional parameter θ and a local polynomial estimator for the infinite-dimensional parameter m based on the empirical solutions to Fredholm integral equations of the second kind, and the other is a sieve IV estimate of the parametric and nonparametric components jointly. We study the asymptotic properties for these two types of estimates when the number of individuals N tends to ∞ and the time period T is fixed. We also propose a specification test for the linearity of the nonparametric component based on a weighted square distance between the parametric estimate under the linear restriction and the semiparametric estimate under the alternative. Monte Carlo simulations suggest that the proposed estimators and tests perform well in finite samples. We apply the model to study the relationship between intellectual property right (IPR) protection and economic growth, and find that IPR has a non-linear positive effect on the economic growth rate.

The global business environment has brought about great innovation according to the advent of the fourth industrial revolution era. Most of the enterprises are focusing on adapting to the era of the fourth industrial revolution and trying to find appropriate strategies. Competitiveness among enterprises is changing fiercely. Such environments are threatening to the sustainability of enterprises. In this regard, it is a key issue that how enterprises can be sustainable and gain competitive advantage. Based on this background, this study emphasized the importance of environmental involvement. Enterprise can improve its image through environmental involvement. Since enterprise image is a variable that directly impacts enterprise growth and performance, it promotes the sustainability of the enterprise. Therefore, this study aims to explore the improvement factors of environmental immersion and verified its influence.

This study focused on creating shared value as a factor to improve environmental involvement. It is divided into three components, which are economic values, social values and cooperative values, respectively. The role of these three factors in enhancing environmental involvement was clearly identified and the process of enhancing enterprise image was verified.

The mediating effect of environmental involvement on the relationship between creative shared values (economic values, social values and cooperative values) and enterprise image was demonstrated.

This study emphasized the importance of environmental immersion in the era of the fourth industrial revolution and provided a way to improve enterprise image, which is directly related to the sustainability of the enterprise.

How to improve the resilience of service firms in the crisis, such as the COVID-19 epidemic, to maintain a sustainable competitive advantage becomes a growing concern worldwide. Digital platform capability (DPC) provides a series of opportunities and advantages for service firms to shape resilience in the crisis. This study aims to clarify the effect and mechanism of DPC on service firms’ resilience, and provides a new mediator (strategic learning [SL]), as well as two boundary conditions (legal inefficiency [LIE] and legal incompleteness [LIC]).

Questionnaires were used to obtain firm data, and executives answered these key questions. Data from 293 service firms during the COVID-19 period were used for hypothesis testing.

DPC was positively related to the adaptive capacity (AC) and planning capacity (PC) of service firms. SL mediated the positive effect of DPC on the AC and PC of service firms. The positive effect between DPC and SL was weakened when LIE and LIC were high.

This study suggests that it is a very desirable measure to improve DPC to gain organizational resilience (OR) in the crisis. In addition, a SL process in the crisis is crucial, because service firms need to absorb key strategic information from digital platforms to cope with uncertainty. The services firms need to realize that the benefits of DPC will be weakened in the dysfunctional institutional environment of LIE and LIC.

To the best of the authors’ knowledge, this study is the first to link the DPC with the resilience of service firms, and provides a new explanation mechanism and some boundary conditions for this important relationship. Furthermore, this study takes a step forward, because these efforts respond to the widespread call of the literature on digitalization and OR, and provide new insights for understanding digital resilience.

As of December 2021, WeChat had more than 1.2 billion active users worldwide, making it the most active online social media in mainland China. The term social commerce is used to describe new online sales through a mix of social networks and/or peer-to-peer communication or marketing strategies in terms of allowing consumers to satisfy their shopping behaviour through online social media. Thus, given the numerous active users, the development of online social media and social commerce on WeChat is a critical issue of internet research.

This empirical study takes WeChat as the online social media research object. Questionnaires for WeChat users in China were designed and distributed. All items are designed as nominal and ordinal scales (not Likert scale). The obtained data was put into a relational database (N = 2,342), and different meaningful patterns and rules were examined through data mining analytics, including clustering analysis and association rules, to explore the role of WeChat in the development of online social media and social commerce.

Practical implications are presented according to the research findings of meaningful patterns and rules. In addition, alternatives to WeChat in terms of further development are also proposed according to the investigation findings of WeChat users’ behaviour and preferences in China.

This study concludes that online social media, such as WeChat, will be able to transcend the current development pattern of most online social media and make good use of investigating users’ behaviour and preferences, not only to stimulate the interaction of users in the social network, but also to create social commerce value in social sciences.

To reduce energy consumption, the time needed of drying, and the loss of ß-carotene content, and ascorbic acid content, response surface methodology (RSM) was employed for optimization.

To reduce energy consumption, the time needed of drying, and the loss of ß-carotene content, and ascorbic acid content, response surface methodology (RSM) was employed for optimization.

The results show that the optimum solar-assisted heat pump drying (SAHPD) conditions for drying pumpkin slice were: drying temperature of 67.40 °C, loading density of 1.05 kg/m³, and material thickness of 4 mm. Under these conditions, slice of pumpkin were dried in 440.637 min, where the unit energy consumption, ascorbic acid content, and ß-carotene content were 16.737 kJ/g, 25.682 mg/ (100–g dried sample), and 10.202 mg/g, respectively. The structure of the samples dried using the optimized SAHPD method exhibited a more complete cell morphology than those dried using heat pump drying when examined using scanning electronic microscopy.

This suggests that the optimized SAHPD conditions used in this study are important for production and processing.