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The success of social commerce group-buying information system (IS) is not a simple accumulation of functions, but a complex process of system integration that makes it difficult to design a high-quality website to improve the conversion rate of users has become a top priority for online companies. The purpose of this study is to further improve the IS success model to adapt to the new research scenarios and explore the boundary conditions between different satisfaction and repurchase intention.

In this study, the users who have used the group-buying website quality for social commerce in the last 6 months are the objects of this study. Finally, 436 valid data were collected by questionnaire survey and analyzed by Smart PLS.

The results indicate that the four dimensions of website quality enhance consumers' economic satisfaction and social satisfaction, except that the path of system quality and social satisfaction is not significant. Economic satisfaction and social satisfaction also have a significant positive effect on repurchase intentions. Besides, the interactive effect of customer involvement and economic satisfaction has no significant impact on repurchase intention, but customer involvement plays a moderate role in the path of social satisfaction on repurchase intention.

n order to make the IS success model better evaluate the characteristics of social commerce sites comprehensively, this present research introduces the measurement construct of interaction quality. Moreover, this study examines the effect of mechanism of economic satisfaction and social satisfaction on repurchase intention from the perspective of practical benefit and psychology. Finally, the boundary conditions of the effect of satisfaction on repurchase intention are explored.

Building on social media and destination brand-related literature, this study aims to explore World Heritage Sites’ (WHSs) brand diffusion and formation process from long-term and short-term perspectives, which includes brand diffusion, user-generated content (UGC), opinion leaders and brand events’ impact.

This study uses a mixed-method including text mining, keyword analysis and social network analysis to explore the brand formation process of four popular WHSs in Beijing, namely, the Palace Museum, Great Wall, Summer Palace and Temple of Heaven and more than 10,000,000 users’ data on Sina Weibo has been implemented to uncover the underlying social media branding mechanism.

The results show that the number of postings keeps in a stable range in most months, but, in general, there are no common rules for changing trends among the four WHSs; long-term high-frequency keywords related to history and culture account for a higher percentage; different kinds of accounts have varying impacts on information diffusion, in which media accounts lead to a bigger influence. However, more followers do not necessarily mean more interactions and most of the interaction ratio is much lower than 0.01000; brand events facilitate brand dissemination and have an impact on the creation of UGC.

This study is valuable for destination marketers to deeper understand brand diffusion and formation and provides valuable insights for developing effective destination marketing strategies.

Unlike previous studies that only concern a few parts of destination brand formation via social media (e.g. brand diffusion, brand events or opinion leaders’ impact), this study takes a more comprehensive perspective by systematically analyzing the brand formation process of WHSs on social media. By considering both long-term diffusion and short-term representative events, this study provides a more holistic understanding of the branding mechanism.

This study applies parasocial relationship theory to identify the role of broadcaster characteristics in the highly interactive business setting of live streaming commerce.

A total of 401 online questionnaires were distributed to individuals with live streaming showroom shopping experience, and SmartPLS software was used to analyse the data and test the hypotheses.

Broadcasters' characteristics are positively associated with viewers' parasocial relationships, thus further enhancing viewers' attitudinal and behavioural loyalty towards that broadcaster's streams. Parasocial relationships mediate the effects of most broadcaster characteristics (except for expertise) on attitudinal and behavioural loyalty. In addition, parasocial relationships have a stronger positive effect on viewer behaviours for hedonic products and under high match-up.

The broadcaster is a key indicator of the success of live streaming commerce. This study establishes a well-organized framework to understand how broadcaster characteristics influence viewer loyalty towards that broadcasters' streams based on parasocial relationship theory.

This paper explores the nexus between lean operations, eco-product innovativeness, social performance, green performance and business performance. Both direct and indirect effects are tested among the variables under consideration in this study.

Data is garnered from 166 Ghanaian small and medium-sized enterprise (SME) manufacturers. All hypothesized relationships are tested using partial least square-structural equation modeling.

The results suggest that lean operations has a significant positive effect on eco-product innovativeness, social performance, green performance and business performance. The results further indicate that eco-product innovativeness significantly influences green performance and social performance, but does not significantly influence business performance. The mediation procedure performed shows that eco-product innovativeness plays a complementary partial mediation role between lean operations, social performance, green performance and business performance.

The study provides enough evidence that informs managers that the application of lean operations should be a necessity instead of an afterthought when pursuing their sustainable performance targets. The study specifically enlightens Ghanaian managers and those in similar environs to substantially invest in lean operations to achieve eco-product innovativeness and contribute to the survival of the manufacturing sector.

In addition to expanding lean operations and environmental management literature, the study happens to be among the scant studies that has verified the direct and indirect effects between lean operations, eco-product innovativeness, social, green and business performances.

The aim of this study is to explore the link between green manufacturing practices, operational competitiveness, firm reputation and sustainable performance dimensions as well as advance a mediation approach.

The study resorted to structured questionnaire to collect data from 158 manufacturing firms from different industries, and partial least square–structural equation modelling is used to test all hypothesized relationships.

The results indicate that green manufacturing has a positive significant impact on social, economic and environmental performance. However, firm reputation and operational competitiveness were found not to significantly influence economic performance. The mediation analysis also showed that operational competitiveness, firm reputation and environmental performance play no mediation role between green manufacturing and economic performance. Furthermore, social performance is found to mediate the relationship between green manufacturing and economic performance.

The study did not consider any moderator variables. Also, the universal applicability and generalizability are somewhat a problem since data was mainly collected from Ghana, an emerging country.

The results provide managers with reasonable evidence to proactively implement and invest in green manufacturing practices because such practices will not only have a positive impact on their sustainable performance dimensions but further enhance operational competitiveness and provide firms with superior reputation.

The study provides significant findings that contribute to and expand the literature on green manufacturing, and it is among the relatively few studies that has investigated the link between green manufacturing, sustainable performance dimensions, firm reputation and operational competitiveness, especially from a mediation analysis perspective.

This study aims to investigate the interactions between lean production, internal green practices, green product innovation and sustainable performance metrics. The study further looks at the mediation effect of internal green practices and green product innovation between lean production and sustainable performance dimensions.

The questionnaire was used to glean data from 209 manufacturing firms. All the hypothesized relationships were processed by using partial least square-structural equation modelling.

The results suggest that lean production significantly leads to the implementation of internal green practices and the production of quality products with eco-oriented features that meet customers’ needs. Further, while lean production and internal green practices were found to significantly influence sustainability performance, green product innovation significantly influences only financial performance. Besides, the mediation analysis shows that internal green practices mediate the relationship between lean production and sustainable performance dimensions but green product innovation mediates the relationship between lean production and financial performance only.

The study is limited to firms from Ghana, a developing country; hence, the results cannot be imported to reflect other geographical contexts.

The results of the study provide sufficient justifications for managers, (especially Ghanaian managers and those from other similar environs) to commit their financial resources towards implementing lean production and internal green practices so as to achieve sustainability excellence.

This study magnifies and provides new insight on lean and green literature by developing a comprehensive research model that concurrently tests the direct and indirect effects between lean production, internal green practices, green product innovation and sustainable performance dimensions.

This study aims to investigate the interrelationships between lean production, green technology adoption, green product innovation, social sustainability performance and green competitiveness. The study further investigates the mediation roles of green technology adoption and green product innovation between lean production systems, social sustainability performance and green competitiveness.

The quantitative research approach is used for the study. Data for the study is garnered from 197 managers of manufacturing firms in Ghana via a self-administered questionnaire. Structural equation modeling, specifically partial least square is applied as the methodological tool to test all hypotheses.

Results of the study suggest that lean production systems have a significant positive impact on green technology adoption, green product innovation and green competitiveness. However, lean production systems are found to have an insignificant impact on social performance. The results further confirm the mediation roles of both green technology adoption and green product innovation between lean production systems, social sustainability performance and green competitiveness; thus indicating that lean production systems create an efficient condition for firms to adopt green technologies and produce innovative green-based products to leverage superior social sustainability performance and green competitiveness.

This study proposes and develops a comprehensive research model that is supported by the natural resource-based view theory to investigate the link between lean production systems, green technology adoption, green product innovation, social sustainability performance and green competitiveness from an emergent country perspective.

This study explores the interplay between lean management and circular production systems and their implications on zero-waste performance, green value competitiveness and social reputation.

Questionnaire-based survey methodology is used to obtain empirical data from Ghanaian manufacturing SMEs. A multivariate statistical technique, specifically partial least square structural equation modelling is chosen to test the hypothesized relationships.

The empirical results confirm that lean management is a vital element in moving SMEs towards the implementation of circular production systems. The results also confirm that lean management and circular production systems combine effectively to bring about significant improvement in zero-waste performance, reinforce green value competitiveness and boost social reputation. The results further confirm the mediation role of circular production system between lean management, zero-waste performance, green value competitiveness and social reputation.

Anchored on the tenets of the natural resource-based view theory, resource orchestration theory and stakeholder theory, this study proposes an integrated research model that builds new insights into the relationship between lean management, circular production system, zero-waste performance, green value competitiveness and social reputation. The proposed model directs the actions of SME managers in emerging countries to comprehensively evaluate their production processes to equalize the possible compatibility of lean management and circular production systems to meet their zero-waste performance targets, gain green value competitiveness and stimulate social reputation.

The real-time generation of feature descriptors for object recognition is a challenging problem. In this research, the purpose of this paper is to provide a hardware friendly framework to generate sparse features that can be useful for key feature point selection, feature extraction, and descriptor construction. The inspiration is drawn from feature formation processes of the human brain, taking into account the sparse, modular, and hierarchical processing of visual information.

A sparse set of neurons referred as active neurons determines the feature points necessary for high-level vision applications such as object recognition. A psycho-physical mechanism of human low-level vision relates edge detection to noticeable local spatial stimuli, representing this set of active neurons. A cognitive memory cell array-based implementation of low-level vision is proposed. Applications of memory cell in edge detection are used for realizing human vision inspired feature selection and leading to feature vector construction for high-level vision applications.

True parallel architecture and faster response of cognitive circuits avoid time costly and redundant feature extraction steps. Validation of proposed feature vector toward high-level computer vision applications is demonstrated using standard object recognition databases. The comparison against existing state-of-the-art object recognition features and methods shows an accuracy of 97, 95, 69 percent for Columbia Object Image Library-100, ALOI, and PASCAL VOC 2007 databases indicating an increase from benchmark methods by 5, 3 and 10 percent, respectively.

A hardware friendly low-level sparse edge feature processing system is proposed for recognizing objects. The edge features are developed based on threshold logic of neurons, and the sparse selection of the features applies a modular and hierarchical processing inspired from the human neural system.

The purpose of this paper is to explore the factors that influence migrant workers' household registration transfer willingness at both individual and urban levels and to provide empirical evidence on adjusting the household registration system to accommodate economic development and migrant workers' imbalances.

This paper adopts a hierarchical nonlinear model and examines individual and urban influencing factors of migrant workers' household registration transfer willingness, based on the data from China Migrants Dynamic Survey (CMDS) and the Urban Statistical Yearbooks.

This paper shows that: (1) multi-factors, such as age, education, marital status, household demographics, industry and migrant workers' contract coverage, have significant effects on migrant workers' household registration transfer willingness; (2) The urban public service equalization indicators, such as regional economic, educational resources, medical care and ecological quality, have significant effects on migrant workers' willingness to transfer household registration; (3) The heterogeneity of migrant workers' willingness to transfer household registration is significant in central, eastern and western China.

The authors provide a fresh perspective on population migration research in China and other countries worldwide based on the pull–push migration theory, which incorporates both individual and macro (urban) factors, enabling a comprehensive examination of the factors influencing household registration transfer willingness. This hierarchical ideology and approach (hierarchical nonlinear model) could be extended to investigate the influencing factors of various other human intentions and behaviors.

Micro approaches (individual perspective) have dominated existing studies examining the factors influencing migrant workers' household registration transfer willingness. The authors combine individual and urban perspectives and adopt a more comprehensive hierarchical nonlinear model to extend the empirical evidence and provide theoretical explanations for the above issues.