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Aiding employment is an important poverty reduction strategy in many countries’ social welfare systems, as this strategy can help empower the recipients with a better living standard, development and social inclusion. The purpose of this paper is to identify the most significant individual and systematic variables for the employment status of low-income groups in urban China.

The data of this study are drawn from “Social Policy Support System for Poverty-stricken Families in Urban and Rural China 2015” report. The Ministry of Civil Affairs of the People’s Republic of China appointed and funded the Institute of Social Science Survey (ISSS) at Peking University to deliver the related project and organize a research team to write the report. Multiple binary logistic regression analysis is adopted to identify both individual and systematic factors that affect the employment status among low-income groups in urban China.

According to the results of the binary logistic regression model, individual factors, including: gender; householder status; education; and self-rated health status, play a significant role in determining the employment status of low-income groups in urban China. Clearly, the impacts of individual factors are more influential to marginal families than to families entitled to receive Basic Living Allowance. In contrast, compared with marginal families, systematic factors are more influential to families entitled to receive Basic Living Allowance.

This study highlights the importance of precise poverty reduction strategy and the issue of “welfare dependence” among low-income groups in urban China. Policy recommendations derived from the findings are hence given, including: the promotion of family-friendly policies; the introduction of a smart healthcare system; the establishment of a Basic Living Allowance adjustment mechanism; and the provision of related social services.

This study investigates the role of source familiarity in moderating the effect of service adaptive behavior (SAB) on customer satisfaction. Applying the accessibility–diagnosticity framework and situated cognition theory as the theoretical basis, this research hypothesizes that when customers are familiar with the source that provides the service (i.e. brand familiarity for Study 1 and personal familiarity for Study 2), customer satisfaction responses to SAB would be more moderate than when customers are not familiar with the source. Two studies were conducted to test the hypotheses.

Two experiments manipulating SAB and the brand name familiarity (Study 1) and personal familiarity with the service staff (Study 2) as the source familiarity were conducted. Customer satisfaction as a function of source familiarity was measured to test the hypothesis that source familiarity moderates the relationship between SAB and customer satisfaction.

Compared to unfamiliar sources, familiar sources generated a more moderate response in customer satisfaction as a function of SAB. High familiarity with the brand and service staff induced top-down, memory-based processing that overrides external stimuli as the basis of satisfaction judgment; bottom-up, stimulus-based processing relying on SAB for judgment kicked in only when the source familiarity is low.

From a practical point of view, this study indicates the importance of SAB, especially for brands with low awareness, and alludes to the comparative importance of relationship building in service delivery processes.

This study contributes to the literature by validating the role of contextual factors in influencing the impact of SAB on customer satisfaction.

This paper aims to discuss the key factors affecting the quality characteristics, such as the number of solder balls, the spread distance of residual underfill and the completion time of the underfilling.

The Taguchi method is applied to configure the orthogonal table and schedule and execute the experiment. In addition, principal components analysis is used to obtain the points. Then, based on gray relational analysis and the technique for order preference by similarity to ideal solution, the closeness between each quality characteristic and the ideal solution is adopted as the basis for evaluating the quality characteristics.

The optimal parameter combination is proposed, which includes 4 dispensing (11 mg/dispensing), a “half flow” interval state, 80°C preheating module PCB board and an L-shaped dispensing path and verification testing is performed.

For vehicles and handheld electronic products, solder joints that connect electronic components to printed circuit boards may be cracked due to collision, vibration or falling. Consequently, solder balls are closely surrounded and protected by the underfill to improve joint strength and resist external force factors, such as collision and vibration. This paper addresses the defects caused during the second reflow process of a vehicle electronic communication module after the underfilling process.

The proliferation of non-fungible token (NFT)-based crypto-art platforms has transformed how creators manage, own and earn money through the creation, assets and identity of their digital works. Despite this, no studies have examined the drivers of continuous content contribution behavior (CCCB) toward NFTs. Hence, this study draws on the theory of relational bonds to examine how various relational bonds affect feelings of psychological ownership, which, in turn, affects CCCB on metaverse platforms.

Using structural equation modeling and importance-performance matrix analysis, an online survey of 434 content creators from prominent NFT platforms empirically validated the research hypotheses.

Financial, structural, and social bonds positively affect psychological ownership, which in turn encourages CCCBs. The results of the importance-performance matrix analysis reveal that male content creators prioritized virtual reputation and social enhancement, whereas female content creators prioritized personalization and monetary gains.

We examine Web 3.0 and the NFT creators’ network that characterizes the governance practices of the metaverse. Consequently, the findings facilitate a better understanding of creator economy and meta-verse commerce.

The proliferation of digital communication on social media provides new opportunities for businesses to take advantage of Internet memes to boost customer engagement. Academic literature on digital communications mostly focuses on popular forms such as selfies, branded posts, and branded emoticons. Less attention has been paid to brand memes and their implications for brand management. Based on the cue utilization theory, this research aims to investigate the informational cues of brand memes foster brand partnerships.

The structural equation modeling and importance-performance matrix analysis were used to empirically validate the research hypotheses with 595 respondents to an online survey.

Three informational cues of brand memes (i.e. comprehensibility, novelty, and meme-brand congruity) stimulated consumers' attitudes, which in turn impacted consumer-brand relationships. Another brand meme informational cue, sarcasm, negatively moderated the relationships between the three informational cues and consumer-brand relationships.

Our findings indicate that a brand can engage consumers in conversations on social media and foster long-term consumer-brand relationships through brand memes.

The purpose of this paper is to develop and validate a multidimensional hierarchical scale for measuring “e-service quality variation.”

Based on the psychometric scale-development approach, qualitative and quantitative methods were employed to develop the e-SERVAR scale. A multidimensional hierarchical factor structure of e-SERVAR is proposed, along with a set of preliminary items derived from literature and the qualitative study. Furthermore, the Yahoo website in Taiwan was chosen to be the target e-service website for data collection to develop the e-SERVAR scale. A series of statistical methods (i.e. item-to-total correlations, exploratory factor analyses, CFAs and structural equation modeling) were adopted to verify construct reliability and validity as well as nomological validity of the scale.

A 41-item e-SERVAR scale based on the structure of a hierarchical factor model was developed that contains three primary dimensions (i.e. information, system and fulfillment) and nine subdimensions (information accuracy, information quantity, information timeliness, information usefulness, system reliability, system security, merchandise quality, merchandise delivery timeliness and merchandise security).

The results of this study help managers identify sources of quality variability and design efficacious strategies to reduce such variability in order to improve the overall e-service quality.

Prior research of e-service quality has paid less attention to the role of e-service quality variability. Discussion of e-service quality variability was mainly conceptual in nature. This research presents the e-SERVAR scale as a measurement tool that provides a new avenue for researchers to study how to improve e-service quality by measuring service variability.

Dealing with online rumors or fake information on social media is growing in importance. Most academic research on online rumors has approached the issue from a quantitative modeling perspective. Less attention has been paid to the psychological mechanisms accounting for online rumor transmission behavior on the individual level. Drawing from the theory of stimulus–organism–response, this study aims to explore the nature of online rumors and investigate how the informational characteristics of online rumors are processed through the mediation of psychological variables to promote online rumor forwarding.

An experimental approach to this issue was taken; the researchers investigated how the informational characteristics of online rumors and the psychological mediators promote online rumor transmission.

Four information characteristics (sense-making, funniness, dreadfulness and personal relevance) and three psychological motivators (fact-finding, relationship enhancement and self-enhancement) promote online rumor-forwarding behavior.

Because any online rumor transmitted on social media can go viral, companies may eventually encounter social media-driven crises. Thus, understanding what drives rumor-forwarding behavior can help marketers mitigate and counter online rumors.

The relationship between farm size and land productivity is a hotly debated issue in the study of agricultural economics and development economics. The purpose of this paper is to explore the causes leading to the inverse productivity relationship by examining the relationship between farm size and factor inputs.

With a large panel data set of farm households in China during 2010–2011, this study uses the factor demand models to examine the relationship between farm size and per-mu labor and non-labor inputs while employing a stochastic frontier production function in determining the difference of labor efforts in farming operation across farm sizes. Moreover, the models for value-added margins and profits are used to further determine producer behavior of small-size farms.

Results of this study show that, as compared to larger farms, smaller farms not only utilize more labor and non-labor inputs per mu, but also benefit from a higher labor effort. Moreover, smaller farms concentrate more on grain output and cash costs while focusing less on the family labor input costs in an effort to maximize value-added margins rather than profits. The higher yields on smaller farms are thus a result of the utilization of a relatively higher level of labor and non-labor inputs along with skilled-oriented precision farming technology. The inverse productivity relationship is explained by the behavior of small-size producers with employment constraints, leading to smaller farms generating a higher yield than larger farms.

While Sen (1966), Feder (1985), Eswaran and Kotwal (1986) and others have theoretically derived the causal relationship between the incomplete factor markets, especially incomplete labor markets, and the inverse productivity, empirical studies to test the causal relationships are limited. In particular, a solid foundation based on an empirical analysis is lacking when it comes to explaining the inverse productivity in China. Results of this study are expected to have significant policy implications in terms of the understanding of small-size producer behavior and the associated mechanism underlying the inverse relationship between farm size and land productivity.

This study aimed to identify and assess the barriers to implementing modular construction systems (MCS) in developing country's architecture, engineering and construction (AEC) industry, targeting built environment professionals from Nigeria and South Africa.

The study adopted a quantitative research method, using a structured questionnaire to seek the opinions of the professionals on the identified categories of barriers.

Results indicated that all identified categories of barriers were statistically significant using a one-sample t-test at p = 0.05 significance level which indicates they are critical towards the implementation of MCS in developing countries. Assessment of the opinion of the professionals using the Kruskal–Wallis scale showed that they hold similar views on the barriers to the adoption of MCS. Pearson correlation shows a high correlation coefficient amongst the barrier categories and an acceptable level of significance (p = 0.05).

This study is limited to two significant African countries (Nigeria and South Africa) selected based on the gross domestic product (GDP). Further studies can consider developing countries outside Africa and investigate broader respondents.

The study provides implications on the barriers affecting MCS in developing countries for the academia, industry and government to have an insight into the barriers and make informed decisions and policies.

The research satisfies the need to study the barriers affecting the MCS in developing countries that can mitigate housing deficits. This innovative construction method has been adopted and implemented in developed countries, and the result has been positive.

This study aims to identify the factors and propose a conceptual framework for the civil aviation industry from the sustainability perspective with the participation of international entrepreneurs. Based on the results of this study, international decision-makers and entrepreneurs in the civil aviation transportation industry will better understand their decision-making processes. A combination of interpretive structural modelling (ISM) and matrix-based multiplication applied to a classification (MICMAC) was used to classify practical factors to depict a conceptual model based on their level and classification in the sustainable supply chain (SSC) of the civil aviation transportation industry. In this study, special attention has been paid to the issue of sustainability as an essential mechanism for developing international entrepreneurship in the civil aviation transportation industry. The factor of flexibility in service production was identified as the driver factor; the factors of organisational commitment to a SSC were found to have the highest driver-dependent power that can attract international entrepreneurs in this field.