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This paper explores what factors influence household textile washing behaviour and how these factors relate to greenhouse gas emissions during the textile use stage.

A questionnaire survey related to textile summer washing and care behavior was conducted among households in 16 administrative districts of Shanghai. This study used the modified Consumer Lifestyle Approach framework of the washing and care ecosystem. The research hypotheses were established by selecting related factors from four aspects: household demographic characteristics, economy and consumption characteristics, washing machines and detergents characteristics.

First, we have demonstrated how some course factors do not significantly affect greenhouse emissions. None of the demographics, detergent-related activities, economy and consumption constructs significantly affect greenhouse emissions. Second, we have identified that washing machine and related activities has a direct positive effect on GHG emissions. The washing machine is not only the de facto carrier of all washing activities but also the core of washing activities. Washing machine is crucial in reducing greenhouse emissions and adjusting consumer behaviors.

This paper conducts a study related to the washing and care behavior of households in Shanghai. The paper examines the factors influencing household washing behavior and the relationship between these factors and greenhouse gas emissions during the textile use phase.

Recently, digital competence has become one of the most important work competencies of employees. This study investigated students' digital competence in the context of Chinese higher education and examined digital competence's relationship with students' career adaptability.

The participants were 298 Chinese higher education students from both universities and colleges. MANOVA (Multivariate Analysis of Variance) was carried out through SPSS (Statistical Package for the Social Sciences) 26.0 to examine whether digital competence varied with the students' personal characteristics, i.e. gender, grade level and school type. In addition, the structural equation model was employed with Mplus 8.3 to analyse the relationship between digital competence and career adaptability as well as the mediation role of digital informal learning and academic performance.

The descriptive statistics revealed that students performed best in the safety construct, whilst worst in the digital content creation construct. The result of MANOVA showed that the digital competence of the participants significantly varied with participants' gender, school type and grade level. Furthermore, the structural equation model results demonstrated that higher education students' digital competence was positively associated with the students' career adaptability. And the mediation role of digital informal learning and academic performance was also confirmed.

To the authors' knowledge, this is the first study focussing on the relationship between digital competence and career adaptability. In particular, both working and learning perspectives were considered to explore this relationship. Besides, the authors also displayed Chinese higher education students' digital competence with consideration of different districts and school types.

The purpose of this research is to investigate the R&D investment (RDI) of manufacturing firms from the perspective of supply chain network, especially the effect of firms' supply chain network structures (network power and network cohesion) on its RDI, and further to explore the contingency conditions of this effect within the context of Chinese manufacturing supply chains.

The authors collect a large sample of Chinese manufacturing firms over the period 2014–2019 and construct a large-scale supply chain network, and finally obtain 2,390 firms from 20,483 observations. Ordinary least squares regression was adopted to analyse how supply chain network structures affect RDI in manufacturing firms.

It is surprising that firm's supply chain network structures have a negative effect on RDI. In addition, knowledge and technology intensity (KTI) positively moderate the relationship between network cohesion and RDI.

This study contributes to the innovation stream from the perspectives of supply chain network, and provides the empirical findings that the negative role of a firm's supply chain network structure on its RDI for the first time. The rationale for these negative effects is straightforward according to the social capital theory that manufacturing firms with a high level of social capital that are possibly to accept established patterns of thinking and behaviour, causing them to decrease the enthusiasm of RDI.

The purpose of this paper is to discuss characteristics of organic food value chain governance and policy tools that can increase the supply of good quality of agri-products.

This paper discusses a national organic food supply system in China, identifying the link between an organization form with a social confidence crisis and information asymmetry as the main challenges. It develops an analytical model of the market structure of organic certification based on the contract theory, which considers the certification incentive driven by both farmers and processors. Two cases of raw milk producers and processors provide empirical data.

The argument which is brought forward is that product information asymmetry together with strict requirement for ensuring organic food integrity brings the organic milk value chain into a highly integrated organization pattern. A tight value chain is effective in the governance of organic food supply chain under third party certification (TPC), while a loose value chain discourages producing organic products because of transaction costs. TPC is found to be a positively correlation with a tight value chain, but it brings high organizational cost and it raises cost for consumers.

This is the first paper discussing the governance of organic food value chain in Chinese milk industry.

Purpose/approach – This introduction sets forth the main themes of the volume, reviews the methods employed by its contributors, and demonstrates the relationships among the chapters.

Research implications – The introduction demonstrates the ways gender research engages topics of current social, economic, and political importance and the ways in which focus on these topics advances an intersectional approach to gender research.

Practical and social implications – Drawing on each of the chapters, the authors point to the ways in which the global movement of people, media, and ideas foster changes in self-concepts, behavior, and social policy.

Value of the chapter – The essay serves as an overall introduction to the volume.

Skeleton plays an important role in representing the essential feature of garment in image. General skeleton extraction methods often yield many short skeletal branches. Though short branches reflect the geometric details of the garment, they are obstacles in extracting the essential features. The purpose of this paper is to provide an approach to hierarchically remove them to reveal the level of details (LOD) of the skeleton, thus both the essential skeleton and the geometric skeletal branches can be definitely extracted and separated.

First, the initial garment image skeleton is extracted and smoothed. Then, the hierarchically removing mechanism is established on scoring the importance of each skeletal branch by an altered PageRank method and computing the symmetry among skeletal branches.

Experimental examples show that this method can extract and separate garment essential skeleton as well as geometric skeletal branches hierarchically. Garments in same class have a similar essential skeleton with detailed differences, so this approach can be potentially applied in garment recognition and style specification.

Traditionally, there is almost no work attempts to build LOD in skeleton of planar shapes. This paper provide an automatic device for building LOD skeleton for garment image. In another word, hierarchic skeletons with details in different prominence level are gradually established. And pairs of symmetric skeletal parts are found by taking advantage of symmetry characteristic of garment. This method is efficient in garment image skeleton extraction.

The study aims to investigate consumer preferences across 25 attributes of plant-based milk (PBM) products and examine the key predictors and underlying mechanisms of consumer purchase decisions of PBM alternatives.

This study employed a multidimensional approach to investigate consumer preferences and the determinants of PBM purchasing decisions. Drawing on data from 819 online surveys conducted in the Jing-Jin-Ji region of China in 2021, we measured consumer preferences across 25 specific attributes and other individual characteristics. Purchasing decisions were framed as a two-stage process – the decision to purchase (frequency) and the decision on how much to pay (WTP). The Least Absolute Shrinkage and Selection Operator (LASSO) model was utilized to examine these dimensions separately, and the selected predictors were incorporated into OLS linear and Heckman’s two-stage regression analyses to establish the underlying mechanisms.

The findings indicate that consumers exhibit a strong preference for freshness and the absence of spoilage, followed by taste experiences such as taste and aroma. Preferences for milk preservation significantly increase the purchase frequency of PBM, while preference for calorie content has a negative and significant impact. Preferences for milk preservation, aroma and processing methods can also significantly increase WTP. Preferences vary across PBM categories. Social influence, knowledge and advertising exposure positively impact purchase frequency and WTP. Consumers with low food neophobia tend to be more responsive to product-related factors, such as freshness, calorie content and processing methods, in their purchase decisions.

This study contributes to the extant literature by comprehensively examining the determinants of consumer purchase decisions for PBM alternatives. The findings provide practical implications for marketers and policymakers, highlighting the strategic product attributes, consumer segments and marketing levers that can effectively target and cater to consumer preferences for PBM alternatives.

The timeliness and quality of information provided to board members are crucial for them to effectively monitor and advise a firm. This study examines the influence of board composition and structure on (1) the board’s actions to mitigate the information asymmetry problem by implementing enterprise information systems (EIS) and (2) the board of directors’ awareness of information asymmetry, their perception of its causes and their efforts to address it.

Our research employs a mixed-methods approach. First, using data from 115 publicly listed Chinese companies, we empirically assess the likelihood of top-level EIS modules adoption at the firm level. Subsequently, through 23 semi-structured interviews, we aim to gain deeper insights into the behavioral motivations behind directors’ attempts to reduce information asymmetry.

The study reveals that boards with a higher number of independent directors or with a strategy committee – indicative of a greater concern regarding information asymmetry problems – are more inclined to adopt top-level EIS modules. Additionally, we identify three primary sources of information asymmetry that directors consider significant in prompting the adoption of top-level EIS modules to alleviate perceived information asymmetry.

This study contributes to both the corporate governance and information systems literature. The implementation and utilization of EIS at the board level have not been extensively explored previously. Moreover, while the issue of information asymmetry at the board level is recognized as a critical governance challenge, the ways in which directors perceive and address this issue remain largely unknown. Our research seeks to illuminate this relatively less-explored area.

This paper aims to investigate the collision avoidance problem for a mobile robot by constructing an artificial potential field (APF) based on geometrically modelling the obstacles with a new method named the obstacle envelope modelling (OEM).

The obstacles of arbitrary shapes are enveloped in OEM using the primitive, which is an ellipse in a two-dimensional plane or an ellipsoid in a three-dimensional space. As the surface details of obstacles are neglected elegantly in OEM, the workspace of a mobile robot is made simpler so as to increase the capability of APF in a clustered environment.

Further, a dipole is applied to the construction of APF produced by each obstacle, among which the positive pole pushes the robot away and the negative pole pulls the robot close.

As a whole, the dipole leads the robot to make a derivation around the obstacle smoothly, which greatly reduces the local minima and trajectory oscillations. Computer simulations are conducted to demonstrate the effectiveness of the proposed approach.