Search results

Grounded in two primary theories such as (1) the triangular alignment model and (2) the technology–organization–environment framework, this paper aims to develop appropriate scales to measure the e-sourcing experience index (EEI).

The sample includes a total of 630 e-sourcing platform users in the US and India who have already utilized e-commerce platforms. Item response theory and factor analysis were used for the psychometric analysis. Measurement invariance was established between the Indian and US participants, indicating similar conceptualization of the items across the two cultures.

The study's results demonstrated that users have a better experience when online sourcing platforms provide adequate resources for making sourcing decisions, finding potential buyers and managing sourcing activities more efficiently. From the perspective of e-sourcing platforms, suppliers' performance and users' experiences can be improved when businesses address the concerns indicated in the five factors.

The study's objective was to develop the EEI in order to assess suppliers' experiences with e-sourcing platforms. Due to the diffusion of innovation theory (DOI), different stages of adaptation may cause varied experiences and relationships with buyers.

From a theoretical perspective, this study is one of the few to combine triangular alignment model (TAM) and technology–organization–environment (TOE) theories and to develop a reliable and valid scale (EEI) for user experiences with online sourcing platforms. Based on the previous scales, the EEI was found to be well in line with the established theories on traditional apparel sourcing, and, at the same time, considered the particulars of e-sourcing practices.

Sustainable houses remain at a low rate among the housing stock in New Zealand. Government, industry and the public are wanting to deliver homes that are energy and water efficient, healthy and adaptive to the climate. The purpose of this paper is to find out the driving forces influencing the uptake of sustainable housing in New Zealand.

Comparative case studies of Hobsonville Point, Wynyard Quarter and Long Bay were adopted as the primary research method. Semi-structured interviews and an online survey were both conducted for data collection to increase the validity of the research.

Central and local governments were the most effective driving forces for encouraging sustainable housing. Corporate brand and leadership were critical drivers for public-owned companies, whereas private-owned companies were mainly driven by local governments’ policies and strategies. Social awareness and client demand were increasing to influence the sustainable housing, but there was still room for improvement.

The developers can learn from the sustainable development frameworks to set the sustainability goals. Policymakers can draw lessons from the public sectors’ experiences to carry out new policies and inspire the private sectors to follow. Besides, the basic framework could help the further study to use a larger sample size and more rigorous statistical analysis to explore the synergies among the identified drivers.

This paper provides the useful information on how to promote the uptake of sustainable housing in New Zealand.

The output of academic literature has increased significantly due to digital technology, presenting researchers with a challenge across every discipline, including materials science, as it is impossible to manually read and extract knowledge from millions of published literature. The purpose of this study is to address this challenge by exploring knowledge extraction in materials science, as applied to digital scholarship. An overriding goal is to help inform readers about the status knowledge extraction in materials science.

The authors conducted a two-part analysis, comparing knowledge extraction methods applied materials science scholarship, across a sample of 22 articles; followed by a comparison of HIVE-4-MAT, an ontology-based knowledge extraction and MatScholar, a named entity recognition (NER) application. This paper covers contextual background, and a review of three tiers of knowledge extraction (ontology-based, NER and relation extraction), followed by the research goals and approach.

The results indicate three key needs for researchers to consider for advancing knowledge extraction: the need for materials science focused corpora; the need for researchers to define the scope of the research being pursued, and the need to understand the tradeoffs among different knowledge extraction methods. This paper also points to future material science research potential with relation extraction and increased availability of ontologies.

To the best of the authors’ knowledge, there are very few studies examining knowledge extraction in materials science. This work makes an important contribution to this underexplored research area.

Because of the properties of loess, the occurrence of collapse following deformation of a large settlement is a common problem during the excavation of tunnels on loess ground. Hence, risk management for safer loess tunnel construction is of great significance. The purpose of this paper is to explore the influence of factors on collapse risk of loess tunnels and establish a risk assessment model using rough set theory and extension theory.

The surrounding rock level, groundwater conditions, burial depth, excavation method and support close time were selected as the factors and settlement deformation was the verification index for risk assessment. First, using rough set theory, the influence of risk factors on the collapse risk of loess tunnels was calculated by researching engineering data of excavated sections. Then, a collapse risk assessment model was developed based on extension theory. As the final step, the model was applied to practical engineering in the Loess Plateau of China.

The weights of surrounding rock level, groundwater conditions, burial depth, excavation method and support close time obtained using rough set theory were respectively 10.811 per cent, 18.919 per cent, 24.324 per cent, 40.541 per cent and 5.406 per cent. The assessment results obtained using the model were in good agreement with field observations.

This study highlights key points in collapse risk management of loess tunnels, which could be very useful for future construction methods. The model, using easily obtained parameters, helps in predicting the collapse risk level of loess tunnels excavated under different geological conditions and by different construction organizations and provides a reference for future studies.

This study aims to test the effects of Technology-related Divestitures (TRDs) on firms' exploratory innovation. The moderating effects of firms' internal and external resource coordination activities, resource buffering and bridging, are also explored.

A set of data including 1,372 Chinese listed firms from 2009 to 2018 is adopted. Based on propensity score matching sample, random-effect Tobit models were employed to test the hypotheses.

The empirical results indicate that TRDs inhibit firms' exploratory innovation, while both resource buffering and bridging can mitigate this negative effect. This implies that to promote exploratory innovation, resource coordination activities are the essential.

The research findings can contribute to both the exploratory innovation and technological divestiture literature. The test on the moderating roles of resource buffering and bridging can also extend our understanding of the effect of TRDs on firms' exploratory innovation. Accordingly, several practical implications can be provided. This is especially important for strategic decisions of firms from emerging and developing countries, which often lack sufficient internal resources and strong technological capabilities to develop exploratory innovation.

The color painting of ancient buildings has high historical and artistic value but is prone to aging due to long-term outdoor exposure. The purpose of this study is to develop a new type of sealing coating to mitigate the impact of ultraviolet (UV) light on color painting.

The new coating was subjected to a 500-h UV-aging test. Compared with the existing acrylic resin Primal AC33, the UV aging behavior of the new coating, such as color difference and gloss, was studied with aging time. The Fourier infrared spectra of the coatings were analyzed after the UV-aging test.

Compared with AC33, the antiaging performance of SF8 was substantially improved. SF8 has a lower color difference value and better light retention and hydrophobicity. The Fourier transform infrared spectroscopy results showed that the C-F bond and Si-O bonds in the resin of the optimized sealing coating protected the main chain C-C structure from degradation during the aging process; thus, the resin maintained good stability. The hindered amine light stabilizer TN292 added to the coating inhibited the antiaging process by trapping active free radicals.

To address the problem of UV aging of oil-decorated colored paintings, a new type of sealing coating with excellent antiaging properties was developed, laying the foundation for its demonstration application on the surface of ancient buildings.

India generates around two million tonnes of e-waste every year, and it is increasing at a very high rate of 30%. However, due to inefficient handling of infrastructure and limited number of collection centres along with the absence of proper incentive structure for producer and recyclers, 95% of e-waste reaches to unorganized sector for disposal. Consumers are not aware of the need of proper e-waste disposal and in absence of proper motivation and they are not inclined towards recycling process. Therefore, this paper aims to identify the best practices of e-waste take adopted all over the world to implement effective policy interventions for e-waste management in India and other emerging economies.

This paper has recommended preventive as well as curative policy interventions on the basis of best e-waste management practices of Germany, Italy and Japan; life cycle assessment of e-waste; and SWOT analysis of Indian electronic product industry.

Preventive measures include a deposit refund scheme wherein a consumer will be responsible for depositing a refundable fees during the purchase of the product. The amount should be arrived at keeping in mind cost involved in handling e-waste and ensure some motivation for the consumers to give back used product. To ensure proper tracking of the product, Radio frequency identification (RFID) tags can be used which will be activated at the time of sale of product and remain so until product reaches some designated recycling space or recycler and consumer is returned back his deposit fee. Subsidy to the producers and recyclers can also be provided by the government to further incentivize the whole process. An example of mobile phones has been used to understand the proposed deposit fees and associated cost structure. Curative measures to reduce the generation of e-waste in long run for managing the discussed issue have also been proposed.

This study is an initiative for proposing and implementing best e-waste take back techniques in a developing economy like India by acquiring learnings from best/advanced economies in terms of e-waste take back.

The purpose of this paper is to bring together the textual and multimedia opinions, since the use of social data has become the new trend that enables to gather the product reputation traded in social media. Integrating a product reputation process into the companies' strategy will bring several benefits such as helping in decision-making regarding the current and the new generation of the product by understanding the customers’ needs. However, image-centric sentiment analysis has received much less attention than text-based sentiment detection.

In this work, the authors propose a multimedia content-based product reputation framework that helps in detecting opinions from social media. Thus, in this case, the analysis of a certain publication is made by combining their textual and multimedia parts.

To test the effectiveness of the proposed framework, a case study based on YouTube videos has been established, as it brings together the image, the audio and the video processing at the same time.

The key novelty is the implication of multimedia content in addition of the textual one with the goal of gathering opinions about a certain product. The multimedia analysis brings together facial sentiment detection, printed text analysis, opinion detection from speeches and textual opinion analysis.