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Community question answering (CQA) platforms play a significant role in knowledge dissemination and information retrieval. Expert recommendation can assist users by helping them find valuable answers efficiently. Existing works mainly use content and user behavioural features for expert recommendation, and fail to effectively leverage the correlation across multi-dimensional features.

To address the above issue, this work proposes a multi-dimensional feature fusion-based method for expert recommendation, aiming to integrate features of question–answerer pairs from three dimensions, including network features, content features and user behaviour features. Specifically, network features are extracted by first learning user and tag representations using network representation learning methods and then calculating questioner–answerer similarities and answerer–tag similarities. Secondly, content features are extracted from textual contents of questions and answerer generated contents using text representation models. Thirdly, user behaviour features are extracted from user actions observed in CQA platforms, such as following and likes. Finally, given a question–answerer pair, the three dimensional features are fused and used to predict the probability of the candidate expert answering the given question.

The proposed method is evaluated on a data set collected from a publicly available CQA platform. Results show that the proposed method is effective compared with baseline methods. Ablation study shows that network features is the most important dimensional features among all three dimensional features.

This work identifies three dimensional features for expert recommendation in CQA platforms and conducts a comprehensive investigation into the importance of features for the performance of expert recommendation. The results suggest that network features are the most important features among three-dimensional features, which indicates that the performance of expert recommendation in CQA platforms is likely to get improved by further mining network features using advanced techniques, such as graph neural networks. One broader implication is that it is always important to include multi-dimensional features for expert recommendation and conduct systematic investigation to identify the most important features for finding directions for improvement.

This work proposes three-dimensional features given that existing works mostly focus on one or two-dimensional features and demonstrate the effectiveness of the newly proposed features.

A lot of people share their living or travelling experiences about cities by writing posts on social media. Such posts carry multi-dimensional information about the characteristics of cities from the public’s perspective. This paper aims at applying text mining technology to automatically extract city images, which are known as how observers perceive the status of the city, from these social media texts.

This paper proposes a data processing pipeline for automatic city image extraction and applies sentiment analysis, timing analysis and contrastive analysis in a case study on Wuhan, a central China megacity. Specifically, the city image constructed with social media text and the expected policy outcomes by the government are compared.

Results reveal gaps between the public’s impression and the strategic goals of the government in traffic and environment.

This study contributes a novel approach to assess government performance by complementary data from social media. This case study implies the value of social media-based city image in the identification of gaps for the optimization of government performance.

A product communicates to consumers through its form and function, which may generate an effective response. Little is known, however, about the impact of the interaction of form and functional newness on consumers’ adoption preference. Drawing on uniqueness theory, this research aims to propose that the relative importance of form and functional newness to adoption preference could vary depending on the degree of consumers’ need for uniqueness (CNFU).

To mimic real consumption behavior as much as possible in these studies, the authors first choose a product that the respondents are familiar with and use on a daily basis. Second, the authors conduct a series of conjoint analysis in which respondents are presented with a set of options simultaneously and are asked to make a choice of adoption among those options. The authors conduct three conjoint studies using students and adult consumers.

Evidence from three conjoint studies using both student and adult consumer samples confirms the moderating role of CNFU. The results indicate that form and functional newness positively impact adoption preference, the positive effect of form newness is weakened in a compare-and-choose decision when functional newness is in place and this weakened interaction effect is mitigated with increasing CNFU.

This research makes several contributions to the extant literature. First, the authors investigate the moderating role of CNFU in the interplay between form and functional newness. By identifying a distinctive pattern between high- vs low-CNFU consumers, the authors propose a new aspect to explain the inconclusive results of the interaction effects in previous studies. Extending this line of research, the authors show that there is a dynamic component to the positive influence of form and functional newness on adoption preference. Consumers’ preference for form newness, relative to functional newness, is likely to be lessened with the decrease in their need for uniqueness. Second, this research goes beyond the survey or sales data approaches of prior studies to examine the interaction of form and function in a context that reflects actual decision processes. Assuming that consumers have access to a set of options before making an adoption decision, the authors are able to determine their priorities and preferences for new products. Using conjoint analysis, the authors observe consumers make a trade-off between form and functional newness. This approach allows us to investigate the relative importance of form and functional newness in affecting consumers’ adoption decision. Finally, the consistency of the results of these three studies enhances the robustness of this research.

While consumers appreciate improved and newer functionality in general, this may not be the case for a novel form. For consumers who desire to belong or to fit into social norms, adopting a product with an extreme atypical form could be risky and provoke a negative social response. For those with such conservative attitudes, learning costs are likely to overshadow the excitement of owning a radical product. Thus, a product with high functional newness and standard form would be the right choice for this group of consumers. On the other hand, consumers with high CNFU are more likely to overcome concerns regarding the risks and learning costs of a novel form due to their desire to use the unconventional product display to differentiate themselves and establish their uniqueness. Therefore, a product with high functional newness and novel form may be more favorable for them. With this insight, marketers can better define their market segment and position their product strengths. For example, in the competitive smart phone industry, some brands may try to focus on high form newness to capture high-CNFU consumers (e.g. LG Flex curved cell phone).

First, the authors propose the moderating role of CNFU to explain the gap in the literature. This new view provides product managers and marketers with a better understanding of how consumers in different consumer segments (e.g. high vs low degree of CNFU) behave distinctively in their response to form and functional newness. Second, most of the literature on consumer response to product form has focused on consumer opinion, attitude, perception or product evaluation. This study focuses on measuring consumers’ adoption preference through a conjoint approach. This distinction is important because a positive attitude does not necessarily translate to adoption when consumers make their final choice decision. Third, prior studies test the effects of form and function using sales data or between subject experiments where respondents only view a single product. This approach is less representative of real adoption behavior when the reality is consumers often compare a set of options simultaneously and make an adoption decision among a pool of available options.

A three‐dimensional model for the fluid convection and heat flow in arc welding is proposed. It extends the previous two‐dimensional model by accounting also for the fluid flow and heat transfer in a travelling rather than a stationary mode. The model can be applied to analyse the heat‐ and fluid‐flow phenomena in welding processes. It is found that the fluid velocity in the pool front is higher than that in the pool rear. The fluid velocity field and the temperature distributions are directly proportional to the welding amperage and inversely to the welding speed. The comparison of the calculated and measured results show that the model is much more accurate than Rosenthal's theory and the pure conduction numerical method. Theoretical predictions based on the model are found to be in good agreement with experimental measurements.

Mathematical models of the metal‐inert gas (MIG) welding process may be used to study the influence of various welding parameters on weld dimensions, to assist in the development of welding procedures, and to aid in the generation of process control algorithms for automated applications. A three‐dimensional model for convection and heat transfer in MIG weld pools has been formulated and solved using the finite difference technique. The energy exchange between the pool and the molten filler metal droplets via spray transfer, and the interaction of electromagnetic, buoyant, surface tension, droplet impact and plasma jet forces were considered. MIG welding was carried out using mild steel plate with heat input from 7 to 17.5 KJ/cm. The calculated and experimentally observed weld bead dimensions were compared. Occurrence of finger penetration phenomena only in MIG welds are adequately explained through the application of the proposed model. Good agreement is demonstrated between predicted weld dimensions and experimentally measured ones.

The purpose of this paper is to examine how use of industry standards and community socialization contribute to the operational, strategic and environmental performances of supply chain partners.

Survey data were collected from 216 firms in China that have implemented RosettaNet standards. Structural equation modeling was used to test the hypotheses forming the research model.

The empirical analysis suggests that use of industry standards and community socialization is central to achieving greater supply chain performances. The results show that the use of industry standards and community socialization enhance inter-organizational knowledge sharing and trust, which eventually improve performances of supply chain partners.

The study makes several contributions to the literature. First, it highlights the importance of standards consortia, which not only develop and promote industry standards, but also improve community socialization. Second, the research examines how use of industry standards could influence the operational, strategic and environmental performances of supply chains, and thus fills the research gap in related literature. Third, this paper explores how industry standards can be used as boundary objects to span organizational boundaries and enable greater supply chain partnerships.

The purpose of this paper is to review research on options theory (OT) in the management information systems (MIS) field.

The paper reviews OT and suggests further ways it may be useful for MIS.

The paper explores current global trends and past uses of OT by MIS researchers within a framework. The objective is to broaden discussion of OT in the MIS field, facilitate theory development, close gaps in existing knowledge, and uncover areas where research is needed. It is believed that MIS researchers will benefit from this study.

The use of OT in MIS is still young. The discussions, issues, and ideas set forth in this paper should stimulate interest in incorporating OT in the field of MIS.

The paper identifies proper application of OT, thus enabling effective development. It seeks to build awareness and understanding of significant works in the field, providing a diversity of perspectives and approaches to MIS and more specific research of OT.

The paper helps future theorizing and makes research suggestions regarding OT and the MIS field based on past research, thereby forming a potential basis for future research.

There has been no systematic literature review of real options in the management field. This paper is the pioneer one to do this.

Examines the relationships between cultural values and preferences for human resource management (HRM) policies and practices in a sample of Taiwanese employees. Specifically, seeks to examine patterns of Chinese national culture in Taiwan, to identify the preferences of employees for specific HRM policies and practices, and to explore the extent to which individual cultural value orientations shape individual preferences for HRM policies and practices. Presents findings from data based on 452 employees from the shopfloor to senior management positions in seven Taiwanese organisations. By controlling the measure of national culture in terms of value orientations, it is found that they account for from only 5 per cent to 10 per cent of the total individual variance in HRM preference. A factor analysis supports the view that national culture value orientations represent a separate construct to both work values and more traditional measures of work outcomes, such as job satisfaction and commitment.

This study attempts to develop an approach with triangulation to explore the determinants of knowledge flows, as well as the relationships among them.

The proposed approach with the use of triangulation is designed to handle the issues that arise in the various interactions and numerous contexts among entities and/or activities that are associated with KM.

The proposed hybrid approach is found to be helpful in dealing with the issue of knowledge flow, especially involving various entities and complex interactions with numerous contents and dynamic contexts. In addition, the findings also show the presence of multi‐directional and adaptive interactions among determinants to knowledge flows, and also how these influence a firm's KM initiatives and performance.

The proposed hybrid approach can be considered as a way to overcome the limitations both of qualitative and quantitative methods, and the relationships among knowledge flows explored in this study provide some directions for future KM research.

The proposed approach focuses on the visualization of probable determinants to knowledge flows within an organization. This visualization can be utilized to evaluate the determinants and their relationships with each other, which may help managers to take actions to achieve more effective and efficient KM.

The results show the value of using a hybrid approach for dealing with research issues involving various entities and activities with complex content, such as knowledge flows.

The paper's objective is to present a group decision support system (GDSS) for facilitating the process of core knowledge selection.

The proposed GDSS is developed by taking advantage of the characteristics of certain existing analytical and mathematical methods, including knowledge‐based SWOT analysis, knowledge audit instruments, gap analysis, synergy analysis, similarity measures, multi‐objective linear programming (MOLP), and fuzzy programming. A case study was performed to identify whether or not the GDSS achieves its designed purpose.

The results show that GDSS can be applied effectively in identifying core knowledge that should be developed.

The proposed GDSS provides a comprehensive procedure for top managers, using a strategy‐orientated perspective to determine suitable core knowledge to be developed by appropriately analyzing internal synergy and external gap effects on core knowledge. Top managers need not only be aware of the relationship between core knowledge and other factors but must also consider decision‐making problems related to this issue.

Few prior studies have provided a systematic approach for develops organizational core knowledge by using analytical and mathematical methods. This paper particularly focuses on the question of how firms can actually identify core knowledge and thus develop appropriate strategies.