A Multi-Attribute Group Decision Approach Based on Rough Set Theory and Application in Supply Chain Partner Selection

In multi-attribute group decision, decision makers (DMs) are willing or able to provide only incomplete information because of time pressure, lack of knowledge or data, and their limited expertise related with problem domain, so the alternative sets judged by different decision makers are inconsistent in allusion to a certain decision problem, how to form consistent alternative sets becomes a very important problem. There have been a few studies considering incomplete information in group settings, but few papers consider the adjustment of inconsistent alternative sets. We suggest a method, utilizing individual decision results to form consistent alternative sets based on Rough Set theory. The method can be depicted as follows: (1) decision matrix of every decision maker is transformed to decision table through an new discretization algorithm of condition attributes ; (2) we analyze the harmony of decision table of every DM in order to filter some extra alternatives with the result that new alternative sets are formed; (3) if the new alternative sets of different DMs are inconsistent all the same, learning quality of DMs for any inconsistent alternative is a standard of accepting the alternative

Market Orientation, Electronic Supply Chain Integration, and Firm Performance in China: The Moderating Role of Ownership Type

Integrating supply chain processes over the Internet to achieve competitive advantages has generated much attention from practitioners and researchers, especially those in emerging economies. Drawing upon the institutional theory and resource based view, this study investigates how market orientation affects electronic supply chain integration (eSCI), which, in turn, influences firm performance in the emerging economy of China. We further examine how the relationships between market orientation and eSCI are moderated by ownership type. The results of a survey with 260 firms in China suggest that the dimensions of market orientation have differential impacts on the eSCI, and both dimensions of eSCI have significant effects on firm performance. In addition, the relationships between market orientation and eSCI are moderated by both ownership type in China. Implications and suggestions for future research are discussed

Effect of Online Brand Community on Customer Behavior Exploration: Reconciling Mixed Findings via Regulatory Focus Theory

This study seeks to address the mixed findings of prior studies regarding the effect of online brand community on customer behavior. Based on the regulatory focus theory, we hypothesize that participation in a brand community tends to increase both visit and purchase frequencies of customers with promotion-focus; on the contrary, the same would typically decrease visit and purchase frequencies of customers with prevention-focus. By analyzing data from an online brand community using a “propensity-score matching” technique, we found a partial validation that attendance of the community led to increases in customer visit frequency for customers with both promotion-focus and prevention-focus. Further, our results show that customers with promotion-focus tend to purchase more; while customers with prevention-focus slightly decreased their purchase volume. Both theoretical and practical implications of our findings are discussed in the paper

Conceptual Modeling of Collaborative Intelligent Manufacturing For Customized Products: An Ontological Approach

Mass customization is implemented to provide outstanding service to customers with diverse tastes and preferences. However, mass customization has limitations in the traditional value chain and production paradigm. Taking advantage of advanced information technology, such as manufacturing grid and virtual enterprise, to facilitate mass customization and improve the customer perceived valued of mass customization raises a challenge issue. To achieve an ideal mass customization, the customer\u27s needs should be identified and met by the collaborative manufacturing from several manufacturers. Comprehensive conceptual models corresponding to the collaborative manufacturing for customized products are essential to understand how the collaborative process can apply in customized production, and facilitate early detection and correction of system development errors. In this paper, an ontology is described via a customized bicycle buying scenario to describe how to use an ontology for collaborative manufacturing. This ontological approach provides understanding of the domain, which can be used as a unifying framework to represent the selected phenomena for conceptual model

A Novel Personalized Academic Knowledge Sharing System in Online Social Network

Information overload is a major problem for both readers and authors due to the rapid increase in scientific papers in recent years. Methods are proposed to help readers find right papers, but few research focuses on knowledge sharing and dissemination from authors’ perspectives. This paper proposes a personalized academic knowledge sharing system that takes advantages of author’s initiatives. In our method, we combine the user-level and document-level analysis in the same model, it works in two stages: 1) user-level analysis, which is used to profile users in three dimensions (i.e., research topic relevance, social relation and research quality); and 2) document-level analysis, which calculates the similarity between the target article and reader’s publications. The proposed method has been implemented in the ScholarMate, which is a popular academic social network. The experiment results show that the proposed method can effectively promote the academic knowledge sharing, it outperforms other baseline methods

THE MODERATING EFFECTS OF CONTEXTUAL FACTORS ON A BUYER’S TRUST IN E-COMMERCE PLATFORMS AND SELLERS

Drawing on trust transfer theory and signal theory, we investigate how perceived effectiveness of e-commerce institutional mechanisms (PEEIM) and perceived website quality of the seller (PWQS) moderate the relationships between trust in platform, trust in seller and purchase intention in the context of Consumer to Consumer (C2C) platforms. To test our proposed model, we surveyed 224 buyers of TaoBao, a major Chinese C2C portal. The results indicate that PEEIM has no effect on the relationship between trust in platform and trust in seller, yet it positively moderates the relationship between trust in seller and purchase intention. In addition, PWQS positively moderates the relationship between trust in platform and trust in seller, but negatively moderates the relationship between trust in seller and purchase intention. The theoretical and practical implications are discussed

Intelligent Agents for Negotiation and Recommendation in Mass Customization

Mass customization, as a means to meet individual consumer’s need on a large scale, has recently attracted the attention of both researchers and practitioners. However, as customers and their needs grow increasingly diverse, meeting every consumer’s need has become a surefire way to add unnecessary cost and complexity to operations. Furthermore, consumers are not all really ready for mass customization. They have to face inconveniences such as expensive price, delay delivery and they have to spend time “designing” their product. In order to solve this problem, we proposed a way of intelligent agent assisted negotiation and recommendation. The recommendation is a preference elicitation process, while the negotiation is a communication process based on the situation of manufacturer, such as the inventory level, production cost and lead time. With the aid of intelligent agent of negotiation and recommendation, a good balance between efficiency and customer satisfactions of mass customization can be reached

Supporting Undergraduate Research: Recommending Personalized Research Projects to Undergraduates

Undergraduates’ participation in faculty-mentored research is becoming an important issue in tertiary education in recent years, and it benefits both undergraduates and faculty members. In reality, many faculty members have research projects that need help from undergraduates, but undergraduates can hardly find the information, which creates information asymmetry problem. Besides, undergraduates lack the experience of doing academic research, the research interest information is incomplete, so they have difficulties in choosing suitable research projects. Thus recommender systems are necessary to facilitate undergraduates’ participation in research projects. Traditional recommendation approaches require relative complete information for decision making, and they can hardly meet the requirements as undergraduates’ research information is incomplete. In this study, we propose a two-stage model that integrates content-based method with collaborative method by leveraging research social networks, where undergraduates are encouraged to connect with faculty members and participate in social network activities, through which research information is collected. The proposed two-stage model alleviates the problems of information asymmetry and incomplete information. The recommender system has been developed in ScholarMate (www.scholarmate.com), and it allows undergraduates to choose suggested research projects

Supply Chain Exploitation, Exploration, and Firm Performance: Effects of Top Management and Information Technology Capabilities

While supply chain (SC) exploitation and exploration have been playing an increasingly important role in supply chain management, there is a dearth of research examining their antecedents and outcomes. In this research, we examine how SC exploitation and exploration impact firm performance. Specifically, drawing upon the boundary spanning theory, we theorize how top management, as boundary spanners, and three types of information technology (IT) capabilities, as boundary objects, enable SC exploitation and exploration. Our research hypotheses are tested using data collected from 157 firms in China. We found that both SC exploitation and exploration have significantly positive effects on firm performance. Also, top management participation directly affects both SC exploitation and exploration. In addition, IT business partnerships and external IT linkages positively affect both SC exploitation and exploration, whereas IT infrastructure is not significantly related to either SC exploitation or exploration. Contributions and implications of this study are discussed

The Interaction Effects between Supply Chain Integration and IT Capabilities on Firm Performance

It is well touted that embedding information technology (IT) capabilities in supply chain processes would allow firms to derive competitive advantage. Yet the outcomes of such embeddedness vary greatly across companies. Investigating how a firm configures appropriate IT capabilities with supply chain integration (SCI) to achieve superior performance is of significance. Drawing upon the dynamic capabilities theory, we examine how SCI and IT capabilities jointly affect firm performance. We test the hypotheses of interest with data collected from 252 firms in China. The results of hierarchical regression analysis reveal that the interactive effects of SCI and IT capabilities on firm performance vary across different combinations of dimensions of SCI (i.e., information sharing and collaborative planning) and IT capabilities(i.e., IT infrastructure flexibility, IT assimilation capability, and top management’s IT knowledge). In addition, the dimensions of SCI and IT capabilities have differential effects on firm performance. Theoretical contributions and managerial implications of the current research are discussed