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The trade-off between knowledge exploration and exploitation in technological innovation SSCI Scopus
期刊论文 | 2018 , 22 (4) , 781-801 | JOURNAL OF KNOWLEDGE MANAGEMENT
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Abstract :

Purpose This study aims to clarify the effect of team effort allocation between knowledge exploration and exploitation on the generation of extremely good or poor innovations. The influence of previous collaborative experience among team members on the effect of team effort allocation is also investigated to understand the relationship between team members' collaboration networks and knowledge learning. Design/methodology/approach This study uses data of all patents granted by the US Patent and Trademark Office between 1984 and 2010. The inventors involved in a patent are regarded as members of the focal team. Logistic regression is used to analyze the data. Findings Allocating greater effort to exploration than to exploitation is beneficial to achieving breakthrough innovations despite the risk of generating particularly poor innovations. This benefit increases with collaborative experience among team members. Placing an equal emphasis on knowledge exploration and exploitation is not particularly effective in achieving breakthrough innovations; it is, however, the best strategy for avoiding particularly poor innovations. Originality/value This research not only provides valuable insights for research on innovation and knowledge management by studying the team effort allocation strategy used to achieve breakthroughs and avoid particularly poor innovations but also represents an advancement in bridging two streams of research - knowledge learning and social networks - by highlighting the influence of the team members' collaborative networks on the effect of team effort allocation between knowledge exploration and exploitation.

Keyword :

Technological innovation Knowledge learning Knowledge exploitation Breakthrough Collaborative network Knowledge exploration

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GB/T 7714 Li, Dehong , Lin, Jun , Cui, Wentian et al. The trade-off between knowledge exploration and exploitation in technological innovation [J]. | JOURNAL OF KNOWLEDGE MANAGEMENT , 2018 , 22 (4) : 781-801 .
MLA Li, Dehong et al. "The trade-off between knowledge exploration and exploitation in technological innovation" . | JOURNAL OF KNOWLEDGE MANAGEMENT 22 . 4 (2018) : 781-801 .
APA Li, Dehong , Lin, Jun , Cui, Wentian , Qian, Yanjun . The trade-off between knowledge exploration and exploitation in technological innovation . | JOURNAL OF KNOWLEDGE MANAGEMENT , 2018 , 22 (4) , 781-801 .
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Scheduling Interrelated Activities Using Insertion-Based Heuristics EI SSCI SCIE Scopus
期刊论文 | 2018 , 65 (1) , 113-127 | IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
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Abstract :

The issue of scheduling interrelated activities is important and of particular concern to design managers. One tool that helps us to solve this issue is the design structure matrix (DSM) which can explicitly represent the information dependencies among interrelated activities. Based on the DSM method, this study presents effective approaches for sequencing interrelated activities with the goal of minimizing total feedback length, which is a good approximation for reducing project completion time. First, we prove two new properties of the problem, and develop an insertion-based heuristic. Second, the proposed heuristic is further improved by combing it with simulated annealing and genetic algorithm. Computer experiments show that our approaches outperform existing heuristics, in that with similar settings, our approaches often produces better solutions.

Keyword :

heuristics Design structure matrix (DSM) interrelated activities product development

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GB/T 7714 Lin, Jun , Huang, Weihao , Qian, Yanjun et al. Scheduling Interrelated Activities Using Insertion-Based Heuristics [J]. | IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT , 2018 , 65 (1) : 113-127 .
MLA Lin, Jun et al. "Scheduling Interrelated Activities Using Insertion-Based Heuristics" . | IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT 65 . 1 (2018) : 113-127 .
APA Lin, Jun , Huang, Weihao , Qian, Yanjun , Zhao, Xi . Scheduling Interrelated Activities Using Insertion-Based Heuristics . | IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT , 2018 , 65 (1) , 113-127 .
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Utilizing multi-source data in popularity prediction for shop-type recommendation EI
期刊论文 | 2018 | Knowledge-Based Systems
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It is important for an investor to determine the most suitable shop type (e.g., restaurant, cafe) given a location. Traditionally, investors determine shop types based on their subjective judgments and perceptions. However, insufficient information and cognitive limitation often lead to flawed decisions and increase investment risks. With advances in information technology, multi-source heterogeneous information and big data analytics can be utilized to provide support for making such a decision. In this paper, we propose a novel shop-type recommendation method that suggests a suitable shop type based on multi-source information collected from a business review site, a location-based navigation system and a mobile carrier. Specifically, our method first constructs the location-type matrix to alleviate the problem of incomplete data and models the location profile by considering internal and external features simultaneously. In particular, a hybrid similarity model is proposed to integrate the location profile and the commercial structure into a unified framework. Then, a location-based collaborative filtering method is developed to predict shop popularity and suggest a suitable shop type. Finally, we demonstrate the effectiveness of our method compared to several benchmark methods by applying it to a real-world dataset from China. © 2018 Elsevier B.V.

Keyword :

Collaborative filtering methods Heterogeneous information Multi-source informations Multisource data Popularity predictions Recommendation methods Shop-type recommendation Similarity measurements

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GB/T 7714 Mao, Xiaoxin , Zhao, Xi , Lin, Jun et al. Utilizing multi-source data in popularity prediction for shop-type recommendation [J]. | Knowledge-Based Systems , 2018 .
MLA Mao, Xiaoxin et al. "Utilizing multi-source data in popularity prediction for shop-type recommendation" . | Knowledge-Based Systems (2018) .
APA Mao, Xiaoxin , Zhao, Xi , Lin, Jun , Herrera-Viedma, Enrique . Utilizing multi-source data in popularity prediction for shop-type recommendation . | Knowledge-Based Systems , 2018 .
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Strategies for new product diffusion: Whom and how to target? SSCI Scopus
期刊论文 | 2018 , 83 , 111-119 | JOURNAL OF BUSINESS RESEARCH
WoS CC Cited Count: 3 SCOPUS Cited Count: 4
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This paper examines the promotional strategies for new product diffusion by leveraging peer effects among consumers. Previous studies have offered conflicting recommendations on whom to target (e.g., influentials, susceptibles, or unsusceptibles) with respect to new product promotions. Utilizing agent-based modeling and simulation (ABMS), we show that each of the proposed consumer groups can be a promising target, depending on how they are targeted, according to target size and promotion intensity. The authors further recommend the optimal combination of whom and how to target under budget constraints. Specifically, where a budget is limited, the best approach is to target as many susceptibles as possible with a weak promotion. Targeting unsusceptibles with free products should be the first choice, where the budget is large. In other cases, the best approach is to target as many influentials as possible with a moderate promotion.

Keyword :

Peer effects New product diffusion Targeting strategies New product promotion Agent-based modeling and simulation (ABMS)

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GB/T 7714 Hu, Hai-hua , Lin, Jun , Qian, Yanjun et al. Strategies for new product diffusion: Whom and how to target? [J]. | JOURNAL OF BUSINESS RESEARCH , 2018 , 83 : 111-119 .
MLA Hu, Hai-hua et al. "Strategies for new product diffusion: Whom and how to target?" . | JOURNAL OF BUSINESS RESEARCH 83 (2018) : 111-119 .
APA Hu, Hai-hua , Lin, Jun , Qian, Yanjun , Sun, Jian . Strategies for new product diffusion: Whom and how to target? . | JOURNAL OF BUSINESS RESEARCH , 2018 , 83 , 111-119 .
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Where do high-impact ideas come from? The interplay between the cumulative knowledge structures and search strategies of researchers SSCI Scopus
期刊论文 | 2017 , 55 (5) , 808-825 | MANAGEMENT DECISION | IF: 1.525
WoS CC Cited Count: 1
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Abstract :

Purpose - The purpose of this paper is to investigate the combined effects of different modalities of long-term knowledge accumulation and short-term knowledge searching on the generation of high-impact ideas. The authors aim at providing useful conclusions for academic scholars. Design/methodology/approach - Two dimensions of the cumulative knowledge structures of researchers are measured: knowledge depth and knowledge breadth. The search strategies employed by researchers are classified as local search and distant search. The authors use researchers' historical publications to measure cumulative knowledge structures. References contained in these publications serve as an indicator of knowledge searching behaviors and are used to measure search strategies. Highly cited papers with random-but-matched papers from the same journal published in the same year are adopted to test the hypotheses. Findings - The knowledge depth of researchers positively predicts the generation of high-impact ideas. Knowledge breadth has a bell-shaped relationship to the generation of high-impact ideas. Two instances of "strategic fit" between the knowledge structures and search strategies of researchers are identified; namely, knowledge breadth combines most effectively with local search, and knowledge depth combines most effectively with distant search in generating high-impact ideas. Research limitations/implications - Using article references to measure authors' knowledge search behaviors may lead to biases. Future research should perform a survey to obtain a comprehensive understanding of the knowledge search behaviors of scholars. Practical implications - A "T-shaped" knowledge structure in the long run is recommended for maximal generation of high-impact ideas. Researchers who have not adopted this optimal knowledge structure can employ a matched search strategy to leverage their existing knowledge structures. Originality/value - This paper is among the first to examine the interactive effects between the cumulative knowledge structures and short-term knowledge searching strategies of researchers. The authors have enriched the exploration and exploitation theory by adding the dimension of time into the analysis.

Keyword :

Local search Knowledge depth High-impact idea Distant search Search strategies Knowledge breadth

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GB/T 7714 Wang, Le , Lin, Jun , Yan, Jie et al. Where do high-impact ideas come from? The interplay between the cumulative knowledge structures and search strategies of researchers [J]. | MANAGEMENT DECISION , 2017 , 55 (5) : 808-825 .
MLA Wang, Le et al. "Where do high-impact ideas come from? The interplay between the cumulative knowledge structures and search strategies of researchers" . | MANAGEMENT DECISION 55 . 5 (2017) : 808-825 .
APA Wang, Le , Lin, Jun , Yan, Jie , Cui, Wentian . Where do high-impact ideas come from? The interplay between the cumulative knowledge structures and search strategies of researchers . | MANAGEMENT DECISION , 2017 , 55 (5) , 808-825 .
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Impact of interaction style and degree on the evolution of cooperation on Barabasi-Albert scale-free network SCIE PubMed Scopus
期刊论文 | 2017 , 12 (8) | PLOS ONE | IF: 2.766
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In this work, we study an evolutionary prisoner's dilemma game (PDG) on Barabasi-Albert scale-free networks with limited player interactions, and explore the effect of interaction style and degree on cooperation. The results show that high-degree preference interaction, namely the most applicable interaction in the real world, is less beneficial for emergence of cooperation on scale-free networks than random interaction. Besides, cooperation on scale-free networks is enhanced with the increase of interaction degree regardless whether the interaction is high-degree preference or random. If the interaction degree is very low, the cooperation level on scale-free networks is much lower than that on regular ring networks, which is against the common belief that scale-free networks must be more beneficial for cooperation. Our analysis indicates that the interaction relations, the strategy and the game payoff of high-connectivity players play important roles in the evolution of cooperation on scale-free networks. A certain number of interactions are necessary for scale-free networks to exhibit strong capability of facilitating cooperation. Our work provides important insight for members on how to interact with others in a social organization.

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GB/T 7714 Xie, Fengjie , Shi, Jing , Lin, Jun . Impact of interaction style and degree on the evolution of cooperation on Barabasi-Albert scale-free network [J]. | PLOS ONE , 2017 , 12 (8) .
MLA Xie, Fengjie et al. "Impact of interaction style and degree on the evolution of cooperation on Barabasi-Albert scale-free network" . | PLOS ONE 12 . 8 (2017) .
APA Xie, Fengjie , Shi, Jing , Lin, Jun . Impact of interaction style and degree on the evolution of cooperation on Barabasi-Albert scale-free network . | PLOS ONE , 2017 , 12 (8) .
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Local Opinion Heterogeneity and Individual Participation in Collective Behavior: A Reconsideration SSCI Scopus
期刊论文 | 2015 , 18 (2) | JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION | IF: 1.101
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Local opinion heterogeneity (LOH) critically influences an individual's choice of collective behaviors, such as voting and protesting. However, several empirical studies have presented different conclusions on how LOH affects such preference. In the current research, the effect of LOH is considered based on agent-based modeling and the threshold model introduced by Granovetter (1978). A series of simulation experiments and statistical analyses are conducted. Results show that LOH has an inverse U-shape effect on the likelihood of participation (whether an individual decides to participate). By contrast, the findings reveal that LOH has a monotonous effect on participation timing (when a participant makes the decision). Specifically, when LOH is high, an individual opts to participate early. These observations can be explained by the influence of LOH on the structure of social networks and by the moderating effect of the global distribution of opinions within the population.

Keyword :

Collective Behavior Agent-Based Modeling Participation Timing Threshold Model Local Opinion Heterogeneity Participation Likelihood

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GB/T 7714 Hu, Hai-hua , Lin, Jun , Cui, Wen-tian . Local Opinion Heterogeneity and Individual Participation in Collective Behavior: A Reconsideration [J]. | JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION , 2015 , 18 (2) .
MLA Hu, Hai-hua et al. "Local Opinion Heterogeneity and Individual Participation in Collective Behavior: A Reconsideration" . | JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION 18 . 2 (2015) .
APA Hu, Hai-hua , Lin, Jun , Cui, Wen-tian . Local Opinion Heterogeneity and Individual Participation in Collective Behavior: A Reconsideration . | JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION , 2015 , 18 (2) .
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Intervention Strategies and the Diffusion of Collective Behavior SSCI Scopus
期刊论文 | 2015 , 18 (3) | JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION | IF: 1.101
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This paper examines the intervention strategies for the diffusion of collective behavior, such as promoting innovation adoption and repressing a strike. An intervention strategy refers to controlling the behaviors of a small number of individuals in terms of their social or personal attributes, including connectivity (i.e., the number of social ties one holds), motivation (i.e., an individual's intrinsic cost-benefit judgment on behavior change), and sensitivity (i.e., the degree to which one follows others). Extensive agent-based simulations demonstrate that the optimal strategy fundamentally depends on the goal and time of intervention. Moreover, the nature of the social network (determined by homophily type and level) moderates the effectiveness of a strategy. These results have substantial implications for the design and evaluation of intervention programs.

Keyword :

Diffusion of Collective Behavior Social Network Agent-Based Modeling Intervention Strategy

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GB/T 7714 Hu, Hai-hua , Lin, Jun , Cui, Wen-tian . Intervention Strategies and the Diffusion of Collective Behavior [J]. | JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION , 2015 , 18 (3) .
MLA Hu, Hai-hua et al. "Intervention Strategies and the Diffusion of Collective Behavior" . | JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION 18 . 3 (2015) .
APA Hu, Hai-hua , Lin, Jun , Cui, Wen-tian . Intervention Strategies and the Diffusion of Collective Behavior . | JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION , 2015 , 18 (3) .
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Cultural Differences and Collective Action: A Social Network Perspective SSCI SCIE Scopus
期刊论文 | 2015 , 20 (4) , 68-77 | COMPLEXITY | IF: 3.514
WoS CC Cited Count: 1
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This study investigates how cultural differences on the individualism-collectivism (I-C) dimension of social networks influence the outcomes of collective action. Evidence shows that I-C values are indicators of how people construct their social networks and use strong/weak ties as a behavioral reference. Specifically, when compared with individualists, collectivists tend to hold larger strong-tie networks and endow strong ties with greater interpersonal influence. Results obtained from agent-based modeling indicate that individualistic cultures are more effective at propagating collective action when one of the two following conditions is met: (1) people have a strong motivation to participate and (2) the connectivity of the social system is low. In contrast, spread of collective action in collectivistic cultures is more effective when motivation is not strong and the connectivity of the social system is high. These findings call for a serious consideration of the role of culture in collective action. (c) 2014 Wiley Periodicals, Inc. Complexity 20: 68-77, 2015

Keyword :

cultural difference social network individualism-collectivism agent-based modeling collective action

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GB/T 7714 Hu, Hai-Hua , Lin, Jun , Cui, Wentian . Cultural Differences and Collective Action: A Social Network Perspective [J]. | COMPLEXITY , 2015 , 20 (4) : 68-77 .
MLA Hu, Hai-Hua et al. "Cultural Differences and Collective Action: A Social Network Perspective" . | COMPLEXITY 20 . 4 (2015) : 68-77 .
APA Hu, Hai-Hua , Lin, Jun , Cui, Wentian . Cultural Differences and Collective Action: A Social Network Perspective . | COMPLEXITY , 2015 , 20 (4) , 68-77 .
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Recent Advances in Concurrent Engineering Modeling EI CPCI-S Scopus
会议论文 | 2015 , 9-12 | 5th International Asia Conference on Industrial Engineering and Management Innovation (IEMI) / 4th Institute-of-Industrial-Engineers (IIE) Asian Conference
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Over the last two decades, a number of studies have examined the trade-off involved in concurrent engineering (CE), time reduction versus additional effort for downstream rework. This study presents an overview of the recent CE modeling literature that examined this trade-off. We find that most CE models are built on the assumption that development stages are dependent where the principal information exchange between consecutive design stages is unidirectional, from upstream stage to downstream stage. According to literature review and field study, we believe such assumption is reasonable, because in many situations, current execution of design stages actually occurs within two sub-stages (Testing 1 and Development 2) which are sequentially dependent. In the future, we may also build analytical models based on interdependent stages so as to better understand the impact of project properties on best CE policies and product development performance.

Keyword :

Concurrent engineering product development overlapping

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GB/T 7714 Qian, Yan-jun , Goh, Thong Ngee , Lin, Jun . Recent Advances in Concurrent Engineering Modeling [C] . 2015 : 9-12 .
MLA Qian, Yan-jun et al. "Recent Advances in Concurrent Engineering Modeling" . (2015) : 9-12 .
APA Qian, Yan-jun , Goh, Thong Ngee , Lin, Jun . Recent Advances in Concurrent Engineering Modeling . (2015) : 9-12 .
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