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1.
This article examines peer influences from network relationships within a social network game (i.e., embeddedness) and across such games (i.e., multiplexity). Drawing on social influence theory, we develop a bivariate Poisson model of users’ repeated visits and latent attrition that accommodates peer interaction after controlling for homophily. We estimate the model using data from two social network games with considerable overlap among network members. We find that friends who are only multiplex across games exert greater peer influence on users’ game visits than members who are embedded within a single game. We also determined that ignoring network multiplexity across games may lead firms to mistarget users due to biased peer influences of embedded friends. This result provides an unresearched explanation—strength of peer influence—for the mixed findings in previous literature on network embeddedness. We utilized our results to conduct several scenario analyses to demonstrate how firms can effectively manage users’ engagement and target users in multiple social network games.  相似文献   
2.
Thanks to the expansion of network technologies and the coupling of smartphone hardware, younger generations have unparalleled access to a diverse range of information and interactive communication opportunities. Despite voluminous research on the causes of social network exhaustion and privacy invasion, limited academic attention has been devoted to understanding the driving forces and contributing factors for discontinuing usage of smartphone app. Drawing on the cognition-affect-conation paradigm, the present research proposes a conceptual research model to examine how information overload and communication overload effect social network exhaustion, privacy invasion, and ultimately, smartphone app users' intentions to discontinue usage. The study evaluates data from 442 smartphone app users, employing statistical analyses to demonstrate that both information overload and communication overload significantly impact users' exhaustion and privacy invasion. Additionally, social network exhaustion and privacy invasion are two major predictors of smartphone app discontinuance intention. By identifying the influential factors and causes of younger generations' discontinuous usage intention of smartphone app, this study meets the need for a thorough assessment of the social network exhaustion and privacy invasion phenomena. The findings may potentially enhance comprehension of the discontinuation intention phenomenon in the context of cognitive overload. Furthermore, they may provide novel insights for practitioners regarding effective strategies conducive to managing mobile social network adoption behavior, as well as the preservation of engagement levels among young users in mobile-saturated societies.  相似文献   
3.
山秋月  吴永强 《科技和产业》2023,23(14):223-227
针对全货运航空公司,研究其货运航线网络的构建问题。基于单分配严格枢纽航线网络,对传统模型进行改进。以各航线上货物的委托运输成本和自有机队的运输成本,取代传统的单位运输成本和折扣因子,考虑枢纽点的中转成本和载运率对路径选择的影响。结合航空货运夜航的特征考虑各机队夜间可用时间的限制,以总成本最小为目标,构建数学模型,采用LINGO优化软件求解,验证模型的有效性,为全货运航空公司构建货运航线网络提供参考。  相似文献   
4.
基于转移概率和网络联系的辽宁省农村居民点适宜性评价   总被引:2,自引:0,他引:2  
[目的]农村居民点适宜性评价在农村居民点调控、规划和预测中具有基础作用,且农村居民点适宜性评价应顾及农村居民点之间的社会经济活动联系。[方法]以辽宁省为研究区,首先运用逐步Logistic回归模型构建农村居民点转移概率,其次运用网络分析方法确定农村居民点图斑间的网络联系强度,最终通过加权求和方法确定农村居民点转化概率,进行农村居民点空间布局适宜性评价。[结果]辽宁省农村居民点可以划分为高度适宜类、较适宜类、一般适宜类和不适宜类4类,分别占农村居民点总面积的比例为28.18%、31.32%、13.26%和27.24%;从各地貌分区来看,高度适宜类主要集中分布在中部平原地区和东部山地丘陵区中的南方沿海地区,而不适宜类整体分布则较为零散;辽宁省中部平原区位条件好,东部沿海地区区位条件也较好,西部山地丘陵区地区较差。[结论]研究方法和结论有助于全面把握农村居民点社会经济与区位适宜性特征,为农村居民点科学规划提供科学指导。  相似文献   
5.
随着网络技术的快速发展以及各种新网络业务的出现,网络的规模日益扩大和复杂。同时,各种网络服务对于网络可靠性的要求也逐渐提高,这就对网络的维护提出了更高的要求。在这种情况下,传统的网络维护模式逐渐不能适应现代网络发展的需求。针对现代大型网络的故障诊断问题,利用大数据分析技术,设计并完成了一套整体的智能化故障诊断系统。在此系统中,针对不同的故障类型,利用能够获取到的数据类型,针对性地设计了相关的故障诊断模块和算法。系统整体基于开源的数据处理平台构建,具备良好的可扩展性。通过实际案例数据的验证,结果表明此系统具备良好的处理实际网络故障的能力,将大数据分析技术应用于网络故障诊断领域也具备较强的可行性。  相似文献   
6.
This research looks into the innovative activities of subunits of large non-U.S firms in the U.S from 1969 to 1995, suggesting that the innovations in the subunits of multinational corporations are closely linked to their specializations in General Purpose Technologies (GPTs). GPTs enable recombining knowledge from different domains on an international scale, and that the specialization of innovations in GPT fields within a subunit is positively associated with the innovative capacity at large, along with the degree of technological diversification of that specific subunit. As firms expand geographically to tap into local innovation centers to develop new growth alternatives, specialization of GPTs in these firms actually facilitates further geographical dispersion of innovative activities across locations. Lastly, additional specializations of innovations in GPT fields within the host innovation centers does help in attracting innovation activities of firms from a wider range of industries.  相似文献   
7.
采用博弈论的方法,考虑声誉效应对博弈双方效用、策略的影响,建立信号博弈模型,并分析精炼贝叶斯均衡,证明声誉水平、对声誉的态度以及技术市场价值的高低是影响建立合作关系的重要因素。探讨双方建立合作关系的行为策略,提出实现合作达成双赢的建议。  相似文献   
8.
大众传播媒介及农业信息服务网络通过环保信息传播可在潜移默化中培养农户的亲环境价值观,进而影响农户的亲环境行为。基于信息传播培养理论,整合计划行为理论和“信念—价值—规范”理论构建亲环境行为理论模型,并采用甘肃省19个县(区)542户样本农户的调研数据进行验证,结果显示:环保信息的有效传播可以潜移默化地强化农户的亲环境价值观,农户的亲环境价值观、行为态度、主观规范、知觉行为控制及责任归属均对其亲环境行为有显著的正向预测作用,农户经营规模和专业化水平对其亲环境行为也有显著正向影响。应提高农户生产经营的规模化和专业化程度,加强对农户亲环境价值观及主体责任认知、亲环境行为知识和技能等方面的教育和培训,并充分发挥农村干部、党员、能人等的带头示范作用,以有效促进农户亲环境行为。  相似文献   
9.
To explore popularly visited tourist locations, travel movement patterns, and movement points, this study collected samples of 321 Chinese tourists and 337 Japanese tourists who were visiting major tourist destinations in Seoul and its vicinity in South Korea. Results of analyzing movement patterns showed that Japanese tourists tend to be clustered around popular attractions, whereas Chinese tourists tend to spread over a larger area of attractions. Some specific shopping and amusement attractions were the locations most popularly visited by both groups. The start points and end points in the two groups’ itineraries were dissimilar overall, even though their patterns were similar in regard to major preferred tourist attractions. Thus, the findings of this study have the potential to contribute to understanding spatial mobility in a tourism destination through tracking tourists’ movement patterns.  相似文献   
10.
The objective of this paper is twofold. First, it develops a prediction system to help the credit card issuer model the credit card delinquency risk. Second, it seeks to explore the potential of deep learning (also called a deep neural network), an emerging artificial intelligence technology, in the credit risk domain. With real-life credit card data linked to 711,397 credit card holders from a large bank in Brazil, this study develops a deep neural network to evaluate the risk of credit card delinquency based on the client's personal characteristics and the spending behaviours. Compared with machine-learning algorithms of logistic regression, naive Bayes, traditional artificial neural networks, and decision trees, deep neural networks have a better overall predictive performance with the highest F scores and area under the receiver operating characteristic curve. The successful application of deep learning implies that artificial intelligence has great potential to support and automate credit risk assessment for financial institutions and credit bureaus.  相似文献   
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