团购网站相关外文翻译

团购网站相关外文翻译 外文翻译 原文1 Matching Models for Preference-sensitive Group Purchasing Matching buyers and sellers is one of the most fundamental problems in economics and market design. An interesting variant of the matching problem arises when self-interested buyers come together in order to induce sellers to offer quantity or volume discounts, as is common in buying consortia, and more recently in the consumer group couponing space (e.g., Groupon).We consider a general model of this problem in which a group or buying consortium is faced with volume discount offers from multiple vendors, but group members have distinct preferences for different vendor offerings. Unlike some recent formulations of matching games that involve quantity discounts, the combination of varying preferences and discounts can render the core of the matching game empty, in both the transferable and nontransferable utility sense. Thus, instead of coalitional stability, we propose several forms of Nash stability under various epistemic and transfer/payment assumptions. We investigate the computation of buyer-welfare maximizing matchings and show the existence of transfers (subsidized prices) of a particularly desirable form that support stable matchings. We also study a nontransferable utility model, showing that stable matchings exist; and we develop a variant of the problem in which buyers provide a simple preference ordering over “deals” rather than specific valuations—a model that is especially attractive in the consumer space—which also admits stable matchings. Computational experiments demonstrate the efficacy and value of our approach. Categories and Subject Descriptors: I.2.11 [Distributed Artificial Intelligence]: Multiagent Systems; J.4 [Computer Applications]: Social and Behavioral Sciences—Economics General Terms: Algorithms, Economics, Theory Additional Key Words and Phrases: stable matching, preferences, demand aggregation, group purchasing,volume discounts, daily deals, cooperative games. 1. INTRODUCTION Matching buyers and sellers is one of the most fundamental problems in economics anddeal” providers like Groupon and Living Social (and services that aggregate such deals) has propelled group discounts into the public consciousness.Group buying and demand aggregation has been studied from several perspectives, and many models have been proposed for their analysis. However, we consider a vital ingredient of group buying that has received insufficient attention in the literature, namely, the fact that buyers often have distinct preferences for the offerings of different vendors. Most matching models with volume discounts assume that vendor offerings are indistinguishable to buyers, which significantly limits their applicability. For instance,suppose two buyers X and Y are (jointly) comparing the offers of two vendors or some item: A offers a price of 10 for one unit, but a discounted price of 8 if both buy from him; and B offers a single price of 9 per unit. If A and B are indistinguishable, X and Y should cooperate and buy from A. But suppose X prefers B (with valuation 11.5) to A (valuation 10). In this case, X would prefer to stick with B unless Y offers some payment to switch vendors (Y would gladly share some of her generated surplus with X for this purpose). Without the ability to express preferences over vendors, “group buying” would not emerge even in this trivial example. market design. A wide variety of models and mechanisms have been developed that reflect different assumptions about the demands, valuations/preferences, and knowledge of the market participants and their ability to cooperate. Each leads to its own computational challenges when developing algorithms for computing stable (core) matchings,Nash equilibria, clearing prices or other solution concepts. In this paper, we address the problem of cooperative group buying, in which a group of buyers coordinate their purchases to realize volume discounts, mitigate demand risk, or reduce inventory costs. Group buying has long been used for corporate procurement,via industry-specific buying consortia or broadly based group purchasingorganizations (GPOs) [Chen and Roma 2010]. The advent of the Internet, in particular,has helped businesses with no prior affiliation more easily aggregate their demand[Anand and Aron 2003]. Consumer-oriented group purchasing has also been greatly facilitatedby the web; and the recent popularity of volume-based couponing and “dailydeal” providers like Groupon and Living Social (and services that aggregate such deals)has propelled group discounts into the public consciousness.Group buying and demand aggregation has been studied from several perspectives,and many models have been proposed for their analysis. However, we consider a vital ingredient of group buying that has received insufficient attention in the literature,namely, the fact that buyers often have distinct preferences for the offerings of different vendors. Most matching models with volume discounts assume that vendor offerings are indistinguishable to buyers, which significantly limits their applicability. For instance,suppose two buyers X and Y are (jointly) comparing the offers of two vendors for some item: A offers a price of 10 for one unit, but a discounted price of 8 if both buy from him; and B offers a single price of 9 per unit. If A and B are indistinguishable, X and Y should cooperate and buy from A. But suppose X prefers B (with valuation 11.5) to A (valuation 10). In this case, X would prefer to stick with B unless Y offers some payment to switch vendors (Y would gladly share some of her generated surplus with X for this purpose). Without the ability to express preferences over vendors, “group buying” would not emerge even in this trivial example.While matching becomes much more subtle in such models, assigning buyers to vendors in a way that triggers volume discounts, while remaining sensitive to buyer preferences, offers flexibility and efficiency gains that greatly enhance the appeal of group buying. Consider a group of businesses or buyers working with a GPO to procure supplies within a specific product category (e.g., manufacturing materials, packaging, transportation, payroll services, etc.). The GPO is able to negotiate volume discounts from a handful of suppliers or vendors, possibly with multiple discount thresholds. Buyers generally have different valuations for the offerings of different vendors (e.g., buyers may have slightly different manufacturing specifications; or may prefer the contract, payment or delivery terms of certain vendors). A suitable matching of buyers to vendors must trade off these preferences with the triggered discount prices.The same issues arise in consumer domains. Suppose a daily deal aggregator creates a “marketplace” for some product category, say, spas. Multiple spas offer deals that only trigger if a certain quantity is sold. Buyers are faced with a dilemma: they may want only one item, but are uncertain about which deal will trigger. If they only offer to buy (i.e., conditionally purchase) their most preferred spa, they may not get any deal if their preferred deal does not trigger. But if they offer on multiple spas to hedge that risk, they run the opposite risk of obtaining more items than they want. A matching model that allows consumers to specify preferences for items relative to their discounted prices provides flexibility that benefits both consumers and retailers.Our model. In broad strokes, our model assumes a set of vendors offering products (e.g., within a specific product category). Interacting with some GPO or informal buying group, vendors offer (possibly multiple) volume discounts that trigger if the group collectively buys in a certain quantity. We assume these are proposed or negotiated in advance, and take them to be fixed, posted prices. For ease of exposition, we assume buyers have unit demand, hence treat items as partial substitutes. Each buyer has valuations for each item and quasilinear utility. Since vendor prices are fixed, our aim is to find an allocation of items to buyers that maximizes social welfare (i.e., sum of buyers? utilities) given the discounts that trigger, while ensuring stability, or buyer “satisfaction” with the resulting allocation at the triggered prices. We consider two main variants of this problem. In the transferable utility (TU) model, the gains due to demand aggregation can be transferred between buyers to ensure cooperation. In the non-transferable utility (NTU) model, each buyer pays the (triggered) price of her allocated item. Both models have a role to play in specific business and consumer applications. We also consider various forms of knowledgeand recourse on the part of the buyer (e.g., whether they know only which discounts triggered, or have knowledge of the entire allocation and discount schedule). Our results. Since vendor prices are fixed given some demanded quantity, the model induces a coalitional game among the buyers, which we refer to as a discount matching game. Vendor discounts introduce significant externalities in the corresponding matching problem: this leads to the emptiness of core of such games in certain instances, both in the TU and the NTU sense. As a consequence, we consider unilateral deviations from the matching, and focus on the weaker notion of Nash stability under several different epistemic assumptions. We focus first (and primarily) on TU games. We establish that stable matchings (under all epistemic assumptions) not only exist, but that they maximize social welfare. Moreover, they can be realized using transfers only between buyers that are matched to the same vendor.We then consider computation of social welfare maximizing matchings: we show that the corresponding decision problem is NP-complete, but that, given a (fixed) set of discount prices, computing an optimal allocation can be done in polynomial time. As a result, a mixed integer programming (MIP) model of the problem can be formulated in which binary matching variables can be relaxed (as is typical in matching/assignment problems [Roth et al. 1993]), leaving a MIP whose only integer variables represent the triggering of specific discount thresholds (which, in practice, are relatively few). Experiments demonstrate the efficacy of the formulation. We then consider the NTU discount matching game, and show stable matchings exist. Finally, we consider qualitative discount matching games, a variant in which buyers do not specify valuations for items, but simply rank the deals offered (where a deal is any item and one of its discounted prices). This model is especially appealing in consumer domains, where buyers may be unable to articulate precise valuations for items, but can easily compare any two items at specific prices. As long as the rankings are rationalizable (i.e., correspond to quasi-linear preferences under some latent valuation), again stable matchings are guaranteed to exist. We do not address incentive issues with respect to reporting of buyer preferences. This is an important part of the design of such markets, but one we leave to future research. Truthful reporting of valuations is commonly assumed in work on procurement and inventory management (see below), where parties interact repeatedly. Similarly, we assume that sellers simply post (base and discounted) prices without regard to strategic interaction with buyers. While interactions between sellers w.r.t. Strategic price-setting is also of interest, the way in which “between-seller” equilibrium prices and discount schedules are set does not impact group buying decisions.Related work. Assignment games and matching markets have a rich history, and the literature is rife with connections between various forms of (individual and coalitional) stability, competitive equilibrium prices, etc. [Shapley and Shubik 1971; Gale and Shapley 1962; Demange et al. 1986]. While a general discount market model would consider strategic behavior on the part of both buyers and sellers, we take seller prices as given and focus on the one-sided problem that results by considering only the strategic behavior of buyers. Of special relevance is work on assignment models, auctions, and procurement optimization that deals explicitly with quantity discounts, buyer/bidder cooperation, and externalities in assignments. Within the context of auctions, Kothari et al. [2005] consider multi-unit (reverse) auctions with discount tiers, and use the VCG mechanism, but consider only a single buyer with no preferences over sellers.1 Conversely, Matsuo et al. [2005] model theproblem of a single seller offering multiple items, each with discount schedules. Buyers with combinatorial preferences bid for items, and allocations/prices are set using VCG; unlike our model, the discounts are not “posted prices” in the usual sense, but are merely used as reserve prices. While the mechanism and assumptions are quite different, and computation is not considered, their motivations are similar to ours. Leyton-Brown and Shoham [2000] study bidding clubs which collude in auction mechanisms to lower prices, and devise payment schemes that induce participation. Author: TYLER LU, CRAIG BOUTILIER Nationality: Canada Originate from: Association for Computing Machinery, Inc.ISBN: 978-1-4503-1415-2 Pages723-740 译文1 团购匹配模型 匹配买家和卖家，是经济学和市场最根本的问之一。当具有个人利益的买家聚到一起以促使卖家提供批量折扣时，一个有趣的匹配问题的变种开始出现，而且在购买财团和最近在消费群的优惠券空间(例如，Groupon的)中都很普遍。我们就以一个一般的模型来考虑这个问题，其中团体或购买财团正面临着来自多个供应商提供的批量折扣，但小组成员对于来自不同供应商的产品有着不同的喜好。与一些现有的打着批量折扣的匹配博弈不同，结合不同消费者的喜好和不同折扣会是匹配博弈的核心，同时在转让和不可转让的都有实用意义。因此，与合并稳定性相反，我们在各种认知和转账/付款的假设下提出了几种Nash稳定的形式。我们调查并计算了买方福利的最大化匹配计算以及表明存在一个可以支持稳定匹配的特别理想的形式，即价格转移(价格补贴)。 涉及的专业领域:算法，经济学，理论学 其他关键词和短语:稳定的匹配，喜好，需求聚集，团购，批量折扣，每日交易，合作博弈。 引言 匹配买家和卖家，是经济学和市场设计最根本的问题之一。各种各样的模式和机制已经被用以放映需求假设、估值与偏好、以及反映市场参与者的知识和合作的能力。每个计算稳定的匹配(核心)，纳什均衡，结算价格或其他解决概念开发算法时，导致其自身的计算挑战。 在本文中，我们试图解决合作团购的问题，其中这些团队中的购买者协调其购买为实现批量折扣，降低需求风险，或降低库存成本。团购早已被用于企业采购，通过特定产业购买财团或广泛基于团购组织。互联网的出现，尤其帮助企业事先没有隶属关系，更容易聚集他们的需求。以消费者为导向的团购，因为互联 网获得了很大的便利。而且最近流行的优惠券、像Groupon等供应商提供的“每日交易”和社会服务，极大地推动公众团体折扣的意识。 我们可以从多个角度来研究团购和聚集需求，同时还可以用多个模型来对其进行分析。然而，我们认为团购的一个关键要素就是没有得到足够的重视，即事实上，购买者往往对不同供应商提供的铲平有不同的喜好。而大多数具有批量折扣的匹配模型均假设厂商提供的产品是无法区分，这极大地限制了购买者的不同喜好的需求。例如，假设两个买家X和Y对来自两家供应商提供的产品进行比较:A供应商提供每件10个单位的价格，但购买两件的折扣价就是每件8个单位的价格;B供应商提供每件9个单位的价格。如果A和B提供的商品是相似的，X和Y应该合作，并购买A提供的商品。但是，假设X更喜欢B提供的商品(与估值11.5 )，与 A提供的商品(估值10 )相比。在这种情况下，X宁愿坚持与B ，除非y提供的一些支付切换供应商(Y很乐意分享一些她产生盈余为此目的与X ) 。如果供应商不能考虑消费者偏好问题， “团购”是不会实现的，即便在这个简单的例子中。 虽然匹配变得更加微妙在这种模型中，分配买家向供应商用批量折扣的方式来触发，而其余敏感的买家喜好、提供了灵活性和效率的提高，也将大大提升产品的团购吸引力。我们可以考虑利用团购组织，促使企业或购买者的在一个特定的产品类别(例如，制造材料，包装用品，运输，工资服务等)中进行产品供给。团购组织是能够与少数供应商协商批量折扣，可能有多个折扣的阈值。购买者对不同厂商的产品(例如，买家可能略有不同的制造规格;或可能更喜欢某些厂商的，付款或交付条款)有不同的估值。一个合适的买家匹配向供应商必须权衡这些偏好与触发的折扣价格。 同样的问题出现在消费者领域。假设每天大量交易的聚集为一些产品类别创建了“市场”一说，比如，温泉。多个水疗中心在只有达到一定数量的消费时才会提供一些优惠。消费者都面临着一个难题:他们可能只需要一个项目，但不确定哪些交易将触发。如果他们只提供给购买(即有条件购买)他们最喜欢的水疗中心，他们可能得不到任何优惠，如果他们的首选交易不会触发。但是，如果他们提供的多个温泉，可以减少这种风险，他们执行比消费者想要更多的项目，而 不是相反的风险。匹配的模式，让消费者以相对优惠价格为指定喜好项目并提供了灵活性，对消费者和零售商均有利。 我们的模型 在广招中，我们的模型假定一组厂商提供的产品(例如，在一个特定的产品类别)。一些团购组织与非正式的购买群体的互动，可能触发供应商提供(可能有多个)批量折扣，如果该团体购买一定的数量。我们假设这些建议被提前告知购买者们，并带他们到固定的、制定价格的市场。为了便于，我们假设买家有不同的需求。每个买家都有每个项目的估值及拟线性效用。 由于供应商的价格是固定的，我们的目标是要找到买家，项目分配实现社会福利最大化(即买家的效用的总和)，同时确保稳定，买方满意的最终价格分配。我们认为这个问题的两个主要变量。在转让实用(TU)模型中，由于需求聚集，收益可以在买家之间转移，以确保合作。在不可转让的实用(NTU)模型中，每个买家支付各自分配的项目价格。这两种模型都在具体的业务和消费类应用中起着各自作用。我们还得考虑各种形式的知识和对买方部分的追索权(例如，他们是否知道只有折算的触发，或对整个分配和折扣计划有了解)。 作者:TYLER LU, CRAIG BOUTILIER 国籍:加拿大 出处:计算机协会 出版 ISBN: 978-1-4503-1415-2 第723-740 页 外文翻译 原文2 "Shared Joy is Double Joy": The Social Practices of User Net works Within Group Shopping Sites ABSTRACT Group-shopping sites are beginning to rise in popularity amongst eCommerce users. Yet we do not know how or why people are using such sites, and whether or not the design of group-shopping sites map to the real shopping needs of end users. To address this, we describe an interview study that investigates the friendship networks of people who participate in group-shopping sites (e.g., Groupon) with the goal of understanding how to best design for these experiences. Our results show that group-shopping sites are predominently used to support social activities; that is, users do not use them first and foremost to find „deals.? Instead, group-shopping sites are used for planning group activities, extending and building friendships, and constructing one?s social identity. Based on these findings, we suggest improved social network integration and impression management tools to improve user experience within group-shopping sites. ACM Classification Keywords H.5.2 INTRODUCTION Electronic commerce (eCommerce) has rapidly transformed over the last several years with the emergence of social networks, app market places, and the proliferation of smart phones. One emerging area of eCommerce is group-shopping sites, such as Groupon, LivingSocial, Plum District and Half Off Depot. These sites entice consumers with wholesale prices and are built on a business model that combines coupon discounts and group-buying In most cases, users browse or receive notices (e.g., in email, phone notifications) about current shopping specials that require a certain number of users to purchase the item in order to receive the reduced price. People then forward these notices to friends, family, or others who they think might purchase the item as well. Once purchased, users redeem a printable voucher from the business to receive their deal. Groupon Inc., the largest group shopping company online grew revenue by 223% percent in 2010 and generated more than $700 million in revenue with a presence in more than 150 markets in North America and more than 100 markets in Europe, Asia, and South America. While online group-shopping sites are becoming large players within the eCommerce sphere, we still know very little about how people are actually using them and to what extent the sites actually support the real needs of shoppers. Hillman et al.?s study of trust in mobile commerce (mCommerce) revealed that small friendship networks of online shoppers exist; yet they do not elaborate on the details of how they shop and how well group-shopping sites support their practices Understanding how users shop within these group shopping sites will provide us with a deeper understanding of the changes occurring within eCommerce and allow us to design shopping experiences more tailored to the needs of real end users. To address this, we investigated the social dynamics of friendship networks: groups of self-selecting individuals who jointly participate (at varying degrees) in shopping for products or services online. Our focus was on the perspective from an individual within the friend network. Based on semi-structured interviews with nineteen people, we document the details of friendship networks, their core shopping practices, and the social implications formed as a result of their shopping behaviour. Surprisingly, we found that the main usage of group-shopping sites was often not about the shopping. That is, the goal of using the sites was not first and foremost about obtaining products or services. Instead, group-shopping users exhibited a larger set of social behaviours focused on social activities, such as event planning, building relationships, and identity construction—similar to activities found within social media sites. The challenge, however, is that the tools built into group-shopping sites are not focused on the social activities we uncovered in the same way that social networking sites and social media directly support group and social networks. This suggests a compelling avenue of interface design for group shopping that is focused more around friend networks and social activities, while still supporting the core routine of shopping as a group. RELATED WORK There exists a variety of research on general shopping and eCommerce. We discuss this first and then narrow in on existing studies of group shopping and buying. Shopping and eCommerce Consumers? behaviours consists of three distinct activities as it relates to commerce: shopping, buying, and consuming . For our purposes, we refer to „shopping? as the first two of these activities as they are often highly-interlinked when it comes to eCommerce . Within this act of shopping, Tauber has identified both personal and social motivations for people to go to stores and shop. Personal motivations includes aspects such as diversion, self-gratification, physical activity, and sensory stimulation, while social motivations include a desire to have social experiences outside of the home, the need to feel a certain social status, and desires to exhibit one?s own authority (by purchasing something) . Turning to eCommerce, Roham and Swaminathan developed a typology of online shoppers based on their shopping motivations. Types of shoppers included: convenience shoppers (motivated by convenience), variety seekers (motivated by variety across brands), balanced buyers (motivated by both convenience and variety), and store-orientated shoppers (motivated by physical store location). Our study reveals a new type of online shopper, motivated by social activities and impression management. The emergence of online shopping has forced retail businesses to no longer just compete on price, selection and extended hours . eCommerce has forced retail to engage in "entertailing"—entertainment and retailing—to remain competitive. Entertailing involves leveraging "bricks and mortar" advantages , such as face-to-face interactions and a physical space, to have the customer be engaged longer and potentially spend more money. This same concept of "entertailing" can also be carried over to eCommerce in the form of increased dynamic experiences. Childers et al. tells us that "a technology orientated perspective that attempts to treat shopping media as cold information systems, rather than hedonic environments, is likely to be fundamentally misguided, especially for products with strong hedonic attributes" . A lot of research has been done to explore trust in eCommerce. The assumption is that online shopping is often risky because people must provide confidential information (e.g., credit card details) on the web, there is no physical store to go to if problems arise, and there is a lack of human interaction (which may help to promote trust and security) . As a result, researchers have suggested various trust models that focus on suggesting mechanisms to ensure trustworthiness in eCommerce sites. These include building trust through similarities between the company and consumer, creating a history of past transactions, and presenting a public presence that is respected and shows integrity . We also see that, as it relates to mobile commerce, small social networks (e.g., friends, family) provided a persuasive impact on trust while shopping on a mobile device . This was a result of the shoppers trusting the shopping recommendations they received from friends, which translated into trusting the company offering the product . Group Shopping and Buying The idea of shopping with others is not a new concept. Studies by Miller et al. in the late 1990s show that even though most people preferred to shop alone, there were times when people highly valued being able to shop with friends, partners, and other family members . This was despite findings showing that shopping with others, in particular family members, would often create interesting social challenges (e.g., teenagers shopping with parents) . We also see many companies developing marketing strategies focused on the idea of „group shopping?. For example, offline "club plans", such as those created by the Great Atlantic & Pacific Tea Company and the Larkin Company date back to as late as the 1800s . Their online counter-parts, such as Mobshop, Mercata and Letsbuyit, have been trying to achieve the success Groupon currently has since the late 1990s. Research on „user network shopping? describes how people in „virtual communities? discuss and influence the shopping behaviors of others . Here virtual communities relate to people who discuss products and shopping over computer-mediated communication systems such as Internet message boards, online chat rooms, and virtual worlds. Study findings show that groups of individuals in these communities do not shop together online but instead influence the purchasing behaviours of others in the community by suggesting normative behaviours . Thus, the idea of a virtual community is distinctly different than the shopping networks we describe. Author: Serena Hillman, Carman Neustaedter, Carolyn Pang, and Erick Oduor Nationality: Canada Originate from:Association for Computing Machinery, Inc.ISBN: 978-1-4503-1899-0 Pages 2417-2426 译文2 “分享的快乐是双倍的快乐”:用户在团购网站上的社会活动 摘要 团购网站随着电子商务的普及开始兴起。然而，不管团购网站的设计是否能 真实反映终端用户的需求真正，我们仍然不知道为何人们都在使用这样的网站。 为了解决这个问题，我们进行研究，通过对参加网上团购的用户的社会网络关系 的分析从而更好地理解这种现象。通过研究结果表明，团购网站主要被用于社交 活动;也就是说，用户不使用它们，首先要找到'交易'。相反，团购网站用于规划小组活动，扩大和建立友谊，构建一个人的社会身份。基于这些发现，我们建议提高社交网络整合和印象管理手段，提高团购网站的用户体验。 关键词 电子商务，购物,团购，印象管理，社交购物，社交电子商务的用户界面,以用户为中心的设计,ACM分类关键词,H.5.2 引言 电子商务开始随着社交网络、应用程序市场、以及智能手机的出现而开始转变。一个电子商务的新兴领开始出现，即团购网站，如Groupon, LivingSocial, Plum District和 Half Off Depot。这些网站吸引以批发价格吸引了大量客户，同时都建立在这种结合折扣和团购的商业模式上。在大多数情况下，用户浏览或接收通知(例如，电子邮件，电话通知)关于当前购物精品的一些优惠情况，并被告知需要有一定数量的用户购买该项目，才能获得降价。于是人们提出这些通知给朋友、家人或其他他们认为可能购买该项目。用户一旦购买，赎回业务打印的优惠券，接受他们的处理。团购网站Groupon，网上购物公司最大的群体，在2010年收入增长223 , ，超过700亿美元的收入。 虽然购物网站正在成为电子商务领域的大范围内的玩家，我们仍然很少了解有多少人真正使用它，以及网站是否能真正支持消费者的真正需求。关于对信任与移动电子商务关系的研究表明，网上购物者很少存在友谊。了解这些参加网上团购的用户可以让我们设计的购物体验更加贴近真正的最终用户的需求。 为了解决这个问题，我们研究了社交网络关系;团购用户的选择偏好和倾向。我们的重点是从个体的角度来看的社交网络关系。通过对19个人的采访调查，我们可以了解其核心购物的做法，以及他们的购物行为对社会的影响。令人惊讶的是，我们发现团购的主要用途通常不是购物。即，使用网站的目标是首先获得产品或服务。相反，团购用户呈现出一大组社会行为更加专注于社交活动，如活动策划、建立关系、建设类似内发现社交媒体网站的活动和身份的社会行为。然而，我们所面临的挑战，不是用同样方式在团购网站中建立工具去集中用户的社会活动。这表明一个好的的团购网站，更注重周围朋友网络和社会活动的途径，同时还支持购物作为一个群体的核心程序。 相关领域 其实，已经存在各种对于一般购物和电子商务的研究。我们讨论这个，然后再缩小范围，讨论一下有关团购和购买的相关研究。 购物和电子商务 当涉及到电子商务，消费者的行为，由三种不同的行为组成:购物，购买和消费。对于我们而言， “购物” 是首选话题，因为他们往往是跟电子商务非常相通的。在购物这种行为中，Tauter已经确定了人们去商店购物的个人和社会的动机。个人动机包括如分流，自我满足，体力活动和感官刺激的方面，而社会的动机包括渴望有家庭以外的社会经验，需要一定的社会地位的感觉。谈到电子商务， Roham 和 Swaminathan根据他们的购物动机制定了网上购物者的类型。消费者的类型包括:便利购物者(动机方便)、各种求职者(出于各种跨品牌)、均衡的购房者(出于方便和品种)、和专卖店为导向的消费者(出于物理存储位置)。我们的研究揭示了一种新型的网上购物者，出于对社会活动和印象管理的动机。 我们已经做了很多的研究，以探讨在电子商务中的信任。假设，网上购物通常是危险的，因为人必须提供机密信息(例如，信用卡详细信息)的网站上，如果出现问题没有实体店可以去，还有就是缺乏社会联络(这可能有助于增进信任和安全)。因此，研究人员提出了各种信任模型，重点提示机制，以确保诚信的电子商务网站。这些措施包括通过相似的公司和消费者之间建立信任，创造一个过去的交易历史，并提出了公众的存在，那就是尊重和显示完整性。我们也看到，随着移动商务中的小型的社交网络(例如，朋友，家人)使用移动设备购物，说明电子商务在消费者心中获得一定的信任。 团购和购买 于他人一起购物并不是一个新的概念。 Miller在 20世纪90年代中后期进行的一项研究表明，尽管大多数人宁愿独自到店去购物，有时候人们还是更愿意和朋友、合作伙伴和其他家庭成员一起去商店购物。尽管这个发现是与他人购物，特别是家庭成员，往往会创造出有趣的社会挑战的结果(例如，青少年与父母购物)。我们也看到很多企业制定市场营销策略专注于'团购'的想法。例如，脱机“俱乐部计划”，如那些可以追溯到19世纪后期建立的大西洋公司、太平洋茶叶公司 和拉金公司 。他们的网上反对者，比如Mobshop，Mercata Letsbuyit的，一直在努力实现Groupon的成功。 研究用户网络购物“介绍如何在”虚拟社区“人讨论和购物行为影响他人的。虚拟社区与这里讨论的产品和购物的人谁在以计算机为媒介的通信系统，如互联网留言板，在线聊天室，和虚拟世界。研究结果表明，在这些社区的个人，团体不一起购物在线社区的其他人的购买行为，而是影响，建议规范的行为。因此，比我们所描述的网络购物，虚拟社区的想法是截然不同的。 作者:Serena Hillman 国籍:加拿大 出处:计算机协会 出版 ISBN: 978-1-4503-1899-0 ISBN: 978-1-4503-1899-0 第2417-2426 页