ERN: Consumer Behavior (Topic)最新文献

{"title":"Quantifying Search and Switching Costs in the U.S. Auto Insurance Industry","authors":"Elisabeth Honka","doi":"10.2139/ssrn.2023446","DOIUrl":"https://doi.org/10.2139/ssrn.2023446","url":null,"abstract":"type=\"main\"> I estimate demand for auto insurance in the presence of two types of market frictions: search and switching costs. I develop an integrated utility-maximizing model in which consumers decide over which and how many companies to search and from which company to purchase. My modelling approach rationalizes observed consideration sets as being the outcomes of consumers' search processes. I find search costs to range from $35 to $170 and average switching costs of $40. Search costs are the most important driver of customer retention and their elimination is the main lever to increase consumer welfare in the auto insurance industry.","PeriodicalId":212100,"journal":{"name":"ERN: Consumer Behavior (Topic)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117190715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Large Scale Study of the Small Sample Performance of Random Coefficient Models of Demand","authors":"B. S. Skrainka","doi":"10.2139/ssrn.1942627","DOIUrl":"https://doi.org/10.2139/ssrn.1942627","url":null,"abstract":"Despite the importance of Berry et al.(1995)'s model of demand for differentiated products (BLP hereafter), there are few results about its finite sample behavior. In theory, simulation experiments provide a tool to answer such questions but computational and numerical difficulties have prevented researchers from performing any realistic studies. Those Monte Carlo studies which exist focus on only one market and often take computational short-cuts.For example, Armstrong (2011) uses only 10 pseudo-Monte Carlo quadrature nodes and fixes the scale of the random coefficients. Nevertheless, by utilizing recent advances in optimization (Su and Judd, 2010; Dube et al., 2011) and multi-dimensional numerical integration (Skrainka and Judd, 2011), I develop a fast, robust implementation of BLP and show that a large-scale simulation approach is now feasible.This study estimated BLP over 320,000 times and used 94,325 CPU-hours (See [sub:Computational.Cost] for further discussion.). I compute the finite sample behavior under both the traditional BLP instruments (characteristics of rival goods) and exogenous cost shifters using synthetic data generated from a structural model for realistic numbers of markets and products. This paper, then, has two objectives: to demonstrate the power of modern computational technology for solving previously intractable problems in Economics via massive parallelization and to characterize the finite sample behavior of the BLP estimator.","PeriodicalId":212100,"journal":{"name":"ERN: Consumer Behavior (Topic)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127147856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-Range Forecasting for a Consumer Durable in an International Market","authors":"J. Armstrong","doi":"10.2139/SSRN.1969710","DOIUrl":"https://doi.org/10.2139/SSRN.1969710","url":null,"abstract":"There has been a substantial amount of interest recently in long-range planning. One necessary component of the long-range plan Is the long-range forecast. In contrast to the emphasis on the planning process, however, little attention has been given to forecasting. This study considers the problem of long-range forecasting in a situation which is of growing importance - forecasting sales for international markets.Many researchers appear to operate under the impression that causal models (i.e., models based on an analysis of underlying factors) lead to more accurate sales forecasts than those provided by naive models (i.e., projections based on historical sales data only). A survey of the research literature led to the conclusion that this confidence in causal models is virtually unsupported. One can hardly criticize firms, then, for relying primarily upon naive models for sales forecasting since these models are simpler and less expensive than causal model.This study was based on the hypothesis that causal models are superior to naive models in certain situations. The key element of these situations is that -there are 'large changes.' Long-range sales forecasting usually involves such large changes; and there are many reasons to expect that long-range forecasting for international markets is a situation in which substantial changes will occur (e.g., the Kennedy round tariff cuts and the formation of common markets.)A causal model was developed to provide long-range forecasts of the international market for still cameras. This model provided unconditional forecasts of unit camera sales by country for year t n on the basis of l) knowledge about camera sales in year t and 2) predicted changes in four causal variables from year t to t n. These four causal variables included, in order of importance, per capita income, price of cameras, number of potential buyers and quality of cameras.The predictive ability of the causal model was superior to that of a naive model purporting to represent current practice. Each model was used to provide backcasts of 1954 camera sales in 17 countries on the basis of data from 1967 to 1960 only. The mean absolute percentage error for the causal model was 23% while that for the naive model was 43%. This result was statistically significant (0? = .05); but, more importantly, it appeared to have great practical significance. An evaluation, based on very conservative subjective estimates, indicated that such an improvement in accuracy would have a present value worth in excess of one percent of a typical firm's yearly sales volume.Further support for the use of the causal model was obtained by noting that the standard errors of the estimated relationships were low (evidence of reliability), that the estimates of causal relationships from different measurement models were in rather close agreement (evidence of construct validity), and that the causal model performed well in another situation where predictions were provided fo","PeriodicalId":212100,"journal":{"name":"ERN: Consumer Behavior (Topic)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134091116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ushering Buyers into Electronic Channels: An Empirical Analysis","authors":"Nishtha Langer, Chris M. Forman, S. Kekre, Baohong Sun","doi":"10.2139/ssrn.1976098","DOIUrl":"https://doi.org/10.2139/ssrn.1976098","url":null,"abstract":"Despite many success stories, B2B e-commerce penetration remains low. Many firms introduce electronic channels in addition to their traditional sales channels but find that buyer usage of the e-channel over time does not keep up with initial expectations. Firms must understand the underlying factors that drive channel usage and how these factors change over time and across buyers. Using panel data pertaining to the purchase histories of 683 buyers over a 43-month period, we estimate a dynamic discrete choice model in a B2B setting that (i) recognizes how price, channel inertia, and inventory change over time; (ii) allows buyers to dynamically trade off these factors when making e-channel adoption decisions; and (iii) takes into account buyer heterogeneity. We find that channel usage is both heterogeneous and dynamic across buyers. Our findings reveal the dynamic tradeoff between channel inertia and the adverse price effect, which interact in opposing directions as the e-channel grows more popular over time: price increases resulting from more bids deter buyers, whereas channel inertia built from sampling experience helps retain repeat buyers for the new channel. Second, we find that the buyers' size and diversity influence purchase decisions, and the e-channel appears more attractive to small and/or diversified buyers. Based on our analysis, we postulate that the seller's allocation decisions of products across channels, if not aligned with buyer behavior, can alienate some buyers. Based on the parameter estimates from the buyer response model, we propose an improved channel allocation that enables firms to selectively attract more buyers to the e-channel and improve revenues. Channel acceptance increases as a result of smart allocation when firms understand and account for individual buyers' channel usage behavior.","PeriodicalId":212100,"journal":{"name":"ERN: Consumer Behavior (Topic)","volume":"578 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116066976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cultivating Admiration in Brands: Warmth, Competence, and Landing in the 'Golden Quadrant'","authors":"Jennifer L. Aaker, Emily N. Garbinsky, K. Vohs","doi":"10.2139/ssrn.1961808","DOIUrl":"https://doi.org/10.2139/ssrn.1961808","url":null,"abstract":"Although a substantial amount of research has examined the constructs of warmth and competence, far less has examined how these constructs develop and what benefits may accrue when warmth and competence are cultivated. Yet there are positive consequences, both emotional and behavioral, that are likely to occur when brands hold perceptions of both. In this paper, we shed light on when and how warmth and competence are jointly promoted in brands, and why these reputations matter.","PeriodicalId":212100,"journal":{"name":"ERN: Consumer Behavior (Topic)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134356069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hedonic Prices and Implicit Markets: Estimating Marginal Willingness to Pay for Differentiated Products Without Instrumental Variables","authors":"Kelly C. Bishop, C. Timmins","doi":"10.3386/W17611","DOIUrl":"https://doi.org/10.3386/W17611","url":null,"abstract":"The hedonic model of Rosen (1974) has become a workhorse for valuing the characteristics of differentiated products despite a number of well-documented econometric problems. For example, Bartik (1987) and Epple (1987) each describe a source of endogeneity in the second stage of Rosen's procedure that has proven difficult to overcome. In this paper, we propose a new approach for recovering the marginal willingness-to-pay function that altogether avoids these endogeneity problems. Applying this estimator to data on large changes in violent crime rates, we find that marginal willingness-to-pay increases by ten cents with each additional violent crime per 100,000 residents.","PeriodicalId":212100,"journal":{"name":"ERN: Consumer Behavior (Topic)","volume":"252 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133989414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating Structure Relationship from Functional and Relational Value to Behavior Intention: The Role of Satisfaction and Relationship Commitment","authors":"Sazali Abdul Wahab","doi":"10.2139/ssrn.1949212","DOIUrl":"https://doi.org/10.2139/ssrn.1949212","url":null,"abstract":"Value is a subjective construct that varies between customers, cultures and at different times. Most of the research focus on the value of physical product/service and neglect the value of relationship. This study is the first to consider customer value in terms of both functional and relational aspect. The main objective of the study is to investigate the most prominent predictor of customer behavior intention and also to examine the indirect factors (functional value and relational value) relate to the respective direct factors (satisfaction and relationship commitment) and their ability to explain customer behavior intention. Data obtained from 429 survey questionnaire were analyzed using the structure equation modeling. The results revealed that relationship commitment followed by satisfaction has a significant direct effect on behavior intention. Additionally, bootstrapping analysis confirmed that relational value has indirect effect on behavior intention through satisfaction and relationship commitment. This study highlighted the role of relational value in building the relationship commitment. Strategic guidelines are provided for managers in designing the value in stimulating the customer behavior intention.","PeriodicalId":212100,"journal":{"name":"ERN: Consumer Behavior (Topic)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115605892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}