A new approach to validate customer satisfaction multi-item measures: the case of shopping goods

In the field of marketing many objects of interest exist that are not directly observable, nevertheless they can be measured through multi-item measurement scales. These instruments are extremely useful and their importance requires accurate development and validation procedures. The traditional marketing literature highlights specific protocols along with statistical instruments and techniques to be used for achieving this goal. For example, correlation coefficients, univariate and multivariate analysis of variance and factorial analysis are widely employed with this purpose. However, these statistical tools are suitable for metric variables but they are adopted even when the nature of the observed variables is different, as it often occurs, since in many cases the items of which the scale is made up are ordinal. Latent class analysis takes explicitly into account the ordinal nature of the observed variables and also the fact that the object of interest is unobservable. The aim of this paper is to show how latent class analysis can improve the procedures for developing and validating a multi-item measurement scale for measuring customer satisfaction with reference to a shopping good, that is a good characterized by a high level of involvement and an emotional learning, linked to the lifestyle of the customer. The latent class approach explicitly considers both the ordinal nature of the observed variables and the fact that the construct to be measured is not directly observable. Applying appropriate latent class models, important features such as scale dimensionality, criterion and construct validity can be better assessed while evaluating the scale.     

数据挖掘中有序资料间距差异的量化与聚类分析

本文针对数据挖掘中的多分类有序资料,提出了用秩分析的方法对其间距差异作出界定。在秩分析的基础上,将有序定性资料定量化,并用于聚类分析。最后,利用该方法对大学生隐性教育调查资料进行了剖析。     

家庭生命周期对农户土地规模经营的影响分析——基于福建农村的调查数据

基于福建农村的调查数据资料,从家庭生命周期这一全新的角度出发,运用有序Prob-it模型就家庭生命周期对农户土地规模经营的影响进行实证分析,结果显示:家庭生命周期对农户土地规模经营具有显著的影响,并且在家庭生命周期的不同阶段,各类家庭土地规模经营的意愿强度不同。总体而言,成长中的核心家庭土地规模经营的意愿要强于其他类型家庭,扩大家庭的土地规模经营意愿最弱。     

Extremity in horizontal and vertical Likert scale format responses. Some evidence on how visual distance between response categories influences extreme responding

In four survey experiments we show that people generally answer more extremely to survey items presented in vertical versus horizontal Likert formats. Our findings suggest that this effect may be at least partly driven by differences in the visual range spanned by the response scale (i.e. the visual distance between endpoint response categories is larger in horizontal than in a vertical format). In addition, compared to traditional horizontal Likert data, vertical Likert data contain more variance, which is mainly non-substantive. As a result, data obtained with scale formats that have different distances between response categories (as is typically the case for vertical vs. horizontal formats) may lead to differences in measurement model parameter estimates like residual terms, and in some cases factor loadings and construct correlations. Based on these results, we provide recommendations on the use of response scale formats in online surveys, bearing in mind that several online survey tool providers promote the use of vertical Likert formats and even automatically change traditional horizontal formats of Likert-type items to vertical Likert formats when viewed on small screens (e.g., on mobile phones).     

Unlocking competitiveness through scent names: A data-driven approach

Naming a product’s scent is a key decision. The same scent can be interpreted differently when different names are assigned to it. Thus, choosing the right scent name can increase competitiveness by successfully appealing to desired consumer segments. We propose that such decisions should be data driven (i.e., on the basis of competitors’ offerings and consumers’ preferences) and provide guidelines on how to assign scent names to products in home care and personal care product categories, focusing on capturing market segments. Based on a large web-based dataset of scented products across multiple brands and categories, this article is the first to construct a typology of scent names empirically: unscented, concrete, abstract, and proprietary. After examining firms’ assortments of scented products with different names across 12 categories and comparing them with consumers’ preferences concerning such assortments, we identify major gaps. Overall, consumers demand far more unscented products and products with abstract names than currently offered; however, preferences for products with proprietary names are mostly aligned. Strategic recommendations center on naming scented products to better align supply and demand in the scented product market and capture new market opportunities.     

Ridit分析在老年人健康状况研究中的应用

老年人健康状况研究中常常会遇到各种等级变量的分组比较,如健康状况自我评价年龄间、性别间、城乡间的比较、当采用原始数据进行分组比较时,通常只能说明等级构成上的不同,却很难判别各组的好差或高低。Ridit分析是一种用来处理等级变量的统计分析方法,平均Ridit值作为一个指标用于处理等级资料具有简单明了、易于理解、便于比较的特点。     

What Makes a New Business Start-Up Successful?

This paper seeks a good measure of new business performance, and then explains this measure by various dimensions of business strategy. Three criteria are used to create a one dimensional ordinal ranking of high, medium and low performance for new business starts: employment growth; return on capital employed; and labour productivity. It is shown that statistical cluster analysis provides a convincing separation of a sample of new business starts into high, medium and low performance categories, using a minimum distance criterion for clustering. An ordinal logit model (with selection) is then used to explain this performance ranking. The results indicate that many widely discussed features of small business strategy have little, or even negative, impact on performance. Of the numerous aims that owner managers may adopt (survival, growth etc.), only one appears to have a major impact on performance; the pursuit of the highest rate of return on investment. Many entrepreneurial perceptions of their own capabilities appear false or unimportant, with the exception of organisational features and systems.     

Planning for self-employment at the beginning of a market economy: Evidence from individual data of East German workers

We investigate the plans of individual workers concerning future self-employment in the former German Democratic Republic shortly before the economic, monetary and social union in June/July 1990. Our data base is the Socio-Economic Panel East. We find that the desire to become an entrepreneur is basically determined by individual and household characteristics, including income and asset indicators, and not as much by the current job situation of the individual. The work experience attained in the socialist economy seems to be irrelevant for the decision to become self-employed in a market economy. Furthermore, we find evidence of barriers to entry which may come from capital market constraints and institutional restrictions. We also present an estimation of the determinants of the probability of being self-employed in Summer 1990. Due to institutional restrictions we find only a few individual characteristics to be important.For estimation, we use the binary and the ordinal logit model. The corresponding stochastic assumptions are tested extensively using pseudo-Lagrange multiplier tests against omitted variables, non-linearity, asymmetry of distribution, and heteroscedasticity.     

How did COVID-19 change what people buy: Evidence from a supermarket chain

This research takes a retrospective view of the COVID-19 pandemic and attempts to accurately measure its impact on sales of different product categories in grocery retail. In total 150 product categories were analyzed using the data of a major supermarket chain in the Netherlands. We propose to measure the pandemic impact by excess sales – the difference of actual and expected sales. We show that the pandemic impact is twofold: (1) There was a large but brief growth at 30.6% in excess sales associated with panic buying across most product categories within a two-week period; and (2) People spending most of their time at home due to imposed restrictions resulted in an estimated 5.4% increase in total sales lasting as long as the restrictions were active. The pandemic impact on different product categories varies in magnitudes and timing. Using time series clustering, we identified eight clusters of categories with similar pandemic impacts. Using clustering results, we project that product categories used for cooking, baking or meal preparation in general will have elevated sales even after the pandemic.     

The CAR Method for Using Preference Strength in Multi-criteria Decision Making

Multi-criteria decision aid (MCDA) methods have been around for quite some time. However, the elicitation of preference information in MCDA processes, and in particular the lack of practical means supporting it, is still a significant problem in real-life applications of MCDA. There is obviously a need for methods that neither require formal decision analysis knowledge, nor are too cognitively demanding by forcing people to express unrealistic precision or to state more than they are able to. We suggest a method, the CAR method, which is more accessible than our earlier approaches in the field while trying to balance between the need for simplicity and the requirement of accuracy. CAR takes primarily ordinal knowledge into account, but, still recognizing that there is sometimes a quite substantial information loss involved in ordinality, we have conservatively extended a pure ordinal scale approach with the possibility to supply more information. Thus, the main idea here is not to suggest a method or tool with a very large or complex expressibility, but rather to investigate one that should be sufficient in most situations, and in particular better, at least in some respects, than some hitherto popular ones from the SMART family as well as AHP, which we demonstrate in a set of simulation studies as well as a large end-user study.     

A Sorting Model for Group Decision Making: A Case Study of Water Losses in Brazil

Many water supply systems in Brazil have serious problems related to the high index of water losses, which provokes financial and environmental impacts. This is an immediate consequence of an inadequate maintenance plan, allied to natural and budgetary constraints. In addition, in these types of problems it is commonplace to consider the opinions of many managers, such as those from the operational, environmental and financial sectors of Water Companies. In view of this, a sorting multicriteria model to support group decision making is developed. We proposed an approach which sorts the areas of the system which are located in critical zones of water losses into categories, and which takes into account different points of view and considers uncertainty in criteria weights by using only ordinal information, so as to make it viable to manage the maintenance plan and to use the scant financial resources more efficiently. The SMAA-TRI method is used to tackle the group sorting problematic by categorizing the network into zones where losses are intense and thus to focus the managers’ effort on the most critical regions. A case study in Brazil is presented to demonstrate the efficiency of the approach proposed.     

Combining sell-out data with shopper behaviour data for category performance measurement: The role of category conversion power

Retailers need to manage a series of complex decisions relating to numerous products. To reduce this complexity, they have introduced category management practices, which consider groups of similar products (categories) that can be managed separately as single business units (SBUs). Although the concept that the store offer should be organised as a category mix and that this strategy allows for better overall store management is already consolidated, retailers still struggle to adopt an approach to the store performance measurement starting from a category level perspective. Nowadays, the available methods for measuring categories’ performance are quite limited. The current trend sees the measurement of category performance mainly based on sell-out data that are ill-equipped to fully address category management issues. Retailers should broaden their field of analysis not only by focusing on the product/sales perspective but also by including other methodologies such as shopper behaviour analysis. In this regard, the use of technology offers the retail sector new perspectives for those analysis. Therefore, we intend to contribute to the ongoing debate on the retail analytics topic by presenting a shopper behaviour analytics system for category management performance monitoring. More in detail, we could derive a new key performance indicator, category conversion power (CCP), aimed at analysing and comparing the single categories organised within the store. The research is based on a unique dataset obtained from a real-time locating system (RTLS), which allowed us to collect behavioural data togheter with sell-out data (from POS scanner). We argue that retailers could exploit this new analytical method to gain more understanding at the category level and therefore make data-driven decisions aimed at improving performance at the store level.     

A theory-based measure of acculturation: The shortened cultural life style inventory

This paper describes a model of acculturation for classifying minority consumers into distinct categories depending on their attitudes and behaviors toward their minority culture and toward the majority culture. These categories are assimilation, segregation, and integration. The model differs from previous models of acculturation in consumer research in that it does not assume a linear progression toward assimilation. The acculturation categories identified by the model can be used to segment minority markets. A reduced version of a previous scale based on that acculturation model is developed and validated in two empirical studies in a consumer research setting. Our scale can be used by managers to segment minority populations.     

A field study of customers’ switching behavior for bank services

This research paper makes three important contributions with managerial implications concerning the issue of bank service switching behavior. First, it identifies four overall dimensions of customer satisfaction with bank services. These are personnel related considerations, financial considerations (interest earnings and interest payments), environment related considerations (atmospherics), and convenience related considerations (ATM and hours). Next, we develop and test some hypotheses pertaining to the relationship between customer satisfaction and bank service switching behavior as it is mediated by the importance of a particular bank service to a particular customer and by the nature of competitive offerings for different types of banking services available from other banks. Based on the empirical results of a large scale field study, we provide several theoretical and managerial implications.     

Consciousness for fair consumption: conceptualization,scale development and empirical validation

Sustainable consumption means that consumers act in an environmentally and socially responsible manner. Compared with the vast amount of studies concerning environmentally conscious consumer behaviour, relatively little is known about socially conscious consumption. The present paper focuses on fair consumption as an important aspect of social consumption. In our study, consciousness for fair consumption (CFC) is defined as a latent disposition of consumers to prefer products that are produced and traded in compliance with fair labour and business practices. A scale to measure CFC was conceptualized and tested in three independent empirical studies. Two studies were conducted at European universities (2010 and 2012) and used 352 and 362 undergraduate business students respectively. The third study, conducted in 2011, used 141 employees at a European university. The results confirmed the reliability and validity of the new CFC scale across samples. While being moderately related to other aspects of sustainable consumption such as ecological concern and moral reasoning, CFC was significantly distinct from those concepts. Most importantly, it was established that the CFC, as measured by the new CFC scale, is a strong determinant of consumption of fair trade products that has been neglected in existing research.     

The Impact of Mobile App Adoption on Cross-buying: The Moderating Roles of Product Category Characteristics and Adoption Timing

With more and more companies introducing mobile apps and consumers using them during the purchase journey, it is increasingly important to understand the consequences of app adoption on behavioral outcomes. This paper investigates the impact of app adoption on the number of additional products purchased by customers (i.e., cross-buying) and how this effect varies across different product categories and different customers. We focus on two key product category characteristics (utilitarian vs. hedonic nature and perceived risk) and on adopters who vary in their adoption timings (early vs. late adopters). Using data from an online retailer and a combination of propensity score weighting with difference-in-differences and Heckman correction estimation techniques, the results show that app adoption has a positive effect on cross-buying overall, but the effect varies greatly across products and consumers. App adoption promotes additional product purchases for hedonic products but leads to less cross-buying for utilitarian products. In addition, early adopters purchase a higher number of additional product categories than late adopters, with this difference decreasing over time and for new consumers compared to existing customers. These results offer novel insights into the behavioral consequences of app adoption and provide managers with useful recommendations for improving the effectiveness of their mobile app investments.     

AN AXIOMATIZATION OF QUANTILES ON THE DOMAIN OF DISTRIBUTION FUNCTIONS

In an environment in which the primitive is the space of distribution functions, we characterize the quantile functions by the axioms ordinal covariance, monotonicity with respect to first-order stochastic dominance, and upper semicontinuity. We show how to characterize the VaR in a similar manner.     

Media influences on consumption trends: Effects of the film Food,Inc. on organic food sales in the U.S.

In this paper, we empirically investigate the effect of Food, Inc. – an influential documentary film on the US food industry – on organic food sales. We use a novel dataset of Google search volume to measure the influence of the film. Organic food sales are measured using store-level data for three categories in 33 major US markets. For two out of the three studied categories – yogurt and peanut butter – we find that areas with more Google searches for the film experienced a greater increase in the share of organic sales subsequent to the film's release. The effect of the film is more pronounced for the yogurt category, which is closer to the farm and more relevant to animal welfare — one of the key issues featured in the film. The effects are economically significant: ceteris paribus, a one standard deviation increase in our Google search stock measure translates into a 0.66% increase in organic market share for the yogurt and a 0.15% increase for the peanut butter category. In addition, we provide a measure of the decay of the film's effect by deriving the 90% duration interval of the focal search stock variable. We find that, for both categories, the film's effect on organic shares faded within six months.