Investigating the factors which affect the performance of the EM algorithm in Latent class models

Latent class models have been used extensively in market segmentation to divide a total market into market groups of consumers who have relatively similar product needs and preferences. The advantage of these models over traditional clustering techniques lies in simultaneous estimation and segmentation, which is carried out using the EM algorithm. The identification of consumer segments allows target-marketing strategies to be developed. The data comprises the rating responses of 262 respondents to 24 laptop profiles described by four item attributes including the brand, price, random access memory (RAM) and the screen size. Using the facilities of R Studio, two latent class models were fitted by varying the number of clusters from 2 to 3. The parameter estimates obtained from these two latent class models were used to simulate a number of data sets for each cluster solution to be able to conduct a Monte-Carlo study, which investigates factors that have an effect on segment membership and parameter recovery and affect computational effort.peer-reviewe

Information-Sharing and Strategy by Food Industry Firms

This study investigates the strategic behaviour of food industry firms. Its two goals are to: (i) characterise strategies being employed; and (ii) identify distinct approaches to information-sharing Data from an interview-format survey of Danish food industry firms are used to characterise strategy at two levels: 11 “strategic orientations”; each of which is composed of 3-6 of a total 57 “strategic actions”. Principal components were identified and two complementary cluster analysis techniques were used to assemble clusters that are composed of firms either with distinct strategies, or sets of strategies occurring in distinct combinations. Eight clusters emerge, with reasonable procedural performance. The clusters are distinct in a surprisingly large number of ways, including their strategies for market share, pricing, approach and response to regulation, exports and use of retailers’ own-label brands. Information-sharing strategies are closely linked to both marketing strategy and regulation response/anticipation. Individual clusters identify distinct sets of behaviour regarding information-sharing up and/or down the value chain, their approach to quality and other aspects of market segmentation, targeting of export markets, and willingness to compete on price. Clusters’ distinct strategies regarding regulation featured anticipation, as opposed to several diverse means of passing on compliance costs: to buyers or to sellers. Such activities were linked to information-sharing strategies in different ways by different clusters.Agribusiness, Agricultural and Food Policy, Farm Management, Food Consumption/Nutrition/Food Safety, Industrial Organization,

Market Segmentation and the Sources of Rents from Innovation: Personal Computers in the Late 1980's

This paper evaluates the sources of transitory market power in the market for personal computers (PCs) during the late 1980's. Our analysis is motivated by the coexistence of low entry barriers into the PC industry and high rates of innovative investment by a small number of PC manufacturers. We attempt to understand these phenomena by measuring the role that different principles of product differentiation (PDs) played in segmenting this dynamic market. Our first PD measures the substitutability between Frontier (386-based) and Non- Frontier products, while the second PD measures the advantage of a brand-name reputation (e.g., by IBM). Building on advances in the measurement of product differentiation, we measure the separate roles that these PDs played in contributing to transitory market power. In so doing, this paper attempts to account for the market origins of innovative rents in the PC industry. Our principal finding is that, during the late 1980's, the PC market was highly segmented along both the Branded (B versus NB) and Frontier (F versusNF) dimensions. The effects of competitive events in any one cluster were confined mostly to that particular cluster, with little effect on other clusters. For example, less than 5% of the market share achieved by a hypothetical entrant would be market-stealing from other clusters. In addition, the product diffe- rentiation advantages of B and F were qualitatively different. The main advantage of F was limited to the isolation from NF competitors it provided; Brandedness both shifted out the product demand curve as well as segmenting B products from NB competition. These results help explain how transitory market power (arising from market segmentation) shaped the underlying incen- tives for innovation in the PC industry during the mid to late 1980s.

"Job Quality, Labor Market Segmentation, and Earning Inequality: Effects of Economic Restructuring in the 1980s by Race and Gender"

The authors examine the effects of employment restructuring in the 1980s on white, black, and Hispanic men and women within a labor market segmentation framework. Cluster analysis is used to determine whether jobs can be grouped into a small number of relatively homogeneous clusters on the basis of differences in job quality. With data centered on 1979, 621 occupation/ industry cells covering 94% of the workforce are analyzed with 17 measures of job quality, ranging from earnings and benefits to skill requirements and working conditions. The paper finds strong support for dual and tripartite schemes that closely resemble those described, but never satisfactorily verified, by the segmented labor market (SLM) literature of the 1970s: the "primary" (independent and subordinate) and "secondary" segments. But the findings also show that each of these three large segments consists of two distinct and easily interpretable job clusters that are significantly different from one another in race and gender composition. The job structure has become more bifurcated in the 1980s, as "middle-class" jobs (the subordinate primary segment) declined sharply and the workforce was increasingly employed in either the best (independent primary) or the worst (secondary) jobs. White women became much more concentrated at the top, while white men and black and Hispanic women were redistributed to both ends of the job structure. Black and Hispanic men, however, increased their presence only in the two secondary job clusters. Meanwhile, the quality of secondary jobs declined considerably, at least as measured by earnings, benefits, union coverage, and involuntary part-time employment. As these results would suggest, the paper research found that earnings differentials by cluster, controlling for education and experience, increased in the 1980s. The male and female wage gap also increased, as did the portion of these increasing differentials that were accounted for by changes in the distribution of racial groups among clusters.

Segmentasi Konsumen Berdasarkan Model Recency, Frequency, Monetary dengan Metode K-Means

A good company is a company that is responsive to market changes and opportunities by utilizing existing data and information. Company data and information can come from internal or external sources. One of the internal data sources that can be utilized is customer data. This data will be used as the basis for determining customer segmentation. Segmentation is a process to determine customer characteristics with certain similarities, making it easier to extract information related to profitable customers. Customer business behavior can be seen from recency (last transaction period), frequency (number of transactions), and monetary (rupiah issued) or known as RFM analysis. The effective RFM analysis helps achieve the implementation of customer relationship management because this model is an important facility in measuring the profitability of customer value. To consider this RFM model, researchers use clustering which assumes that customers are in the same cluster, then consider customers with customers in the cluster. This clustering will display customer segmentation. This clustering method uses K-Means clustering. From the results of data processing, 3 clusters were formed from 25 customer data. Based on the clusters formed, it can be concluded that customer purchases have a different pattern. Clusters included in the segment of potential customers are cluster 1. Clusters are needed to get customers who previously had low R, high F, and high M values. While the strategy that needs to be improved is cluster 2

Latent class analysis for segmenting preferences of investment bonds

Market segmentation is a key component of conjoint analysis which addresses consumer preference heterogeneity. Members in a segment are assumed to be homogenous in their views and preferences when worthing an item but distinctly heterogenous to members of other segments. Latent class methodology is one of the several conjoint segmentation procedures that overcome the limitations of aggregate analysis and a-priori segmentation. The main benefit of Latent class models is that market segment membership and regression parameters of each derived segment are estimated simultaneously. The Latent class model presented in this paper uses mixtures of multivariate conditional normal distributions to analyze rating data, where the likelihood is maximized using the EM algorithm. The application focuses on customer preferences for investment bonds described by four attributes; currency, coupon rate, redemption term and price. A number of demographic variables are used to generate segments that are accessible and actionable.peer-reviewe

Managerial Segmentation of Service Offerings in Work Commuting, MTI Report WP 12-02

Methodology to efficiently segment markets for public transportation offerings has been introduced and exemplified in an application to an urban travel corridor in which high tech companies predominate. The principal objective has been to introduce and apply multivariate methodology to efficiently identify segments of work commuters and their demographic identifiers. A set of attributes in terms of which service offerings could be defined was derived from background studies and focus groups of work commuters in the county. Adaptive choice conjoint analysis was used to derive the importance weights of these attributes in available service offering to these commuters. A two-stage clustering procedure was then used to explore the grouping of individual’s subsets into homogeneous sub-groups of the sample. These subsets are commonly a basis for differentiation in service offerings that can increase total ridership in public transportation while approximating cost neutrality in service delivery. Recursive partitioning identified interactions between demographic predictors that significantly contributed to the discrimination of segments in demographics. Implementation of the results is discussed

Market opportunities for animal-friendly milk in different consumer segments

Consumers have increasing, but highly variable, interest in sustainability attributes of food, including ethical aspects, such as animal welfare. We explored market opportunities for animal-friendly cow’s milk based on segmentation (cluster) analysis. Flemish survey participants (n = 787) were clustered (n = 6) based on their intention to purchase (IP) animal-friendly milk, and their evaluation of cows’ welfare state (EV). Three market opportunity segments were derived from clusters and labelled as “high”, “moderate” and “limited”. Only 8% of the participants belong to the “high market opportunities” segment, characterized by a high IP and a low EV. The “limited” segment (44%) indicated a neutral to low IP and a positive EV. The “moderate” segment (48%) had a moderately positive IP and positive/negative EV. Reported willingness to pay, interest in information about the state of animal welfare and importance of the product attribute “animal welfare” differed among segments and were strongly related to IP. Most promising selling propositions about animal-friendly milk were related to pasture access. The high degree of differentiation within the Flemish milk market reveals market opportunities for animal-friendly milk, but for an effective market share increase supply of animal-friendly products needs to get more aligned with the heterogeneous demand