Search results

Strategy Question: How do I better understand the make-up of my overall market?

Summary: Assuming that the market has been properly sized, it is important to also spend similar effort to define segments and size these appropriately. This tool basically mirrors the approach of the Bottom-up Market Sizing Tool. At this stage, emphasis turns to breaking the overall market into actionable segments. Two to three iterations again are common to improve accuracy. The tool output casts the segments as a rectangular graphic, made up of one column for each segment. Segment width is representative of its size relative to the other segments. The width of all segment columns, added together, ties back and equals the overall size of the markets. The result provides guidelines for determining strategic market segments and niches, and how to best position the firm within those segments.

Strategy Question: Is there a simple yet comprehensive way to characterize the business health of my markets, segments, and niches?

Summary: Now that we have the markets segmented and niched, we need to research each segment relative to attractiveness. This can be simply an indication of segment growth prospects in the chosen planning horizon, or it can be a conglomeration of key elements important to the organization (market strength, opportunity for growth, margin yield opportunity, etc.). This tool takes the user through ways to evaluate the segments for use in prioritizing the importance of various segments to product/service and channel actions. We build on either the Market Segmentation Tool or the Segment Niching Tool by assigning an attractiveness code to the column heading (green, yellow, or red). We then recommend the organization rank order the segments, with the one chosen most attractive positioned on the far left, and those next bests located in decreasing order to the right. We have found the resulting one-page Market Map Tool output extremely helpful in simply conveying what is usually a difficult and very complex picture to explain and communicate.

Strategy Question: Now that my market is sized and segmented, how do I better understand segment niches?

Summary: The Segment Niching Tool gets to the next important level of detail in the understanding of an organization’s environment. We use the Market Segmentation Tool output as a starting point. Here we further carve out key niches for further understanding related to product or service offerings. We add a scale to the segment columns of the Segment Niching Tool, and break the column further into sections whose size represents the percent of that niche to the segment. Like the segmentation tool above, understanding niches within the segments provides important information within the competitive environment. Here is where people can get mired down in infinite ways to niche a segment. We introduce our approach, based on numerous scars of wisdom, of niching based on only two questions: (1) “Why they buy?” — the main reason the product or service is purchased, and (2) “How they buy?” — the main way the product or service is purchased.

To establish a method of transforming the 3D cutting patterns constructed and modelled into 2D patterns, excluding the fabric parameters.

Three methods have been developed for transforming 3D cutting part segments into 2D segments. They are based on the computer‐based application of the mathematical models developed. The mathematical models differ in their concepts and the application in a particular manner of transforming the 3D segments. Complex spatial matrix transformations have also been developed and used to further transform the 2D segments into the plane of chained 2D cutting pattern segments.

Two‐dimensional cutting patterns have been defined for the 3D garment model, initially constructed on a computer‐generated body model.

The method has been developed on an example of a 3D garment basic cut construction of a single article of clothing. However, the same principles can be applied and developed for any garment basic cut.

The mathematical models developed can be used in a new computer‐based application for the 3D garment construction and the development of the 2D cutting patterns, matched to individual physical characteristics.

The most outstanding property of the method developed is the possibility of gradual transformation of 3D cuts into 2D ones, with no need to define physical‐mechanical properties of the fabric used and no need to introduce fabric drape. The newly created 2D cutting patterns are of outstanding quality and preciseness.

Segmenting techniques used in the lodging industry typically assume that individuals fall into mutually exclusive groups, that is, they are assigned to one type of lodging concept by the segmenting method used. In reality, however, travelers often use several types of lodging alternatives. This study utilized a canonical correlation approach to segment the senior pleasure traveler market. The analysis resulted in both uniquely defined and overlapping segments based on the relationship between lodging preferences and benefits/attributes sought in a lodging accommodation. The study also revealed implications dealing with overlapping segments as well as loyalty to specific lodging segments.

The purpose of this paper is to evaluate the cogging torque in a surface-mounted permanent magnet (SPM) machine with both uniformly and non-uniformly segmented stator cores and to find out the optimal solution of stator core segmenting.

The cogging torque with segmented stators is synthesized from a single slot model, and analytical prediction is given to analyze the cogging torque with both uniformly and non-uniformly segmented stators. Finite element method (FEM) is used to figure out the electromagnetic field and validate the analytical prediction. Moreover, models with various shapes and positions of connecting tongues between the stator core segments are explored to achieve the optimal design.

The cogging torque is found to be greatly related to the number of segments and the electrical angle between adjacent additional air gaps caused by the tolerance of stator segments. Different shapes of the connecting tongues are tested and proved to be of great importance to the flux density, both radial and tangential, and therefore affect the cogging torque. Finally, position of the connecting tongues is perceived to have little influence on the performance of machine.

By utilizing analytical prediction and FEM calculation, the optimal solution is discussed to minimize the cogging torque in the SPM machine from the perspective of the stator core segmentation.

This paper establishes formula of cogging torque with segmented stators and predicts the variation of cogging torque with analytical method. Besides, different combinations of segments are compared and measures to reduce the cogging torque produced by the segmentation are proposed.

This paper explores the existence of different food‐related lifestyle segments in the Republic of Croatia. Using international instruments and a cluster analysis (joining‐tree clustering), five different segments were found which differ in buying motives, quality aspects of the food, buying decisions, cooking methods and consumption situations. They also differ in socio‐demographic characteristics. These segments, making up the following percentage of the population, were named: relaxed – 13 percent, traditionalists – 27 percent, modern – 32 percent, concerned –11 percent and hedonists – 17 percent. The names were determined by the main statements more frequently used by the families who belong to the respective segments. These segments are expected to change in the future, in size and in the characteristics of behaviour concerning food‐related lifestyles. Therefore, we plan to repeat the research in the year 2004. At the same time, we would like to compare these segments with those distinguished in developed European countries that have conducted similar research.

Alongside structural equation modeling (SEM), the complementary technique of partial least squares (PLS) path modeling helps researchers understand relations among sets of observed variables. Like SEM, PLS began with an assumption of homogeneity – one population and one model – but has developed techniques for modeling data from heterogeneous populations, consistent with a marketing emphasis on segmentation. Heterogeneity can be expressed through interactions and nonlinear terms. Additionally, researchers can use multiple group analysis and latent class methods. This chapter reviews these techniques for modeling heterogeneous data in PLS, and illustrates key developments in finite mixture modeling in PLS using the SmartPLS 2.0 package.

This study aimed to identify and profile segments of seaweed consumers in the United Kingdom.

Hierarchical k-means cluster analysis was used to identify consumer segments based on consumers' self-identity and environmental values. In addition, the study used subjective knowledge, intentions and consumption to profile different consumer segments. The data were collected in 2022 through a consumer survey with a representative sample from the United Kingdom (n = 1,110).

Cluster analysis segmented consumers into three groups: progressive (39%), conservative (33%) and egoistic (28%). The progressive segment was most likely to consume seaweed food products. Consumers in the progressive segment identify themselves as food innovative and healthy; they also highly value the environment and their pleasure. Conservative and egoistic consumers were significantly less likely to consume seaweed food products.

The results suggest that public policy officers and marketers promote seaweed food products by emphasizing biospheric values for innovative (younger) consumers, as well as seaweed’s good taste and nutritional/health qualities.

This study identifies and examines the profiles and characteristics of seaweed consumers based on their values and self-identity. Through this research, the authors have discovered how environmental values and self-identity can effectively group consumers into homogeneous segments. Moreover, the authors have identified a specific consumer group in the UK that is more likely to consume seaweed food products.