Search results

This paper reports findings from a study into how marketing academics and MBA students view segmentation. The research indicates that both respondent groups view segmentation as being more valuable in helping to understand customers than improving business performance. For MBA students there appears to be no relationship between their reported marketing knowledge and the value attributed to using market segmentation. The findings for academics suggest inconsistencies in how they interpret the value of segmentation and appraise the usefulness of analytical and evaluation approaches.

The study aims to explore how segmentation as a methodology can be adapted to the healthcare context to provide a more nuanced understanding of the served population and to facilitate the design of patient-centric services.

The study was based on a collaborative project with a national healthcare organization following the principles of action design research. The study describes the quantitative segmentation performed during the project, followed by a qualitative interview study of how segments correspond with patient behaviors in an actual healthcare setting, and service design workshops facilitated by segments. A number of design principles are outlined based on the learnings of the project.

The segmentation approach increased understanding of patient variability within the service provider organization and was considered an effective foundation for modular service design. Patient characteristics and life circumstances were related to specific patterns of health behaviors, such as avoidance or passivity, or a persistent proactivity. These patterns influenced the patients' preferred value co-creation role and what type of support patients sought from the care provider.

The proposed segmentation approach is immediately generalizable to further healthcare contexts and similar services: improved understanding of patients, vulnerable patients in particular, improves the fit and inclusivity of services.

The segmentation approach to service design was demonstrated to be effective in a large-scale context. The approach allows service providers to design service options that improve the fit with individual patients' needs for support and autonomy. The results illuminate how patient characteristics influence health and value co-creation behaviors.

Successful segmentation and implementation are crucial for firms. This paper aims to focus on what areas small- and medium-sized enterprises (SMEs) consider when implementing new target segments in the organization. If firms do not understand the potential complexity and plan for implementation, they risk overlooking important areas that cause organizational resistance and failure in the market.

This paper builds on a literature study and five SME case studies based on 44 interviews and 10 intervention workshops.

The authors identify key areas of change that SMEs consider when planning to implement segments in the organization, including marketing strategy and plans, organizational aspects and implementation processes. Organization changes and sales plays are key considerations among SME managers. The authors further identify four categories characterized by different degrees of marketing and organizational changes that SMEs face when implementing new target segments, reflecting SMEs former choices.

This research is based on interviews and workshops that bring managers into a situation where they can evaluate needed changes to implement segments. The managers can express the complexity and the effect of the implementation.

This paper presents considerations and insights derived from SMEs and discusses how firms can be better equipped to implement new segments.

This paper offers new insights and directions for segmentation literature, focusing on implementation and proposing how to advance the segmentation literature.

This study aims to capture the views of executives about the merit of using the two segmentation approaches (quantitative vs qualitative). Furthermore, this study aimed to examine costs and benefits for two different segmentation approaches, using a minimax simple cost-benefit analysis (CBA) matrix.

A total of 16 semistructured interviews were conducted with executives within the University of Sharjah (UoS). Furthermore, a minimax approach was applied to the CBA study.

Evidence in this study found that the financial cost of quantitative segmentation approaches was higher than qualitative approaches. However, the decision-makers trusted the quantitative approach more regardless of the incurred costs. The study also found that there was a limited knowledge about social marketing and segmentation among executives.

Limitations of this study relate to the methodology applied, the sample selected and the lead research. Another factor is selection bias, which limited this study to one organization’s executives. It is conceivable that middle-level management would have had the desire to participate because they make the recommendations to top management in decision-making. The researcher did not collect precise data on time taken to design, implement and analyses the two segmentation studies, which qualified the precision of the CBA. Also, the fact that the sample includes participants from a relatively narrow range of disciplines should be noted as a limitation of the study.

The current study provides a case study demonstrating how CBA provides a dollar amount estimate permitting alternate segmentation approaches to be compared and contrasted, assisting in the value estimation of any social marketing project.

The paper draws upon two streams of the literature: social marketing and CBA. The paper focused on the understanding of the literature, CBA offers a technique applicable to demonstrating cost savings that can be derived from choosing one method over another. Moreover, CBA assists in understanding the benefits or potential opportunity cost both financially and nonfinancially.

This paper presents one of the first studies conducting a CBA to compare and contrast two segmentation approaches in social marketing. The study provides interesting insights into the perceptions of management executives over alternative research methods, although the results are limited to a case study.

Extraction of leaf region from the plant leaf images is a prerequisite process for species recognition, disease detection and classification and so on, which are required for crop management. Several approaches were developed to implement the process of leaf region segmentation from the background. However, most of the methods were applied to the images taken under laboratory setups or plain background, but the application of leaf segmentation methods is vital to be used on real-time cultivation field images that contain complex backgrounds. So far, the efficient method that automatically segments leaf region from the complex background exclusively for black gram plant leaf images has not been developed.

Extracting leaf regions from the complex background is cumbersome, and the proposed PLRSNet (Plant Leaf Region Segmentation Net) is one of the solutions to this problem. In this paper, a customized deep network is designed and applied to extract leaf regions from the images taken from cultivation fields.

The proposed PLRSNet compared with the state-of-the-art methods and the experimental results evident that proposed PLRSNet yields 96.9% of Similarity Index/Dice, 94.2% of Jaccard/IoU, 98.55% of Correct Detection Ratio, Total Segmentation Error of 0.059 and Average Surface Distance of 3.037, representing a significant improvement over existing methods particularly taking into account of cultivation field images.

In this work, a customized deep learning network is designed for segmenting plant leaf region under complex background and named it as a PLRSNet.

This paper presents a comparative study of different stator-segmentation topologies of a permanent magnet synchronous machine (PMSM) used in traction drives and their effect on iron losses. Using stator segmentation allows one to achieve more significant copper fill factors, resulting in increased power densities and efficiencies. The segmentation of the stators creates additional air gaps and changes the soft magnetic material’s material properties due to the cut edge effect. The aim of this paper is to present an in-depth analysis of the influence of stator segmentation on iron losses. The main goal was to compare various segmentation methods under equal excitation conditions in terms of their influence on iron loss.

A transient finite element method analysis combined with an extended iron-loss model was used to evaluate discussed effects on the stator’s iron losses. The workflow to obtain a homogenized airgap length accounting for cut edge effects was established.

The paper concludes that the segmentation in most cases slightly decreases the iron losses in the stator because of the overall reduced magnetic flux density B due to the additional air gaps in the magnetic circuit. An increase of the individual components, as well as total power loss, was observed in the Pole Chain segmentation design. In general, segmentation did not change the total iron losses significantly. However, different segmentation methods resulted in the different distortion of the magnetic field and, consequently, in different iron loss compositions. The analysed segmentation methods exhibited different iron loss behaviour with respect to the operation points of the machine. The final finding is that analysed stator segmentations had a negligible influence on the total iron loss. Therefore, applying segmentation is an adequate measure to improve PMSMs as it enables, e.g. increase of the winding fill factor or simplifying the assembly processes, etc.

The influence of stator segmentation on iron losses was analysed. An in-depth evaluation was performed to determine how the discussed changes influence the individual iron loss components. A workflow was developed to achieve a computationally cheap homogenized model.

The purpose of this study is to propose a new consumer value segmentation method for low-dimensional dense market datasets to quickly detect and cluster the most profitable customers for the enterprises.

In this study, the comprehensive segmentation bases (CSB) with richer meanings were obtained by introducing the weighted recency-frequency-monetary (RFM) model into the common segmentation bases (SB). Further, a new market segmentation method, the CSB-MBK algorithm was proposed by integrating the CSB model and the mini-batch k-means (MBK) clustering algorithm.

The results show that our proposed CSB model can reflect consumers' contributions to a market, as well as improve the clustering performance. Moreover, the proposed CSB-MBK algorithm is demonstrably superior to the SB-MBK, CSB-KMA and CSB-Chameleon algorithms with respect to the Silhouette Coefficient (SC), the Calinski-Harabasz (CH) Index , the average running time and superior to the SB-MBK, RFM-MBK and WRFM-MBK algorithms in terms of the inter-market value and characteristic differentiation.

This paper provides a tool for decision-makers and marketers to segment a market quickly, which can help them grasp consumers' activity, loyalty, purchasing power and other characteristics in a target market timely and achieve the precision marketing.

This study is the first to introduce the CSB-MBK algorithm for identifying valuable customers through the comprehensive consideration of the clustering quality, consumer value and segmentation speed. Moreover, the CSB-MBK algorithm can be considered for applications in other markets.

Prior studies have confirmed market segmentation as an important shackle to China's macroeconomy upgrade, but the systematic analysis of microenterprise upgrade remains inadequate. This paper aims to investigate the nonlinear impact of market segmentation on microenterprise upgrade.

The price method was applied to calculate China's provincial market segmentation, including commodity, capital, labor and energy. The generalized method of moments was employed to examine the nonlinear impact of market segmentation on the upgrading of manufacturing enterprises based on microenterprise data from 2003 to 2019.

First, China’s heterogeneous market segmentations have been significantly reduced. Macroeconomics and policies are critical factors in market integration. Second, there is an inverted U-shaped relationship between China’s total market segmentation and the upgrading of manufacturing enterprises. Third, the relationship between the commodity market segmentation, labor market segmentation, energy market segmentation and manufacturing enterprises' upgrade is shown as an inverted U-shaped. Nevertheless, the relationship between the capital market segmentation and upgrading of manufacturing enterprises exhibits a U-shape.

The impact of market segmentation on the upgrading of manufacturing enterprises in China performs nonlinearly. An inverted U-shaped relationship exists between market segmentation in commodity, labor and energy and the upgrading of manufacturing enterprises, while a U-shaped relationship prevails between capital market segmentation and the upgrading of manufacturing enterprises.

Customer service represents a significant opportunity for segmenting markets. This article reviews the importance of customer service and the conceptual issues associated with segmenting industrial markets on the basis of customer service. A methodology is presented which can be used by managers to classify a market into segments with different customer service needs. Empirical results from a high‐technology industry are also presented. The article emphasises the need to recognise the differing customer service requirements of segments of customers when establishing priorities for customer service expenditures.