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Research summary: How do peripheral firms compete and secure future growth? Building on literature in strategy and organizational theory, we test a model of peripheral entry and growth in the mainstream market segment. Using data from 289 craft breweries over 11 years, we find evidence that niche producers are increasingly entering the mainstream market and competing with market-center firms. We identify two mechanisms contributing to these actions: legitimacy transfer and cognitive claims of authenticity. As hypothesized, imitation of niche products by macro breweries facilitates craft beer entry into mainstream markets. Moreover, two authenticity-based identity codes are found to reliably influence craft brewery growth: a local identity (i.e., operating in one's local market) and a product proliferator identity (i.e., offering a more diverse set of products). Managerial summary: How can small niche firms compete with larger, more established organizations? By examining the rapidly expanding craft beer industry, this study explores how craft breweries are able to both enter the market space of these larger competitors and secure sustained patterns of growth. Specifically, we highlight two factors influencing the success of craft breweries. First, as major beer producers mimic niche products (i.e., faux craft beer), smaller niche firms are allowed to enter the market by exposing the typical consumer to the tastes of craft beer. Second, craft breweries enjoy increased success if they (a) emphasize the local elements of their company, and/or (b) offer a larger number of products.

Purpose This paper discusses the dos and don'ts of market segmentation analysis. Market segmentation analysis is younger than the journal Tourism Review, but nevertheless has a rich history in tourism research and continues to be extensively used by both tourism researchers and industry. Design/methodology/approach After a brief overview of the origins of market segmentation analysis and its uptake in tourism, a number of key considerations are discussed, which are critical to ensuring that practically useful and reliable market segments emerge from the analysis. Findings Do accept that market segmentation is exploratory. Do spend a lot of time ensuring you collect high-quality data. Don’t use ordinal data. Don’t use correlated variables. Do ensure your sample size is large enough. Don’t use factor-cluster analysis. Do conduct data structure analysis. Don’t complicate things. Originality/value This is a perspective study; it offers a concise discussion of key issues in market segmentation analysis and directs the interested reader to resources where they can learn more about each of these issues.

An appropriate optimal number of market segments (ONS) estimation is essential for an enterprise to achieve successful market segmentation, but at present, there is a serious lack of attention to this issue in market segmentation. In our study, an independent adaptive ONS estimation method BWCON-NSDK-means++ is proposed by integrating a new internal validity index (IVI) Between-Within-Connectivity (BWCON) and a new stable clustering algorithm Natural-SDK-means++ (NSDK-means++) in a novel way. First, to complete the evaluation dimensions of the existing IVIs, we designed a connectivity formula based on the neighbor relationship and proposed the BWCON by integrating the connectivity with other two commonly considered measures of compactness and separation. Then, considering the stability, number of parameters and clustering performance, we proposed the NSDK-means++to participate in the integration where the natural neighbor was used to optimize the initial cluster centers (ICCs) determination strategy in the SDK-means++. At last, to ensure the objectivity of the estimated ONS, we designed a BWCON-based ONS estimation framework that does not require the user to set any parameters in advance and integrated the NSDK-means++ into this framework forming a practical ONS estimation tool BWCON-NSDK-means++. The final experimental results show that the proposed BWCON and NSDK-means++ are significantly more suitable than their respective existing models to participate in the integration for determining the ONS, and the proposed BWCON-NSDK-means++ is demonstrably superior to the BWCON-KMA, BWCONMBK, BWCON-KM++, BWCON-RKM++, BWCON-SDKM++, BWCON-Single linkage, BWCON-Complete linkage, BWCON-Average linkage and BWCON-Ward linkage in terms of the ONS estimation. Moreover, as an independent market segmentation tool, the BWCON-NSDK-means++ also outperforms the existing models with respect to the inter-market differentiation and sub-market size.

Formalized breeding schemes are a key component of breeding program design and a gateway to conducting plant breeding as a quantitative process. Unfortunately, breeding schemes are rarely defined, expressed in a quantifiable format, or stored in a database. Furthermore, the continuous review and improvement of breeding schemes is not routinely conducted in many breeding programs. Given the rapid development of novel breeding methodologies, it is important to adopt a philosophy of continuous improvement regarding breeding scheme design. Here, we discuss terms and definitions that are relevant to formalizing breeding pipelines, market segments and breeding schemes, and we present a software tool, Breeding Pipeline Manager, that can be used to formalize and continuously improve breeding schemes. In addition, we detail the use of continuous improvement methods and tools such as genetic simulation through a case study in the International Institute of Tropical Agriculture (IITA) Cassava east-Africa pipeline. We successfully deploy these tools and methods to optimize the program size as well as allocation of resources to the number of parents used, number of crosses made, and number of progeny produced. We propose a structured approach to improve breeding schemes which will help to sustain the rates of response to selection and help to deliver better products to farmers and consumers.

Purpose The purpose of this paper is to determine the demographic characteristics and habits of craft beer consumers, as well as to identify the motivational factors for consumption. Design/methodology/approach Data were collected through questionnaires applied to 316 Brazilian craft beer consumers, and results were evaluated descriptively and by multivariate statistics. Findings The results of the survey revealed that there is a growing market segment with different buying habits and behaviors compared to traditional beer consumers. Demographically, it was found that these consumers are an attractive part of the beer market in terms of age, schooling and, more importantly, in terms of income, factors that indicate the probability of continued growth in the sector. Research limitations/implications The research was limited to craft beer consumers in the metropolitan region of Belo Horizonte/MG, Brazil. Practical implications The results obtained are important, as they can help new craft breweries, as well as help established industry managers to create strategies related to marketing four Ps in order to increase the consumption of its products, with competitive advantages to the market. Originality/value This research presents the characteristics of the consumers of craft beer, a market segment in evident rise in Brazil, about which there are few studies. In addition, it provides valuable information to both the new beverage manufacturers as well as to the already established entrepreneurs in the market so that they can increase the consumption of their products in a strategic way.

With the increase in complexity of real problems, more and more, the decision makers are involved remarkably in the decision-making processes. It is required more efficient technique or tool to give reliable outcomes. This paper proposes a new dissimilarity measure on picture fuzzy sets. A multi-criteria decision-making problem is utilized to apply this new measure to select the optimal alternative. Finally, an example uses the proposed measure to evaluate and select the optimal market segment.

PurposeThe main purpose of this conceptual paper is to identify and explain the technique of branding “Halal” as a marketing strategy to reach and capture a certain market segment (niche), particularly Muslims.Design/methodology/approachThe approach of this paper is descriptive based on literature survey as well as the author’s own opinion, experience and judgment.FindingsIn many cases, particularly in food market, the term “Halal” is being used to attract the Muslim customers’ religious feelings rather than providing them cost-effective value products.Research limitations/implicationsThe paper is expected to contribute to the theoretical base, as it focuses on the use of religious sentiments in marketing that is worth further research conduction.Practical implicationsThe arguments of this paper can be used by the producers of “Halal” products in including certain features that might satisfy the demands of religious Muslims regarding food products.Social implicationsThis paper can be contributive for the greater needs regarding societal and Islamic values.Originality/valueThis paper is one of the initial attempts to highlight the religious feelings to attract a specific market segment.

In the literature, there is extensive, although in some cases inconclusive, evidence on the impact of Energy Performance Certificates (EPC) on housing prices. Nonetheless, the question of whether such an impact is homogenous across residential segments remains highly unexplored. This paper addresses this latter issue utilizing multifamily listing data in metropolitan Barcelona. In doing so, first the entire sample is analyzed using a hedonic model. Second, the sample is split on the basis of a multivariate segmentation. Finally, separated hedonic models are specified again. The results suggest that in general, there is a modest impact of EPC ratings on listing prices, nonetheless it is not homogeneous across housing segments: (1) for the most modern apartments, with state-of-the-art features and active environmental comfort, energy ratings seem to play a null role in the formation of prices; (2) conversely, for the cheapest apartments, apartments boasting the most basic features, and apartments located in low-income areas, the “brown discount” is enormously significant, potentially depreciating the equity of those who have the least resources to carry out an energy retrofit. These results have implications for the assessment of the EPBD and its Spanish transposition, since a very well-intentioned environmental policy could have potentially harmful social repercussions in the absence of corrective measures.

The typical ranges available for electric vehicles (EVs) may be considered by users to be inadequate when compared to long, real-life trips, and charging operations may need to be planned along journeys. To evaluate the compatibility between vehicle features and charging options for realistic journeys performed by car, a simulation approach is proposed here, using travel data collected from real vehicles to obtain trip chains for multiple consecutive days. Car travel activities, including stops with the option of charging, were simulated by applying an agent-based approach. Charging operations can be integrated into trip chains for user activities, assuming that they remain unchanged in the event that vehicles switch to electric. The energy consumption of the analyzed trips, disaggregated by vehicle type, was estimated using the average travel speed, which is useful for capturing the main route features (ranging from urban to motorways). Data were recorded for approximately 25,000 vehicles in the Turin Metropolitan Area for six consecutive days. Market segmentation of the vehicles was introduced to take into consideration different energy consumption rates and charging times, given that the electric power, battery size, and consumption rate can be related to the vehicle category. Charging activities carried out using public infrastructure during idle time between consecutive trips, as well as those carried out at home or work, were identified in order to model different needs.

Understanding luxury tourists required a more comprehensive approach than traditional expenditure-based segmentation, which often overlooked travelers’ financial capacity. This study therefore aimed to develop and validate a new typology of luxury tourists by jointly analyzing income and expenditure patterns using the International Visitor Survey of South Korea. The study addressed the need to capture both tourists’ economic capability and consumption behavior to enhance the precision of market segmentation and support sustainable destination management. Using the Jenks natural breaks classification and logistic regression, four distinct tourist types were identified: economy, spurious, scrooge, and premier, each reflecting unique combinations of income and expenditure. The results revealed that age, nationality, occupation, and trip purpose significantly influenced tourists’ classification. Younger and middle-aged professionals from East Asia were more likely to belong to high-income and high-expenditure groups, whereas Western tourists tended to spend more relative to their income. This income–expenditure typology advanced theoretical understanding of luxury tourism segmentation and provided practical insights for destination marketing organizations. The findings offered new insights for understanding how the alignment between tourists’ financial capacity and spending behavior can redefine strategies for sustainable and inclusive tourism development.