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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.

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.

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.

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.

The architecture, engineering and construction (AEC) industry encounter substantial risks and challenges in its evolution towards sustainable development. International businesses, multinational AEC organisations, technical professionals, project and portfolio management organisations face global connectivity challenges between business units, especially during the outbreak of novel coronavirus pandemic, to manage construction megaprojects (CMPs). That raises the need to manage global connectivity as a main strategic goal of global organisations. This paper aims to investigate barriers to integrating lean construction (LC) practices and integrated project delivery (IPD) on CMPs towards the global integrated delivery (GID) transformative initiatives and develop future of work (FOW) global initiatives in contemporary multinational AEC organisations.

A two-stage quantitative and qualitative research approach is adopted. The qualitative research methodology consists of a literature review to appraise barriers to integrating LeanIPD&GID on CMPs. Barriers are arranged into six-factor clusters (FCs), with a conceptualisation of LeanIPD&GID, GID strategy placements and FOW global initiatives with multiple validations. This analysis also involved semi-structured interviews and focus group techniques. Stage two consisted of an empirical questionnaire survey that shaped the foundation of analysis and findings of 230 respondents from 23 countries with extensive cosmopolitan experience in the construction of megaprojects. The survey examined a set of 28 barriers to integrating LeanIPD&GID on CMPs resulting from a detailed analysis of extant literature after validation. Descriptive and inferential statistical tests were exploited for data analysis, percentage scoring analysis, principal component analysis (PCA) and eigenvalues were used to elaborate on clustered factors.

The research conceptualised LeanIPD&GID principles and proposed GID strategy placements for LeanIPD&GID transformative initiatives and FOW global initiatives. It concluded that the most significant barriers to integration of LeanIPD&GID on CMPs are “lack of mandatory building information modelling (BIM) and LC industry standards and regulations by governments”, “lack of involvement and support of governments”, “high costs of BIM software licenses”, “resistance of industry to change from traditional working practices” and “high initial investment in staff training costs of BIM”. PCA revealed the most significant FCs are “education and knowledge-related barriers”, “project objectives-related barriers” and “attitude-related barriers”. Awareness of BIM in the Middle East and North Africa (MENA) region is higher than LC and LC awareness is higher than IPD knowledge. Whilst BIM adoption in the MENA region is higher than LC; the second is still taking its first steps, whilst IPD has little implementation. LeanBIM is slightly integrated, whilst LeanIPD integration is almost not present.

The research findings, conclusion and recommendation and proposed GID strategy placements for LeanIPD&GID transformative initiatives to integrating LeanIPD&GID on CMPs. This will allow project key stakeholders to place emphasis on tackling LeanIPD&GID barriers identified in this research and commence GID strategies. The study has provided effective practical strategies for enhancing the integration of LeanIPD&GID transformative initiatives on CMPs.

Focussing on behaviors and attitudes of casual dining patrons, the purpose of this paper is to use a factor-cluster approach to segment patrons into market groups and attempts to determine if differences exist in motivational factors among segments.

Factor-cluster analysis is an alternative segmentation method to more traditionally used methods based on consumer demographics. Push and pull motivators were analyzed through factor analysis to determine important groupings. Then, to identify homogenous subgroups, k-means cluster analysis was conducted to segment 559 survey respondents based on factor importance.

Three diverse groups were identified: Fraternizing Kitchen Fearfuls, Functional Feasters, and Foodie Fanatics. The various push and pull factors appeared to affect segments differently, with each cluster ascribing various importance levels to each of the factors used in the clustering approach.

Limitations include the use of a convenience sample and on-campus sampling. Future research should use random sampling methods and obtain surveys from sites not associated with a college campus.

Though not often used in hospitality research, factor-cluster analysis can be useful to segment diners based on behavioral intentions and attributes, allowing marketers to more accurately target these diverse consumer segments. Marketing implications for casual dining restaurants are suggested.

Using the involvement construct with push/pull motivators, this study groups respondents though factor-cluster analysis. Though used in tourism studies, factor-cluster analysis has yet to be studied in the context of casual dining restaurant patrons.

The purpose of this paper is to investigate risk dimensions affecting food risk perceptions and to develop effective risk communication strategies based on their risk perceptions dimensions. The reason for writing this paper is that applying single risk communication strategy for public often fails because food risks are systemic risks and public perceptions toward them consist of multiple dimensions. Launching an effective risk communication need to investigate the perception dimensions of the target audience.

A total of 2,673 parents of 3-14-year-old children from the rural area of Sichuan province in China were chosen as target audience. Based on the survey conducted about parents’ food risk perceptions, this study used factor-cluster analysis method to segment parents to sub-clusters with significantly different risk perception dimensions. Parents’ representative demographic characteristics within each cluster were further identified through cross-tabs analysis with χ² tests.

All the parents could be segmented into four sub-clusters, namely, sensitive parents, dependent parents, familiarity-oriented parents and institutional distrust parents, according to their risk perception difference on five dimensions. A series of risk communication strategies were specifically designed for each cluster based on their risk perception features as well as demographic characteristics.

The insight derived from this study described a deeper image of public risk perceptions and provided suggestions for risk communication launchers to pinpoint the risk perception as well as perception dimensions of the target audience and accordingly develop effective risk communication strategies.

Slot machines and other machine gaming generate between 65 percent and 90 percent of a US casino's revenue. This article aims to examine the motivations, behaviors, and preferences of slot machine customers, and to develop market segments.

The study's objectives include: understanding the demographic, gambling motivation, and gambling behavioral characteristics of slot machine players; identifying important reasons for choosing one slot machine game over another; examining player attitudes and behaviors pertaining to progressive machines; and investigating player desire for theme‐based games. This was accomplished through an online survey of slot machine players.

Profiles of slot machine players are developed and the slot players are segmented into four clusters that explain motivations and game preferences.

This article fills in some of the gaps in understanding the gambling behavior of slot players. This study can help gaming machine manufacturers design new products and features to serve existing machine gaming customers and to attract new customers. Casino and other gaming operators can use this information not only to select the right types of machines to provide on‐site, but also to develop advertising and promotions to attract and retain new and existing customers for slot machines and other types of gaming machines.

This is the first published study that segments slot machine players from a marketing perspective and identifies their preferences, behaviors, and demographic groupings.

Focusing on food markets popularity among tourists, the purpose of this paper is to differentiate clusters of tourists based on their behaviour during their visit of these food halls.

Factor-cluster analysis is the segmentation method used to identify food markets groupings related to their motivations, while ANOVA was performed to determine differences between clusters when it comes to perceived authenticity, satisfaction and revisit intention. La Boqueria in Barcelona (Spain) is the paradigmatic food market used to conduct 196 survey respondents based on factor importance.

Two homogenous clusters were identified and labelled as apathetic-market visitors and food-market lovers.

Segmentation proposal provides insights to be taken into account for future Destination Management Organisation’s policies, related to promotional activities and destination branding development. They could create effective tailor-made promotional campaigns and adequate business strategies to further attract more food lovers markets, without removing apathetic-market visitors.

Fill the gap in the existing knowledge on the tourism interest of local markets in destinations and identify through factor-cluster analysis.

The purpose of this paper is to demonstrate that there are three major blood donor segments in China, namely benefit‐oriented donors, altruistic donors and health salience donors, with the use of factor‐cluster segmentation approach. It also investigates the blood donation attitudes, group characteristics, and preference for information acquisition of the identified donor segments.

A factor‐cluster segmentation approach was used in this study. A questionnaire survey on Chinese respondents who had just completed a blood donation process was conducted in China and 7‐point Likert‐type questions were used to measure the respondents’ attitude toward blood donation, their motivation to donate blood, lifestyles, demographics and information acquisition. K‐means non‐hierarchical clustering method was used to segment groups of blood donors. ANOVAs were conducted to assess the differences regarding the blood donation factors across the cluster segments.

Results demonstrate that there are three blood donor segments as predicted. Benefit‐oriented donors are found to be the largest cluster (42.6 per cent), followed by altruistic donors (29.6 per cent) and health salience donors (27.8 per cent). The three clusters of donors show some extent of differences in attitudes toward blood donation, lifestyles and preference for information acquisition.

Through a better understanding of the donor segments, a more effective marketing communication strategy can be formulated. This can promote more blood donation by the first‐time and repeat blood donors and may save many more lives in a society.

The major advertising appeal for blood donation is altruistic in nature, particularly in Western countries. However, in other emerging countries such as China, some other appeals may be even more effective. Benefit appeal or health fitness appeal may be a better option in marketing communication strategy.

The purposes of this paper is to segment spectators of collegiate football game using a cluster analysis and to determine differences between spectator clusters based on motivations, satisfaction, and demographic characteristics.

A survey instrument was utilized, and a total of 407 usable data were gathered through a convenience sampling method at a main campus in the Southern USA. A discriminant analysis was employed to create cluster profiles including demographic variables not previously included in the clustering procedure. Cluster analysis is a procedure used to determine best group segmentation.

Through a factor-cluster analysis, two distinct groups are identified as attendees of collegiate football games: far-away fans and seasoned sideliners. Knowing the different spectators in event attendance allows marketers of collegiate sport events to effectively target segments and attract larger numbers of visitors to each event. Although the results indicated lower satisfaction with the far-away fans cluster, they are nonetheless spending their money at these events. A concerted effort to better welcome tourists that are supporting the visiting team may help boost their image of the local community and thus increase their spending level.

The current study adds to the literature on sport event research, while providing great insight for researchers and practitioners how to segment their target market. Therefore, it is believed that the results of the present study will help future researchers and industry practitioners make use of the implications and findings to broaden their knowledge about sport marketing.

The purpose of this paper is to include grandparents’ characteristics, identifying who they are, revealing the differences in their motivation while taking a trip with their spouses and with their grandchildren or without grandkids using a factor-cluster market segmentation approach.

The sample population for this research consisted of tourists who are grandparents and visited the Rudkhan Castle in the city of Fuman in Iran. The push and pull motivation data were collected from a questionnaire and separated respondents into parts of with grandchildren and without grandchildren samples. The motivation factors were derived from 26 motivation items through factor analysis. Among 528 questionnaires distributed, 516 questionnaires were used for further data analyses.

As a result of cluster analysis, grandparents with spouses and grandchildren were divided into three clusters including “Family lovers” which constituted nearly half of the sample, “Multi-purpose seekers” and “Knowledge hunters”, while grandparents who were only with their spouses were segmented into four clusters. The first and the largest was “Escapists, followed by “Enjoy seekers”, “Novelty seekers” and “Historical/Natural explorers”.

Recognizing the differences between tourists is the first step toward competitive advantage. Segmentation allows the identification of groups of tourists who share some common characteristics and who are likely to respond similarly to marketing stimuli. However, there are a few studies about motivations of elderly tourists who experienced a holiday trip with their grandchildren or without them.

The purpose of this study is to profile market segments using travelers’ decision-making styles (DMS) as segmentation bases and to identify similarities and differences between traveler segments regarding a series of psychographic and attitudinal characteristics.

Data are gathered from a sample of 426 travelers in Dubai and Shanghai via self-reported surveys. Analyses included factor, k-means cluster, discriminant and MANOVA.

Study findings reveal significant differences among the rational, adaptive and daydreamer decision-makers’ segments in their behavioral and attitudinal characteristics with respect to tourism involvement and destination images.

Findings provide important practical implications for generating effective marketing and positioning strategies based on the identified attitudinal characteristics of the traveler segments for destination marketing organizations.

A stream of recent tourism studies shows a strong relationship between tourism involvement and destination images, yet very little research has tackled the issue of how these critical variables can be affected by individuals’ decision-making styles. This study explores and tests the relationships among DMS, tourism involvement and destination image using a factor-cluster approach.