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Community clusters of tsunami vulnerability in the US Pacific Northwest
Edited by B. L. Turner, Arizona State University, Tempe, AZ, and approved March 17, 2015 (received for review October 22, 2014)
We present an analytical framework for understanding community-level vulnerability to tsunamis that integrates population exposure, demographic sensitivity, and evacuation potential.We identify three types of communities along the US Pacific Northwest coast that are directly threatened by tsunamis associated with a Cascadia subduction zone earthquake: (i) demographically diverse with low numbers of exposed people, (ii) high numbers of exposed populations but sufficient time to evacuate, and (iii) moderate numbers of exposed populations but insufficient time to evacuate. This approach is a significant advance over current practice because traditional measures of social vulnerability do not relate population structure to specific hazard characteristics. Results help managers to develop risk reduction strategies that are tailored to local conditions and needs.
Many coastal communities throughout the world are threatened by local (or near-field) tsunamis that could inundate low-lying areas in a matter of minutes after generation. Although the hazard and sustainability literature often frames vulnerability conceptually as a multidimensional issue involving exposure, sensitivity, and resilience to a hazard, assessments often focus on one element or do not recognize the hazard context. We introduce an analytical framework for describing variations in population vulnerability to tsunami hazards that integrates (i) geospatial approaches to identify the number and characteristics of people in hazard zones, (ii) anisotropic path distance models to estimate evacuation travel times to safety, and (iii) cluster analysis to classify communities with similar vulnerability. We demonstrate this approach by classifying 49 incorporated cities, 7 tribal reservations, and 17 counties from northern California to northern Washington that are directly threatened by tsunami waves associated with a Cascadia subduction zone earthquake. Results suggest three primary community groups: (i) relatively low numbers of exposed populations with varied demographic sensitivities, (ii) high numbers of exposed populations but sufficient time to evacuate before wave arrival, and (iii) moderate numbers of exposed populations but insufficient time to evacuate. Results can be used to enhance general hazard-awareness efforts with targeted interventions, such as education and outreach tailored to local demographics, evacuation training, and/or vertical evacuation refuges.
During the last decade, tsunamis have killed hundreds of thousands of people and destroyed coastal communities throughout the world (1). Geologic evidence of past events and geophysical models of potential sources suggest that many communities face substantial tsunami hazards. Although tsunami scenarios are often regional, local vulnerability varies because of how communities choose to use tsunami-prone areas, the types of people in hazard zones, the local conditions that enable or hinder evacuations, and the ability and willingness to mitigate threats.
The sustainability and hazards literature includes multiple efforts to conceptualize vulnerability, yet they share a common perspective that it is influenced by the exposure, sensitivity, and resilience of a system to a threat (2⇓⇓–5). Efforts to measure population vulnerability to tsunamis primarily have relied on indices that summarize population exposure (6), potential building damage (7), or institutional aspects of resilience (8). Indices also have been developed based on characteristics of people that make them more sensitive to hazards in general but are detached from a specific hazard context (9). These approaches are of limited utility to practitioners because they focus on individual components of vulnerability and inadequately capture the complex interactions between natural events and at-risk populations. For example, exposure to tsunamis should not be interpreted as a loss estimate given the potential for evacuations. Age as a vulnerability indicator for reasons related to mobility (2, 9) will likely have greater relevance for tsunamis requiring self-evacuations within minutes than they do for events with hours of warning.
To address these shortcomings, we developed an analytical approach for hazard-specific vulnerability assessment that considers population exposure, demographic sensitivity, and short-term resilience. This approach is an advance over traditional vulnerability measures because it relates compositional aspects of the population and landscape to the hazard. We focus on the tsunami threat posed by earthquakes associated with the Cascadia subduction zone (CSZ) in the US Pacific Northwest, where regional impacts could be analogous to those in Japan during the 2011 Tohoku disaster. Of all tsunami-prone areas in the United States, CSZ-related tsunamis represent one of the greatest threats to human safety (10) based on the regional extent of the source (∼1,000 km from northern California to Washington), the limited amount of time available for evacuations (15–-30 min for many communities), and the thousands of people that would need to self-evacuate (6, 11, 12).
The policy-relevant questions that drive this research are determining where loss of life is possible, what types of interventions could best serve at-risk populations, and what knowledge networks can be established to connect communities with similar issues. The work addresses the lack of pedestrian-evacuation studies to guide US tsunami risk-reduction efforts (10) by integrating geospatial and statistical methods, specifically demographic overlays to gauge exposure, anisotropic path distance models to estimate potential travel times to safety (13), and clustering algorithms (14) to segment coastal settlements into distinctive types. It deviates from current practices of developing indicators to rank geographic areas and instead focuses on the similarities and differences in community vulnerability. Community classification provides policymakers and practitioners with a framework for understanding vulnerability drivers and actionable information, as well as helps to minimize the reductionism and oversimplification involved in translating the multidimensional construct of vulnerability into a single index score.
All coastal communities in the US Pacific Northwest are threatened to varying degrees by CSZ-related tsunami inundation. In this section, we first characterize community variations in population vulnerability separately in terms of exposure, demographic sensitivity, and short-term resilience of at-risk individuals to tsunamis and discuss how results from this approach may influence emergency management decisions. We then characterize population vulnerability as a combination of these factors and discuss the value of this holistic perspective.
Population Exposure.
We first classified communities in terms of exposure, here defined as the number of people and businesses in tsunami-hazard zones. This definition follows the vulnerability component of exposure described in Turner et al. (3) and Polsky et al. (4), but differs from others' use of the term to describe physical characteristics of the hazard. We explicitly recognize hazard characteristics in the hazard zone delineation and in evacuation modeling assumptions.
The tsunami hazard zones in northern California, Oregon, and Washington that are associated with a CSZ earthquake contain 94,872 residents, 42,424 employees, 486 public venues, 440 dependent-care facilities, and 2,314 businesses with a significant customer presence. These at-risk populations and businesses are distributed unevenly across 49 incorporated cities, 7 tribal reservations, and 17 counties (Fig. 1), ranging from estimates of 1 resident in Coquille to 12,322 residents in Aberdeen (Fig. 2). The majority of at-risk populations are on the Washington coast; for example, 48% of the residents in the tsunami-hazard zone for the region are in Pacific and Grays Harbor Counties.
Cluster analysis suggests that there are three distinct community groups that characterize population exposure to CSZ tsunamis (Fig. 3A). The first group includes Aberdeen, Seaside, and Eureka. On average, members of this group are 2–4 SDs above the mean in terms of the number of residents, employees, public venues, dependent-care facilities, and community businesses in tsunami hazard zones. Communities in the second group are 1–2 SDs above the mean and include Crescent City, Hoquiam, Ocean Shores, Port Townsend, and the unincorporated portions of Grays Harbor and Pacific Counties. The second group differs from the first group in terms of higher percentages of residents in the tsunami hazard zone (29% of regional totals compared with 21%) but lower percentages of employees (21% compared with 42%) and dependent-care facilities (28% compared with 43%). The third group contains the remaining communities and counties, with relatively lower numbers of at-risk population across the five categories, although certain communities have high numbers of exposed populations in specific categories (e.g., 3,846 residents in Warrenton; 1,445 employees in Newport). If risk reduction efforts emphasized communities with the highest population exposure, then resources may be focused on the seven communities and two counties of the first two groups (Fig. 3A), which together account for 50% of the residents, 63% of the employees, 53% of the public venues, 71% of the dependent-care facilities, and 64% of the community businesses in tsunami hazard zones.
Demographic Sensitivity.
We then characterized the sensitivity of communities based on the demographic characteristics of their exposed residential populations. Analysis was limited to commonly used demographic variables (2, 9) associated with block-level data in the 2010 US Census because of the small size of the hazard zone relative to larger census units. Geospatial analysis of census blocks identified the percentage of residents in the tsunami hazard zone for each jurisdiction with certain attributes of race and ethnicity, age, house structure, and tenancy. Cluster analysis of these data identified three primary community groupings. The first group (Fig. 3B) includes six tribal reservations in Washington (Hoh, Lower Elwa, Makah, Quileute, Quinault, and Shoalwater Bay), which predictably had higher percentages of American Indian or Alaska Native (ranging from 66% to 91%) compared with an average of 4% for the remaining communities in the study area. The percentage of single-mother households in the tsunami hazard zones of these communities was also high (ranging from 10% to 29%) compared with an average of 5% for the remaining communities. The percentage of residents greater than 65 y in age was relatively low (from 6% to 12%) compared with an average of 26% for the remaining communities. The other two community groupings (Fig. 3B) are distinguished by relatively minor differences in racial composition, housing tenure, and age. Basing risk reduction efforts on demographic differences may result in practitioners focusing on the needs of tribal communities (group 1), older residents (group 2), and renters and Hispanic or Latino populations (group 3).
Previous efforts to characterize resilience have focused largely on demographic and institutional characteristics (8). For local tsunami threats, the ability to reach higher ground before wave arrival is a critical aspect of population vulnerability to tsunami hazards in this region, and this can be conceived as short-term resilience. An individual has little to no resilience to survive a local tsunami if he or she must travel 15 km on foot in less than 15 min to reach high ground. Vertical evacuation in buildings may be an option for some but not all individuals, given the likelihood of destroyed or flooded structures (15). We do not consider vertical evacuation, given the lack of systematic studies across this region to gauge building performance to the CSZ earthquake and tsunami impacts.
Based on pedestrian evacuation models and assuming a slow walking speed of 1.1 m/s for evacuees, we estimate that there are 21,562 residents, 6,372 employees, 142 public venues, 50 dependent-care facilities, and 473 businesses with a significant customer presence in places where travel times out of hazard zones are greater than predicted wave arrival times. Washington contains the majority of the residents with insufficient time to evacuate (67%), followed by Oregon (29%) and California (4%), whereas Oregon has the majority of employees with insufficient time to evacuate (43%), followed by Washington (36%) and California (21%). Percentages of dependent-care facilities, public venues, and community businesses with insufficient travel time to safety vary only slightly in Washington (44–49%), Oregon (43–48%), and California (2–13%). Although Aberdeen has the highest number of residents in tsunami hazard zones, other communities, such as Seaside and Ocean Shores, have higher numbers of residents that may have insufficient time to evacuate before the arrival of the first tsunami waves (Fig. 2).
Cluster analysis suggests that there are four distinct community groups based on the number of at-risk individuals with insufficient time to evacuate (Fig. 3C). Seaside occupies a group by itself, representing the community with consistently the highest number of employees (2,435), public venues (51), dependent-care facilities (22), and community businesses (182). Ocean Shores and unincorporated Pacific County comprise a second group and differ from Seaside in terms of higher or comparable numbers of residents (5,491 and 4,272, respectively, compared with 4,450 in Seaside) but fewer employees and the suite of business types. A third group includes Aberdeen, Eureka, Long Beach, and unincorporated Grays Harbor County and are characterized by communities with relatively fewer individuals that would have insufficient time (e.g., magnitudes in the 1,000–2,000 range instead of the 2,000–6,000 range for residents). The fourth group includes all of the remaining communities and represents communities with fewer, if any, individuals that would have difficulty evacuating.
Another element of short-term resilience to tsunamis is an individual's ability to move faster during an evacuation. To demonstrate where increased travel speeds may be the most effective in saving lives, we modeled travel times assuming a fast walking speed of 1.52 m/s (13). Using this new travel speed, we estimate that there are still 15,970 residents, 4,807 employees, 102 public venues, 36 dependent-care facilities, and 328 businesses with a significant customer presence in tsunami hazard zones where evacuation travel times to safety are greater than predicted wave arrival times. The majority of the residents (77%), employees (59%), and certain business types (71%) are in Ocean Shores, Seaside, and unincorporated Pacific County (Fig. 2). A cluster analysis (Fig. 3D) suggests that there are four distinct types of places: (i) Seaside, primarily due to large presence of employees and businesses; (ii) Ocean Shores, due to the high number of residents and community businesses; (iii) Long Beach and unincorporated Pacific County, due to the moderately high number of residents; and (iv) all of the remaining communities that have very few, if any, individuals that would have difficulty evacuating if traveling at a fast walking speed.
Evacuation-modeling results can be used for risk reduction efforts in two ways. Programs that include evacuation training may focus on Aberdeen and Eureka, which contain some of the highest numbers of individuals and businesses in tsunami hazard zones but most, if not all, may have sufficient time to evacuate (Fig. 2). Mitigation planners with resources to build vertical-evacuation refuges may instead focus on communities such as Ocean Shores, Seaside, Long Beach, and the unincorporated parts of Pacific County due to their high number of individuals and businesses that are in areas where travel times out of hazard zones exceed wave arrival time.
Comprehensive Clusters of Population Vulnerability.
A combined analysis was conducted to derive overall community clusters based on (i) the number of people and businesses in the tsunami hazard zone, (ii) the demographic characteristics of residents in the zone, (iii) the number of people and businesses that may have insufficient time to evacuate assuming a slow walking speed, and (iv) the number of people and businesses that may have insufficient time to evacuate assuming a fast walking speed. Results from this analysis indicate there are 3 primary community groupings and 11 secondary community groupings (Fig. 4). Group 1 includes the majority of the communities, which have relatively low numbers of residents, employees, or customer-heavy businesses in the tsunami hazard zones that will likely have sufficient time to reach high ground before tsunami wave arrival. The three secondary clusters in this group relate to variations in demographic characteristics; for example, group 1a has relatively higher percentages of Hispanic or Latino residents and renter-occupied households, group 1b represents relatively higher percentages of residents over 65 y in age, and group 1c represents the tribal reservations with relatively higher percentages of American Indian and single-mother households.
Group 2 includes five communities and is characterized by relatively high numbers of populations in tsunami hazard zones but in areas where successful evacuations are likely given a slow or fast walking speed (Fig. 4). Three secondary community groupings reflect variations in the number of exposed populations and their ability to successfully evacuate. Group 2a represents two communities (Crescent City and Hoquiam) with relatively high numbers of exposed populations but high likelihood of successful evacuations given the short distances to high ground. Group 2b (Port Townsend) is very similar to group 2a and varies by a higher number of community businesses in the hazard zone and relatively lower percentages of residents that are Hispanic or Latino, American Indian, younger than 5 y in age, and single-mother households. Group 2c represents two communities (Aberdeen and Eureka) that have very high numbers of exposed populations that may have difficulty evacuating everyone at a slow walking speed but may be successful at a fast walking speed.
Group 3 includes three communities and two counties (Fig. 4), which are characterized by moderately high numbers of exposed populations and businesses but in areas where successful evacuations are unlikely even at fast walking speeds. The primary distinction between secondary groupings is due to increasing numbers of individuals and businesses in areas where successful evacuations are unlikely even assuming a fast walking speed, ranging from unincorporated Grays Harbor County (group 3a) on the low end to Seaside (group 3e) on the high end of the spectrum. Although Seaside has the highest number of employees and certain business types in these areas, Ocean Shores and unincorporated Pacific County (groups 3d and 3c, respectively) have higher mean values for residents. This result suggests that population vulnerability is highest for residents in Ocean Shores and unincorporated Pacific County, but is highest for customers, dependent-care populations, tourists, and employees in Seaside.
How to best reduce loss of life from future tsunamis is a complex question given the local vulnerability context and the multiple strategies that can be implemented. Although tsunami hazards are often characterized by practitioners as regional threats requiring a common response (e.g., move to high ground) with little acknowledgment of demographic considerations (10), our results identify three community groupings with distinct vulnerability issues (Figs. 1 and 4). Most of the communities (group 1) have people in tsunami hazard zones, but the magnitude of the exposed population is lower than other communities, and the populations may have sufficient time to evacuate before wave arrival. Successful evacuations are not guaranteed in these communities, because individuals still need to understand the threat, recognize signs of imminent waves, and take self-protective action. Education efforts that recognize demographic differences (e.g., age, race and ethnicity, and residents vs. tourists) may be the best course of action for these communities.
Tsunami education will be useful in group 2 communities (Fig. 4), but they could also benefit from evacuation training. Although Crescent City, Hoquiam, Port Townsend, Aberdeen, and Eureka have some of the highest numbers of individuals and businesses in tsunami hazard zones, at-risk individuals may have enough time to evacuate, especially if they had additional training on where and on how fast they may need to go to reach high ground. For example, the percentage of Aberdeen residents in the tsunami hazard zone that may have sufficient time to evacuate rises to 99% if some individuals move at a fast walking speed.
Group 3 communities (Fig. 4) may warrant consideration of vertical evacuation refuges to create safe havens, because at-risk populations may not have enough time to evacuate even at a fast walking speed. Within each group 3 community, there are likely to be multiple sites that could provide refuge, and each may provide benefits to different population groups (16).
Our results show how recognizing the variations in population exposure, demographic sensitivity, and resilience for evacuations provides advantages over existing rank-based indices that focus individually on population exposure inventories or demographic sensitivity. An emphasis on the number of individuals in hazard zones would lead policymakers to focus on group 2 communities. A focus on demographic attributes alone would lead them to focus on education efforts in communities with few people in the tsunami hazard (group 1) or in communities where successful evacuations are unlikely (group 3). An emphasis on community rankings may lead practitioners and the media to focus on communities such as Seaside and Ocean Shores and unintentionally ignore or at least downplay the other communities.
An integrated treatment of vulnerability places societal issues in a risk reduction context and provides practitioners and policymakers with actionable information for community specific interventions. However, rather than simply saying "places are different and have unique needs," our approach identifies shared risks in a way that allows for the development of knowledge networks between communities with similar issues. To leverage limited funds, public officials in one community could learn from case studies conducted in communities with similar issues or possibly work together to seek out mutually beneficial projects. For example, Seaside (OR) may have more in common with Ocean Shores (WA) because of similar evacuation challenges than neighboring communities in Oregon (Figs. 1 and 4). Officials in Aberdeen (WA) and Eureka (CA) may also find common ground in tsunami vulnerability issues. An international knowledge network of communities could provide opportunities for direct learning of effective mitigation and preparedness, response during actual disasters, and postdisaster recovery.
We hope our analysis will broaden the discussion of how communities vary in their vulnerability to sudden-onset hazards and how results can be used to develop effective risk reduction efforts. Further research should consider variations in evacuation behavior, response capabilities of at-risk individuals, the reliability of evacuation routes, and the sensitivity of the clustering modeling. Future clustering analysis could be a practitioner-driven process constructed around specific risk reduction options and/or hierarchical to provide additional nuance, as opposed to our approach that assumed no a priori knowledge of the communities or strategies. The clear mitigation-based groupings did not drive our cluster analysis, but rather serve as evidence for the utility of the approach. This observation may not be as clearly evident in other studies. Despite these limitations, our results demonstrate the highly variable nature of community vulnerability to tsunami hazards. Given the multidimensional nature of community vulnerability to natural hazards, we contend that typologies of vulnerability provide a richer characterization to practitioners and policymakers than rank-based indices.
Although we focused on deterministic hazards and current population distributions, the approach has utility for characterizing population vulnerability to probabilistic hazards, as well as incorporating changes in population distributions and landscapes over time. Variables to represent exposure, sensitivity, and resilience may be similar for other sudden-onset hazards that require pedestrian evacuation (e.g., volcanic lahars, flash floods) but could vary for other hazards. For example, short-term resilience variables may emphasize vehicular evacuation potential for hurricanes or institutional capacity for contending with chronic coastal hazards or drought conditions.
Materials and Methods
Our analysis focused on inventorying the number and characteristics of individuals in tsunami-hazard zones, modeling evacuation travel times to safety, and classifying communities with similar vulnerability attributes. We discuss here the various elements required to compile such estimates.
Tsunami Hazard Delineation.
State agencies vary somewhat in how they have delineated tsunami hazard zones associated with CSZ earthquakes; therefore, we used published zones that have similar source and modeling assumptions. Tsunami hazard zones in Oregon and in Whatcom, Skagit, Island, and San Juan counties (WA) reflect an Mw 9.0 earthquake with source parameters of the LI scenario, a deterministic scenario assuming 650–800 y of slip accumulation and a 95% CI (17). In Pacific and Grays Harbor counties, the hazard zone is based on a combination of the L1 source parameters and earlier work associated with the 1A with asperity deterministic scenario for an Mw 9.1 earthquake that assumes 450 y of slip accumulation (18). In Clallam and Jefferson counties, hazard zones in populated areas are based on the 1A with asperity scenario (19), and the undeveloped areas reflect a 25-ft contour line (11). For the two California counties, we used the statewide maximum tsunami hazard zone (20, 21), which is considered to be similar to the L1 CSZ scenario (21). Estimated arrival time of the first tsunami wave varies across the study area but is assumed to be 15 min in California and Oregon (17), 25 min for the open ocean coast of Washington (18), 45 min along the Strait of Juan de Fuca (19, 22⇓–24), 2 h for Skagit County in Washington (25), and 2.5 h for Whatcom County, WA (26).
Unit of Comparison.
Comparative analyses focused on incorporated cities, tribal boundaries, and the remaining land in the various counties, as delineated in the 2010 US Census (27).
Population Demography.
Residential distributions were generated by disaggregating population counts in 2010 Census block data (27) to residence points manually interpreted in 1-m resolution, red-green-blue (RGB)-band orthorectified imagery taken between 2009 and 2012 (28). Demographic factors, such as age, ethnicity, and tenancy, can amplify an individual's sensitivity to hazards and reduce their ability to respond (9, 29). For the residents in the tsunami zones of each community, we inventoried demographic attributes available at the census-block level and related to ethnicity (Hispanic or Latino), race (American Indian and Alaska Native, Asian, black or African American, Native Hawaiian and other Pacific Islander, and white), age (individuals <5 and >65 y in age), sex based on particular family structures (female-headed households with children under 18 y of age and no spouse present), and tenancy (group quarters and renter-occupied households). Some attributes were excluded from the statistical cluster analysis because they demonstrated low variability (white) or low percentages of the exposed population in communities (Asian, black or African American, and Native Hawaiian and other Pacific Islander). The percentage of a community's residents in the hazards zone is also calculated to determine the scope of disruption to the community that could result from a tsunami. Employee locations and counts were identified using the 2012 Infogroup Employer Database (30). The North American Industrial Classification System (NAICS) codes in this database were used to identify community support businesses (e.g., banks, government offices, grocery stores, and religious organizations), dependent-care facilities (e.g., child and elderly services, schools, and medical facilities), and public venues (e.g., accommodations and outdoor venues).
Pedestrian Evacuation Modeling.
Vehicular evacuations are not evaluated due to the probable earthquake damage to roads (15). Pedestrian travel times to safety are based on an anisotropic, path distance model that focuses on the slope and land cover of an area to calculate the most efficient paths on foot to safety from every location in a hazard zone (13). Difficulty of traveling through each location is represented as a cost in terms of increased travel time. Anisotropy incorporates direction of travel and path distance calculates distances and slopes between cells of varying elevations. Land cover and elevation derived slope data are transformed into speed conservation values (SCVs) and represent the proportion of maximum travel speeds that are expected on areas with given conditions. Slope SCVs are based on Tobler's hiking function (31), and slopes were derived from 1-m resolution elevation data (32), except for less-populated portions of Washington in which coarser data, such as 3- and 10-m National Elevation Dataset data, were used. Land cover SCVs are based on Soule and Goldman's (33) energy cost terrain coefficients for certain land cover types, and land cover was derived from a supervised and manual classification of the previously described imagery (28). Cost surfaces that integrate land cover and slope variability are converted to maps of pedestrian travel times using travel speed assumptions of a slow walk and fast walk (1.1 and 1.52 m/s, respectively) (34).
Cluster Analysis.
Cluster analysis is a statistical procedure based on the assumption that each community belongs to a class, but that the class membership is unobserved and unknown. Class memberships were estimated using the K-means algorithm in the R statistical computing language version 3.0.1 (14). Independent models were run for the demographic, exposure, and short-term resilience variables. For each model, solutions with a number of output classes (K) set between 2 and 10 were estimated, with 1,000 random initializations for each setting of K. For each set of variables, a combination of manual inspection and statistical criteria (i.e., within and between cluster sum of squares) were used to select a final model. The combined classification combines the class assignments for demographic, exposure, and short-term resilience variables.
We thank Mara Tongue, Dr. Tim Frazier, and two anonymous reviewers for insightful reviews of earlier versions of the article. This research was supported by the US Geological Survey Land Change Science Program and National Science Foundation Award 1333271.
- ↵1To whom correspondence should be addressed. Email: nwood{at}usgs.gov.
Author contributions: N.J.W., J.J., and S.S. designed research; N.J.W., J.J., and S.S. performed research; J.J. and S.S. contributed new reagents/analytic tools; N.J.W., J.J., S.S., and M.C.S. analyzed data; and N.J.W., J.J., S.S., and M.C.S. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
Freely available online through the PNAS open access option.
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My Skincare Ride-or-Die's
It's been a while since I last updated you on my skincare routine, but today's post talks more so of the skincare products I CANNOT live without ⏤ my all-time faves, my ride-or-die's, the products I will repurchase when I run out!
For context, my skin type is combination (normal/oily) before I was pregnant. When I was pregnant with Adeline, my hormones went cuckoo and my skin all of a sudden became really dry! I didn't really change much in my skincare routine, but during my weird skin journey, the products I will be sharing today have proven themselves worthy whatever my skin's condition is.
This precleanse is something everyone should have in their skincare arsenal. It's the best makeup remover in my opinion because it does such a great job in removing makeup, even the most stubborn mascaras, and still remain gentle on the skin. It smells relaxing which makes the whole "night time routine" more enjoyable.
2. Dermalogica Special Cleansing Gel
I always double cleanse because that's just how I roll, also because the precleanse leaves my skin a little oily. This cleansing gel is so gentle on the face that I use this to remove the excess oils around my eyes without stinging them. After I rinse this off, I just feel so clean and refreshed. It's unscented and a little bit of product goes a long way!
3. Dermalogica Daily Microfoliant
I don't use this everyday even though it says "daily" on the name, but when I do, my skin feels like a baby's bottom! It's the gentlest exfoliant I've ever used on my face. It gets rid of dead skin cells and leaves my skin very smooth and bright.
This is what I use as a toner. It's a cleanser, toner, and essence all in one. On my lazy days, I use this as my only skincare step and then moisturizer.
5. La Prairie Skin Caviar Essence-In-Lotion
My skin LOVED this stuff all throughout my pregnancy. Because my skin became dry, this product definitely helped my skin retain moisture. Whenever I used this essence, my skin felt like it just drank a glass of water. It smells amazing, and is every bit luxurious! It's my favorite part in my night time routine. Is it worth its price tag? Definitely! I was sent this bottle in exchange for a post, but I will absolutely purchase this once I run out.
6. Kiehls Midnight Recovery Eye Cream
The eye cream that really helps diminish my dark circles! I've been using this since the day Kathleenlights mentioned it in her video - that was years and years ago! Though it's pricey for such a small tube, it goes a long long way even when it's used daily!
7. Dermalogica Active Moist • Dermalogica Sleep Sound Cocoon Gel-Cream
For my day time skin care routine, I just wash my face with water and apply my day time moisturizer which is Dermalogica's Active Moist. It's very moisturizing but still lightweight, and it's a great base for makeup.
At night, I use something a little more special and this gel-cream from Dermalogica instantly became a fave when I got it! I got the LaMer gel moisturizer at around the same time I got Dermalogica's but I prefer the hydration the Sleep Sound Cocoon gives me. I really feel like my skin looks restored and well-rested in the morning whenever I use this gel-cream the night before. And because of it is a gel rather than a cream, it's so lightweight on the skin! Definitely recommend this!

subset: commoncrawl


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Please stay after the film for a discussion with local experts and community leaders.
About Indie Lens Pop-Up: Indie Lens Pop-Up is a neighborhood series that brings people together for film screenings and community-driven conversations. Featuring documentaries seen on the PBS series Independent Lens, Indie Lens Pop-Up draws local residents, leaders, and organizations together to discuss what matters most, from newsworthy topics to family and relationships. Make friends, share stories, and join the conversation. Can't attend in person? Find Independent Lens on Facebook for information on our online Pop-Up events.
This series is a partnership between ITVS, WPT, and Madison Public Library.


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Metanoia Drawing
Metanoia Drawing
"Metanoia" came from many steps in the process, including a final drawing as seen here. It measures 9" x 12" and is matted to 11" x 14." Created with graphite on watercolor paper, this final drawing was scanned and then enlarged to the 18" x 24" final size and transferred, which the final piece was created from.
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Custom journal maker Jenni Bick has returned to her hometown D.C. to open her first brick-and-mortar store in Dupont Circle.
The new Jenni Bick Custom Journals shop celebrated its grand opening at 1300 Connecticut Ave. NW last month, expanding an online brand that's existed since 1999, according to a release. The stationery store specializes in customized notebooks, journals and photo albums designed in Bick's own workshop, in addition to brands including Moleskine, Leuchtturm 1917, Paperblanks and a host of artisanal Italian collections.
Based in Martha's Vineyard, Mass., Bick names Oprah Winfrey, Carly Simon, Robin Wright and Sean Penn as past customers, in addition to corporate clients including Google. With the Dupont store she returns to her roots in Washington, where she grew up and also where she began making books 30 years ago in her husband's Adams Morgan bookstore, according to the release.
Jenni Bick Custom Journals is open seven days a week for walk-ins and private appointments. The store (online at jennibickdc.com) offers branding and logo customization for corporate clients along with "while-you-wait personalization" for customers who want to add a name or inscription to their journals and books, the release says.


text: Weather is a big variable that tends to be overlooked in self defense. Here in Ohio, things get cold. People wear hoodies, jackets, hats, gloves, etc… Knowing how to use these to your advantage as well as how they can be used against you is crucial. Here we're talking about the simple idea of using…Read More


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The Handbook of Marketing Research: Uses, Misuses, and Future Advances
Publication Year: 2006
DOI: http://dx.doi.org/10.4135/9781412973380
Subject: Quantitative Techniques for Business & Management Research, Marketing Research
The Handbook of Marketing Research: Uses, Misuses, and Future Advances comprehensively explores the approaches for delivering market insights for fact-based decision making in a market-oriented firm. Divided into four parts, the Handbook addresses (1) the different nuances of delivering insights; (2) quantitative, qualitative, and online data gathering techniques; (3) basic and advanced data analysis methods; and (4) the substantial marketing issues that clients are interested in resolving through marketing research.
- Chapters
- Front Matter
- Back Matter
- Subject Index
Part I: Foundational Design
- Chapter 1: Trusted Adviser: How it Helps Lay the Foundations for Insights
- Chapter 2: Structuring Market Research Departments and Processes for Optimal Impact
- Chapter 3: What do "Really Good" Managers and "Really Good" Researchers Want of One Another?
Part II: Data Collection
- Chapter 4: Deep Engagement with Consumer Experience: Listening and Learning with Qualitative Data
- Chapter 5: Questionnaire Design and Scale Development
- Chapter 6: Response Biases in Marketing Research
- Chapter 7: Online Marketing Research
- Chapter 8: Advanced Techniques and Technologies in Online Research
- Chapter 9: Sampling and Weighting
- Chapter 10: Dealing with Missing Data in Surveys and Databases
Part III: Analysis and Modeling
- Chapter 11: Basic Data Analysis
- Chapter 12: Marketing Decision Support Models: The Marketing Engineering Approach
- Chapter 13: Using Regression to Answer "What If"
- Chapter 14: Advanced Regression Models
- Chapter 15: Conjoint Analysis: Understanding Consumer Decision Making
- Chapter 16: Construction of Efficient Designs for Discrete Choice Experiments
- Chapter 17: Structural Equation Modeling
- Chapter 18: Cluster Analysis and Factor Analysis
- Chapter 19: Latent Structure Regression
- Chapter 20: Hierarchical Bayes Models
- Chapter 21: Hazard/Survival Models in Marketing
- Chapter 22: An Introduction to Data Mining
Part IV: Conceptual Applications
- Chapter 23: Ad Testing
- Chapter 24: Modeling Marketing Mix
- Chapter 25: A Guide to the Design and Execution of Segmentation Studies
- Chapter 26: Measuring Brand Equity
- Chapter 27: Customer Satisfaction Research
- Chapter 28: Measuring Customer Equity and Calculating Marketing ROI
- Chapter 29: Customer Lifetime Value
- Chapter 30: International Marketing Research
- Chapter 31: Marketing Management Support Systems and Their Implications for Marketing Research
The Handbook of Marketing Research: Uses, Misuses, and Future Advances comprehensively explores the approaches for delivering market insights for fact-based decision making in a market-oriented firm. Divided into four parts, the Handbook addresses (1) the different nuances of delivering insights; (2) quantitative, qualitative, and online data gathering techniques; (3) basic and advanced data analysis methods; and (4) the substantial marketing issues that clients are interested in resolving through marketing research.
Copyright © 2006 by Sage Publications, Inc.
All rights reserved. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher.
For information:
Sage Publications, Inc.
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E-mail: firstname.lastname@example.com
Sage Publications Ltd.
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Printed in the United States of America.
Library of Congress Cataloging-in-Publication Data
The handbook of marketing research : uses, misuses, and future advances / edited by Rajiv Grover, Marco Vriens.
p. cm.
Includes bibliographical references and index.
ISBN 1-4129-0997-X (cloth)
1. Marketing research. I. Grover, Rajiv, 1953- II. Vriens, Marco.
This book is printed on acid-free paper.
06 07 08 09 10 10 9 8 7 6 5 4 3 2 1
Acquiring Editors: Todd R. Armstrong/Al Bruckner
Editorial Assistants: Camille Herrera/Mary Ann Vail
Project Editor: Astrid Virding
Copyeditor: Gillian Dickens
Typesetter: C&M Digitals (P) Ltd.
Indexer: Juniee Oneida
Cover Designer: Candice Harman
Dedication[Page vii]
To the so many loving members of my extended family…
To Annika, Aidan, and Erin
—Marco[Page viii]
Introduction: The Changing World of Marketing Research[Page ix]The Basis for the Book
There is a growing sentiment in the business community as well as the academic field that to continue to fully satisfy the changing needs of clients, marketing research needs to be retooled. Innovative methodologies and more effective and efficient relationships between marketing researchers and clients need to be developed. The need for these changes in marketing research has been expressed by visionary academic researchers as well as professionals since more than a decade ago ("The Bloodbath," 1991; Hodock, 1990; Lesh, 1999; "Surveys Proliferate," 1990; "When Customer Research," 1993).
As businesses increasingly adopt fact-based decision-making approaches and embrace the concept of market orientation, they expect marketing research to deliver market insights. One way for marketing research to fulfill this expectation is to expand the marketing research function to incorporate the role of trusted advisers. Trusted advisers have broader knowledge base and skill sets than pure marketing researchers, thereby enhancing their capability of delivering high-quality, value-added information for decision making and market learning.
The issue of market insights is fraught with challenging facets. It is not simple or easy for market researchers to uncover or deliver insights because insights are inherently subject to an individual client's idiosyncratic evaluations and perceptions that are, in turn, based on the client's needs and wants. The characteristics of insights that render them thus are as follows: They are not obvious or logically derived from existing knowledge; they are new in that they have not been previously recognized by the client; once identified for the client, they are perceived as credible and actionable by the client; they are generally about a complex phenomenon; they have to be stated in a manner that is clear and concise for the client; and they have not necessarily been thoroughly proven or tested.
Though it is well acknowledged that insights result from creative data gathering and sophisticated data analysis, it is not adequately recognized that discovering market insights also requires that the right problems that need to be addressed by marketing research be identified and the right questions that need to be asked be posed. A problem that is right can be characterized as one that conceptually has the potential of resulting in different findings upon investigation, with each finding suggesting a different course of action for the firm—however, only the actual investigation by marketing research of the problem can reveal which one of the potential findings is true. In the practice of marketing research, enormous resources get wasted because wrong problems are selected for marketing research projects. One significant [Page x]reason for this rampant lack of proper problem definition is the inadequate level of interaction of market researchers with clients and other individuals within the company with relevant important information for the problem definition process. A trusted adviser status of market researchers allows for such interaction and, hence, for better problem definition.Highlights of the Book
This handbook of marketing research addresses the above issues of generating insights through creative data gathering, deep analytics, and right problem definition with the hope that marketing research will be able to meet client expectations. The book is organized in four sections, with each section dealing with a different aspect and ways of delivering insights. The first part of the book focuses on the insights topic. It talks about the kind of information that could be believed as insights by clients and that could be capable of eliciting "ahas" from clients. It addresses how such insights can be generated by individual marketing researchers at the project level and how they can be routinely produced at the marketing research organizational level.
The second part of the book essentially discusses techniques of gathering accurate data that are capable of yielding insights. It presents traditional quantitative data-gathering techniques, innovative qualitative techniques, and emerging online methods. It also details how accuracy and representativeness of data can be ensured through minimization of response bias, utilization of proper sampling techniques, weighting of data, and appropriate treatment of missing data.
Part III, the largest section, is devoted to data analysis. Starting with basic data analysis techniques, the section presents advanced analytics techniques that have a greater chance of producing market insights. These include models such as logit, Tobit, probit, conjoint, discrete choice, latent structure regression, structural equation, hazard/survival, hierarchical Bayes, and data mining. This section also includes a chapter on the basic philosophy of mathematical and statistical models and their use in marketing for decision support systems.
The final part of the book slices the marketing research pie in a different manner. It is structured based on the substantial marketing issues that clients would be interested in resolving through marketing research. It presents testing and modeling of advertising and other marketing mix variables, as well as conceptualization and measurement of segments, brand equity, satisfaction, customer lifetime value, and marketing return on investment (ROI). The section concludes with chapters on international marketing research and marketing management support system.
The book is targeted to users as well as to suppliers of marketing research. Given its broad target audience, efforts have been made, as far as was possible, to articulate and present the contents of the book in a reader-friendly and applications-oriented fashion. By better informing users on when and how market research should be used and suppliers on how to meet the needs of clients, the book seeks to not only prevent market research from being purchased under wrong expectations but also to elevate the level of expectations from marketing research and, thereby, of the actual performance of marketing research. By doing so, the book hopes to raise the level of satisfaction of all the stakeholders in marketing research.ReferencesThe bloodbath in market research, (1991, February 11). Business Week, pp. 72–74.(1990, September). The fall and decline of marketing research in corporate America. Paper presented at the 11th Annual Marketing Research Conference, American Marketing Association, Chicago.(1999, March). Departments that provide information used by CEOs to make decisions. Paper presented at the 45th Annual Advertising Research Foundation Conference, New York.Surveys proliferate, but answers dwindle, (1990, October 5). New York Times, p. A1.When customer research is a lousy idea. (1993, March 8). Wall Street Journal, p. 12.
Acknowledgments[Page xi]
We sincerely thank all the authors of this book who so willingly committed to this project. Without their contributions, we would not have been able to take the book to print. Their individual standing and stature in the field can only add to the credibility of the contents.
Our gratitude extends to the academic and practicing marketing researchers who reviewed the various chapters of the book without standing to gain anything in return for this painstaking task. Because of their indulgence, each chapter benefited from a second look by an expert. Our thanks go to Pascale Quester, Adelaide University, Patrick Quinlan, Adrian College, and Jo Sprague, San Jose University for their careful review of the manuscript.
We also express our appreciation for the cooperation that Al Bruckner, Todd Armstrong, Camille Herrera, Gillian Dickens, Astrid Virding, and Mary Ann Vail at Sage Publications showed us at every step. Their unwavering support was valuable to us through the effort.
Finally, we acknowledge the patience and understanding of our families, especially our spouses, in letting us take this enjoyable and rewarding ride.[Page xii]
Author Index
About the Editors[Page 699]
Dr. Rajiv Grover is the Head of the Department of Marketing and holder of the Terry Chair of Marketing at the Terry College of Business, The University of Georgia in Athens, Georgia. The Department of Marketing houses the unique Master of Marketing Research program, and through the Department's Center of Marketing Studies, it conducts several executive programs in marketing research. Dr. Grover has received several honors for his research and teaching efforts, including the O'Dell award for the best paper in the Journal of Marketing Research and the Hugh O. Nourse Outstanding MBA Teacher Award. He received a Ph.D. degree in Marketing from the University of Massachusetts at Amherst; an MBA degree from Indian Institute of Management, Calcutta; and an Electronics Engineering BTech degree from IIT, Kharagpur.
Dr. Marco Vriens is the Senior Marketing Manager of Audience Intelligence and Segmentation at Microsoft, Inc. Prior to Microsoft, he worked on the supplier side, and prior to that, he was Assistant Professor of Marketing at the University of Groningen. Dr. Vriens has consulted many leading companies such as IBM, Seagate, Philips, Dell, and others. He has published more than 50 articles, both in journals such as the Journal of Marketing Research and industry magazines such as Marketing Research, and he has also published a book, Conjoint Analysis in Marketing (1995). He received several "Best Paper" awards, including the David K. Hardin memorial award.[Page 700]
About the Contributors[Page 701]
Gerald S. Albaum is Research Professor at the Robert O. Anderson Schools of Management at the University of New Mexico, Professor Emeritus of Marketing at the University of Oregon, and a Senior Research Fellow at the IC2 Institute, University of Texas at Austin. His Ph.D. (1962) is from the University of Wisconsin-Madison.
Greg M. Allenby is Kurtz Chair in Marketing at Ohio State University. He is a Fellow of the American Statistical Association and is coauthor of Bayesian Statistics and Marketing (2005). He has authored numerous publications that have appeared in leading marketing and statistics journals and serves on the editorial boards of many distinguished journals.
Chad R. Allred earned an Electrical Engineering degree and M.B.A. from Brigham Young University (BYU). He became an Intel Product-Line Manager and Novell Marketing Director prior to earning a Ph.D. from Purdue University. He is currently an Assistant Professor of Marketing at BYU. His research interests include high-tech business-to-business exchange and marketing research technology.
Eric J. Arnould, an anthropologist, is PETSMART Distinguished Professor in the Norton School of Family and Consumer Sciences at the University of Arizona. His research appears in the major U.S. marketing journals and many social science publications. Recent investigations focus on consumer resource theory, marketing clusters, households and consumption, and multi-method research.
David Bakken is Senior Vice President and director of marketing science for Harris Interactive. He earned his doctorate in social psychology at Boston University.
Allan L. Baldinger (M.B.A., Columbia University) has spent 37 years as a marketing research practitioner. His corporate career included Research Manager at Warner Lambert, Marketing Research Director positions at Mennen and at the Advertising Research Foundation, and then VP positions at NPD, Ipsos, and MarketTools. He is widely published in Advertising Research and in Brand Equity.
Hans Baumgartner (Ph.D., Stanford University) is Professor of Marketing, Charles & Lillian Binder Faculty Fellow, and Director of Ph.D. Programs in the Smeal College of Business at the Pennsylvania State University. His research and teaching interests are in the areas of consumer behavior and research methodology.
Peter M. Bentler is Distinguished Professor of Psychology and Statistics at UCLA. Past president of the Psychometric Society and other organizations, he received the Distinguished Scientific Contributions Award (Division 5, American Psychological Association) and the Sells Award for Outstanding Career Contributions to Multivariate Experimental Psychology (Society of Multivariate Experimental Psychology).
Pradeep K. Chintagunta is the Robert Law Professor of Marketing at the Graduate School of Business, University of Chicago. His recent research focuses on factors influencing the sales of technology and pharmaceutical products. He is also interested in studying vertical and horizontal interactions among firms.
[Page 702]William A. Cook (Ph.D., University of Florida) is SVP, Research and Standards for the ARF. He left academia to research DuPont's corporate image advertising. Subsequently, he worked on consumer product advertising strategy and research at DuPont and Kraft General Foods. At Simmons MRB and Equifax NDS, he developed tools for the integration of media and marketing planning.
Wayne S. DeSarbo is the Mary Jean and Frank P. Smeal Distinguished Professor of Marketing at the Smeal College of Business at the Pennsylvania State University at University Park. His methodological interests lie in multidimensional scaling, classification, and multi-variate statistics. His marketing research interests lie in market segmentation, positioning, new product/service design, consumer choice, and strategy.
William R. Dillon is the Herman W. Lay Professor of Marketing and Professor of Statistics at the Cox School of Business, Southern Methodist University, and the Senior Associate Dean. He has published numerous articles and books in the areas of segmentation, positioning, market structure, and issues related to the use of latent class/mixture models and covariance structure models.
Xiaojing Dong is a doctoral student at Northwestern University, expecting to finish by June 2006. Her dissertation proposal, "Quantifying the Benefits of Individual Level Targeting in the Presence of Firm Strategic Behavior," won the 2005 Clayton Award. Xiaojing is from China and got her M.S. degree in Transportation from MIT.
Amber Epp is a doctoral student in the Marketing Department at the University of Nebraska-Lincoln (expected completion spring 2007). Her research examines family consumption behaviors, specifically centering on the intersection of individual, relational, and family identity enactments. Using multiple methods in her research, she works extensively with qualitative data analysis.
Curtis L. Frazier is VP-Marketing Science, Millward Brown. Previously, he taught political science, where he focused on statistical methodology, American politics, comparative politics, and politics of the developing world. He holds a Ph.D. and master's degree from the University of Houston and a B.A. from the University of Texas.
Sunil Gupta is Professor of Business at Harvard Business School. His research interests include choice models, cross-category purchase, and customer value. He has won several awards, including the O'Dell (1993, 2002) and the Paul Green (1998, 2005) awards for the Journal of Marketing Research. He serves on the editorial boards of six journals.
Raghuram Iyengar is Assistant Professor at The Wharton School of the University of Pennsylvania in Philadelphia. He has an undergraduate degree in engineering from IIT Kanpur, India, and has a Ph.D. in Marketing from Columbia University, New York. His research interests are in pricing, structural models, and Bayesian methods.
Wagner A. Kamakura is the Ford Motor Company Professor of Global Marketing at Duke University. He is a coauthor of Market Segmentation: Conceptual and Methodological Foundations, as well as numerous articles in academic journals. His current research interests are in market segmentation and market structure, CRM, and the modeling of customer satisfaction, retention, and profitability.
Kevin Lane Keller is the E. B. Osborn Professor of Marketing at the Tuck School of Business at Dartmouth College. His academic resume includes degrees from Cornell, Duke, and Carnegie-Mellon universities and faculty positions at Berkeley, Stanford, and UNC. His textbook, Strategic Brand Management, has been adopted at top business schools and leading firms around the world.
Warren F. Kuhfeld manages the multivariate models research and development group at SAS and specializes in experimental design and marketing research methods. He has developed SAS software since 1984 and has developed an extensive catalog of designs and design software. He earned his Ph.D. from the University of North Carolina at Chapel Hill.
Ajith Kumar is Professor of Marketing at Arizona State University. His primary research interests are in the development of quantitative research methodologies and applications of statistical models to market segmentation [Page 703]problems. His publications include articles in the Journal of Marketing Research, Journal of Marketing, and Psychological Bulletin.
V. Kumar (Ph.D., University of Texas, Austin) has received numerous teaching and research excellence awards and has published more than 75 articles in many scholarly journals in marketing. He was recently listed as one of the top five ranked scholars in marketing worldwide and has consulted for many global Fortune 500 firms.
Donald R. Lehmann is Professor of Business at the Columbia University Graduate School of Business. His research interests include decision making, empirical generalizations, the adoption of new products and innovations, and the value of brands and customers. He has been Executive Director of MSI and President of ACR.
Katherine (Kay) N. Lemon is Associate Professor of Marketing at Boston College's Carroll School of Management. Her research focuses on customer equity, customer asset management, and marketing strategy. Her research appears in leading marketing and management journals and has been implemented by top global firms in several industries.
Gary L. Lilien is Distinguished Research Professor of Management Science at Penn State and cofounder and Research Director of the ISBM. He holds a doctorate from Columbia and three honorary degrees. He is author or coauthor of 12 books (including Marketing Models and Marketing Engineering) and more than 100 articles.
Naresh K. Malhotra is Regents' Professor, Georgia Institute of Technology. Ranked number one based on articles published in the Journal of Marketing Research, Journal of Health Care Marketing, Journal of the Academy of Marketing Science, and International Marketing Review, he is also the recipient of the Academy of Marketing Science Distinguished Marketing Educator Award, 2005.
Dan Mallett has been a statistical consultant in media and marketing research for 35 years. Prior to starting Daniel Mallett Associates in 1986, he was Managing Director of Marketmath, Inc. He has graduate degrees (M.B.A., M. Phil) from NYU and Columbia University.
Jeff Miller is Senior Vice President of Burke, where he has overall responsibility for the Online Research practice and the Decision Sciences function at Burke, Inc. For the past 8 years, his research efforts have focused on the effective use of the Internet as a marketing research tool.
Soumen Mukherjee is a Principal at Marketing & Planning Systems (MaPS), a Boston-based strategic marketing research and consulting firm. He has more than 15 years of research experience and has extensive experience with advanced statistical methods in marketing research. He has presented and published his research in leading marketing conferences and journals.
Richard L. Oliver (Ph.D., University of Wisconsin) is Professor of Management at Vanderbilt University and has interests in consumer psychology, especially customer satisfaction, loyalty, and postpurchase processes. He is a Fellow of the American Psychological Association. Books include Satisfaction: A Behavioral Perspective on the Consumer and Service Quality: New Directions in Theory and Practice (coeditor).
Arvind Rangaswamy (Ph.D., Northwestern University) is the Anchel Professor of Marketing at Penn State and cofounder and Research Director of the eBusiness Research Center (http://www.ebrc.org). He also holds an M.B.A. from the Indian Institute of Management, Calcutta; and a B. Tech from the Indian Institute of Technology, Madras. For further details visit http://www.arvind.info.
Peter E. Rossi is the Joseph T and Bernice S. Lewis Professor of Marketing and Statistics at the Graduate School of Business, University of Chicago. His research interests include pricing and promotion, target marketing, direct marketing, micro-marketing, limited dependent variable models, and Bayesian statistical methods. He is the founding editor of Quantitative Marketing and Economics and is the Director of the Kilts Center for Marketing, GSB, University of Chicago.
Roland T. Rust is Chair of the Marketing Department and Executive Director of the Center for Excellence in Service at the University of [Page 704]Maryland. He has won numerous awards for his contributions to marketing, various journal articles, and for his book Driving Customer Equity (with Valarie Zeithaml and Katherine Lemon). He has consulted with many leading companies worldwide.
Victoria Savalei is an advanced graduate student in the Psychometrics Program at UCLA. Her research interests include structural equation modeling with incomplete and nonnormal data.
Subhash Sharma is the James F. Kane Professor of Business in the Moore School of Business, The University of South Carolina. His research interests include CRM, data mining, and global marketing strategies. He has published in leading academic journals and has authored Applied Multivariate Techniques and coauthored Scaling Procedures: Issues and Applications.
Sandip Sinharay received his Ph.D. in Statistics from Iowa State University in 2001 and is a research scientist at the Center of Statistical Theory and Practice in Educational Testing Service, Princeton, NJ. His research interests are Bayesian statistics, model checking and model selection methods, statistical computing, and educational statistics.
Jared Smith is the Manager of Online Technical Operations for Google and was the founding product manager for Novell Directory Services (NDS), where he oversaw the installed base of 19 million users worldwide. As a product manager in the Consumer Products Division of WordPerfect Corporation, his international portfolio consisted of 12 different software products in 22 countries.
Scott M. Smith, Ph.D., is the James Passey Professor of Marketing, Marriott School of Management, Brigham Young University, and founded several online survey software and research companies. Author of research methodology and modeling books, his research interests include Internet research and methodology and the development of online computer applications employing real-time data collection techniques for marketing research.
Jan-Benedict E. M. Steenkamp is the C. Knox Massey Professor of Marketing and Marketing Area Chair, Kenan-Flagler Business School, University of North Carolina at Chapel Hill. His research focuses on global marketing, effectiveness of marketing instruments, interorganizational relationships, and marketing research techniques. He has written and edited five books and published articles in Journal of Marketing, Journal of Marketing Research, Journal of Conflict Resolution, International Journal of Research in Marketing, Marketing Science, and other journals.
Christopher R. Stephens has worked in areas from theoretical physics, with Nobel laureate Gerard't Hooft, to artificial intelligence, biology, and finance. Among his honors are the Jorge Lomnitz Prize of the Mexican Academy of Sciences, a Leverhulme Professorship at the University of Essex, and member of the editorial board of Genetic Programming and Evolvable Hardware.
R. Sukumar has served as a faculty member in Marketing at business schools, including Thunderbird and the University of Maryland, and also served as Vice President, Research Sciences for IPSOS-Vantis. He has a degree in Mechanical Engineering and an M.B.A. and Ph.D. from the University of Pittsburgh.
Gerard J. Tellis (Ph.D., Michigan) is Professor of Marketing and Neely Chair of American Enterprise at Marshall School of Business, University of Southern California. He was Visiting Chair at Cambridge University, United Kingdom, and Distinguished Visitor, Erasmus University, Rotterdam. He has published more than 70 papers and books, which have won numerous awards (http://www-rcf.usc.edu/~tellis/).
Gerrit H. Van Bruggen is Professor of Marketing at RSM Erasmus University in the Netherlands. Most of his research deals with the application of information technology in marketing. His articles have appeared in journals such as the Journal of Marketing, Journal of Marketing Research, Marketing Science, Management Science, and Information Systems Research.
Michel Wedel has an MS.C. in Biomathe-mathics (1981), an MS.C. in Statistics (1986), and a Ph.D. in Marketing (1990). He is the [Page 705]Dwight F. Benton Professor of Marketing at the Ross School of Business at the University of Michigan. His research interests are in the application of statistical and econometric methods to marketing problems.
Berend Wierenga is Professor of Marketing at RSM Erasmus University in Rotterdam. His research focuses on marketing decision making and marketing decision support, and his articles have been published in the Journal of Marketing, Marketing Science, Management Science, and other journals. He is also the coauthor of Marketing Management Support Systems (2000).
Gerald Zaltman is a senior partner in Olson Zaltman Associates, a market research and consulting firm specializing in developing deep understandings of consumers for use in developing marketing and corporate strategy. He is also the Joseph C. Wilson Professor of Business Administration at the Harvard Business School and codirector of the Mind of the Market Laboratory and has received several awards for his work.
Lindsay Zaltman is a Managing Director at Olson Zaltman Associates, a marketing research firm. He lectures extensively at various Fortune 500 companies and conferences within and outside of the United States. He earned a master's degree in Marketing Research from the University of Georgia and a B.A. in Anthropology from the University of Maine.
Valarie A. Zeithaml (Ph.D., Maryland) is the Roy and Alice H. Richards Bicentennial Professor and M.B.A. Associate Dean at the Kenan-Flagler Business School of the University of North Carolina, Chapel Hill. Coauthor of Delivering Quality Service (1990), Driving Customer Equity (2000), and Services Marketing (2006), she has won numerous awards for teaching journal articles, andDriving Customer Equity.
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Two iconic tales of love and laughterPublished : 12:01 am December 1, 2018 | No comments so far | |
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Cinnamon Life continues to bring the best of West End to Colombo
To find out more about Mamma Mia! and to book your tickets now, visit www.cinnamonboxoffice.comor call 07 1 711 8111.
Following the immense success of The Sound of Music, Cinnamon Life is set to bring yet another iconic West End Production to Colombo – Mamma Mia! A tale of love and laughter and a daughter's trip down the aisle with three possible fathers, Mamma Mia! is one of the world's best-loved musicals of all time and will be performed for the first time in South Asia at the Nelum Pokuna Theatre from the 22nd -30th of December.
Filled with smash hits by Swedish pop group ABBA, and produced by Benny Anderson and Bjorn Ulvaes, Mamma Mia! is the ultimate feel good show, that will brighten up the holiday season for the entire family. A worldwide phenomenon, Mamma Mia! is a vibrant, modern production, whilst The Sound of Music told a more traditional tale and was equally iconic in its own right.
Both productions are masterpieces that have had incredible influencing power and have impacted people across generations. Having touched audiences regardless of their nationalities or backgrounds, these stories are both filled with important life themes that resonate with people from all walks of life. However, both productions are also unique and different in their own way; in their tonality, storytelling and thematic overtones. The Sound of Music (TSOM) is centred around a traditional family structure, aspirations of settling down and self expression. The characters in TSOM focus on finding their place in society, whilst in Mamma Mai! the characters don't conform to the traditional expectations of society, and the play is all about discovering inner strength and forging one's own path in the world.
Both musicals seem to feature a missing part of a puzzle – a person that completes the story. In the Sound of Music, Maria emerges as the mother and wife figure who fills an important void for the Von Trapp family, whilst in Mamma Mia!, the story calls for a partner for Sophie and a partner for her mother Donna. Both plays focus on the importance of having meaningful and fulfilling relationships with the people who are dear to you and bring out the best in you.
Commenting on the play, Dileep Mudadeniya, Vice President John Keells Holdings, CEO of Cinnamon Life Mall and Head of Brand Markeing Team, Cinnamon Hotels and Resorts said: "From a traditional classic like The Sound of Music to a production fused with modern thinking and a contemporary storyline like Mamma Mia!, Cinnamon Life is proud to offer residents of Colombo yet another world-class West End production. Ideal for the festive season, Mamma Mia! is a feel-good entertainment option that is well suited for the entire family. A "city within a city", Cinnamon Life will serve as an entertainment hub in the region, that will transform Colombo and offer residents countless lifestyle enhancing opportunities. This is the second West End production that we have brought to South Asia for the first time, and it provides a glimpse into the inspiring and vibrant moments and experiences that Cinnamon Life has to offer."
For the first time in the country, Cinnamon Life will also give young theatre fans the chance to participate in an exclusive Mamma Mia! workshop, which will be run exclusively for children and youth. To give your child the chance to participate in this one-of-kind opportunity that will enable them to work and learn from world-renowned West End choreographers and stars; Jamie Wilkins and Courtney George, simply buy tickets for two adults and children for the show. A handful of lucky participants will then be selected to attend the fully interactive and free of charge workshop, which will be conducted on the 28th of December.
To find out more about Mamma Mia! and to book your tickets now, visit www.cinnamonboxoffice.com
- The Nelum Pokuna Theatre from the 22nd -30th of December