Family life cycle and the life course paradigm: A fourcountry comparative study of consumer expenditures

Marketers and academics have long been trying to develop effective segmentation models such as several versions of the family life cycle (FLC), which predicts behavior based on stages people are expected to sequentially experience during their lives. However, stagebased factors have been found poor predictors of consumer behavior, and assumptions held by the FLC model fall short of reality. Despite limitations inherent in family life cycle models and recent developments in other disciplines that have resulted in the replacement of the term “life cycle” with the more continuous concept of the “life course,” marketers are yet to capitalize on such recent developments for improving FLC models. This study shows how the traditional FLC model can be improved by incorporating variables from the life course paradigm (LCP). Although the databases employed do not permit the development of refined FLC stages for testing various assumptions derived from the LCP, the paper provides a “sensitizing” framework for thinking how to improve efforts to study consumers at different FLC stages

JOURNAL OF GLOBAL SCHOLARS OF MARKETING SCIENCE 2020, VOL 30, NO 1, 34–44 https://doi.org/10.1080/21639159.2019.1613913 Family life cycle and the life course paradigm: A four-country comparative study of consumer expenditures Randall Shannon Thorsten Teichert a , Thuckavadee Sthienrapapayut and Betul Balikcioglu d a , George P Moschis a,b , c a College of Management, Mahidol University, Bangkok, Thailand; bDirector of the Center of Mature Consumer Studies, Georgia State University, University Plaza, Atlanta, GA, USA; cChair of Marketing and Innovation, University of Hamburg, Hamburg, Germany; dDepartment of Business Administration, Hatay Mustafa Kemal University, Antakya, Turkey ABSTRACT ARTICLE HISTORY Marketers and academics have long been trying to develop effective segmentation models such as several versions of the family life cycle (FLC), which predicts behavior based on stages people are expected to sequentially experience during their lives However, stage-based factors have been found poor predictors of consumer behavior, and assumptions held by the FLC model fall short of reality Despite limitations inherent in family life cycle models and recent developments in other disciplines that have resulted in the replacement of the term “life cycle” with the more continuous concept of the “life course,” marketers are yet to capitalize on such recent developments for improving FLC models This study shows how the traditional FLC model can be improved by incorporating variables from the life course paradigm (LCP) Although the databases employed not permit the development of refined FLC stages for testing various assumptions derived from the LCP, the paper provides a “sensitizing” framework for thinking how to improve efforts to study consumers at different FLC stages Received 26 March 2019 Revised 11 April 2019 Accepted 29 April 2019 KEYWORDS Family life cycle; life course; life events; consumer behavior; marketing 关键词 家庭生命周期; 生活历程; 生活事件; 消费者行为; 营销 家庭生命周期及生命历程范式: ：四国消费支出比较 研究 市场销售人员和学者长期以来一直在努力开发有效的细分模型, 例如几种不同版本的家庭生命周期（FLC）, 它根据人们在生活中 预计按顺序经历的阶段来预测行为° 然而, 用阶段性因素预测消费 者行为, 结果往往不尽如人意° 而FLC模型所支撑的假设也不符合 实际° 尽管家庭生命周期固有的局限性以及近来其他学科取得的 新发展导致“生命周期”一词被“生命历程”这一更为连续的概念所 取代, 但销售人员还没有利用这些最新发展来改进FLC模型° 本研 究展示了如何通过吸收生命历程范例中的变量, 来改善传统的FLC 模型° 尽管所使用的数据库不允许开发用于测试LCP得出的各种 假设的精细FLC阶段, 但本文提供了一个“敏感”框架, 用于思考如 何改进在不同FLC阶段研究消费者的工作° CONTACT Randall Shannon Thailand A.Randall@gmail.com © 2020 Korean Scholars of Marketing Science Mahidol University, 69 Vipavadee Rangsit Road, Bangkok, JOURNAL OF GLOBAL SCHOLARS OF MARKETING SCIENCE 35 Introduction Marketers have long attempted to apply segmentation techniques to help identify groups of consumers with homogenous interests and needs in order to more efficiently market to them Segmentation based on demographics has been popular, yet these variables are found poor of consumer behavior (e.g Moschis, 2019a) Segmentation by generational cohorts may help marketers understand shared experiences and values among consumers (Schewe & Meredith, 2004), although this may be limited to specific place and time contexts and thus less generalizable Another variation of demographic segmentation is the family life cycle (FLC) model, which categorizes stages of life based partially on age and family structure in a person’s life Certain events are expected to produce homogenous consumer responses, such as buying things needed to raise a baby or a car practical for a family These events are seen as predictable in that social norms provide guidance as to when they are likely to occur (Bearden & Wilder, 2007; Du & Kamukura, 2006), and all consumers are assumed to follow each stage defined in the model (e.g single, married, full nest, empty nest, solitary survivor) Various versions of the FLC model have been proposed (e.g Schaninger & Danko, 1993), but they all share the same assumptions; and they provide limited explanations of consumer behavior (Moschis, 2019a) Family life cycle models are descriptive and largely atheoretical, ignoring potential within-group differences due to the timing of the various life events experienced, and the duration of time a person has occupied at a given stage of life Behaviors are expected to occur after transitioning into a specific stage, ignoring the fact that many consumers change their behaviors in anticipation of making a transition to a new life stage, such as from employment to retirement (Mathur, Moschis, & Lee, 2008) They also focus on predictable and socially shared transitional events (e.g marriage, empty nest, retirement), ignoring unexpected events, such as experiencing hearing loss or loss of a job Furthermore, the traditional FLC model (Wells & Gubar, 1966) may not provide satisfactory explanations of consumer behavior, as social norms have changed Marriages may occur later in life, if at all, or even multiple times Single parenthood is not uncommon, and many couples opt not to have children Retirement may be expected to occur at a particular time of life, but this event may come earlier or later than planned and consumers may re-enter the workforce later in life And increasing longevity also invalidates assumptions of homogenous behaviors, as people may experience circumstances that can affect their behaviors across longer life spans Assumptions that consumers follow a predictable and linear path through life stages and that their behavior will be the same as others in the same stage, unrelated to earlier stages or experiences in life, suffer criticism (Moschis, 2000; Rentz & Reynolds, 1983; Salthouse, 2010) Rather than focusing on fixed stages, researchers suggest a more continuous research approach, called “life course” (Giele & Elder, 1998; Moschis, 2019a) In contrast to specifying a temporal order of life stages, such as lifespan and growth models, the life course approach views age and social structure as contexts for understanding consumer behavior Life conditions and circumstances affect consumer behavior, suggesting the need for researchers to consider when events occurred, as well as their duration (Elder & Johnson, 2002; Elder, Johnson, & Crosnoe, 2003; Pulkkinen & Caspi, 2002) 36 R SHANNON ET AL This study analyzes consumer behavior across FLC stages It examines whether the addition of variables underscored by the life course paradigm adds explanatory power to the traditional FLC models used by marketers First, hypotheses are formulated based on the traditional FLC model Next, hypotheses are formulated based on the life course paradigm Finally, the study tests these hypotheses using data collected from four countries: USA, Germany, Thailand, and Turkey Background In contrast to assumptions of the FLC model, the life course paradigm considers life changes and events people experience over time, such as biological, psychological and social changes (Moschis, 2019a, 2019b) The latter approach expects to find heterogeneity in consumer behavior within stages due to the variability of life course events, their timing as to when they are experienced, as well as their duration People behave in different life contexts, and variations in their life experiences may create heterogeneity in their consumption behavior, despite their given stage in the FLC (Moschis, 2012, 2017, 2019b) People may not transition into stages at the same age, or they may not occupy the stage for the same length of time: and they may experience stages or events multiple times, such as starting a family again later in life The interaction of temporal contexts and transitional FLC events may also affect lifestyle and consumption behavior (Lee, Mathur, Kwai Fatt, & Moschis, 2012) Life events often bring on stress, which can lead to coping and the adjustment of behavioral patterns and preferences (Mathur, Moschis, & Lee, 2003; Mathur et al., 2008) Loss of a spouse or one’s job may lead to psychological and financial difficulties, which brings about stress, coping, and possibly changes in consumer behavior, even in anticipation of an event before an actual transition between stages has been made The timing and duration of these events are expected to vary across individuals, rather than being predictable and sequential, and to affect consumer behavior Hypotheses The traditional FLC model assumes that certain role transitional events define a person’s status or stage in the FLC model, leading to consumption as a result of needs for specific products and services In contrast, the LCP suggests additional factors influencing consumption It considers not only transitional events but also their timing, as this may influence behavior Furthermore, the LCP attempts to explain within-stage heterogeneity and changes in behaviors by considering additional factors, including the person’s duration at (time s/he has occupied) a particular stage as well as within-stage experiences of role transitional events, not only those that define FLC stages but also other experienced and anticipated role changing event (e.g becoming a caregiver to a disabled person) and unexpected events (e.g onset of a chronic condition) Effects of timing The life course paradigm assumes that people’s behaviors are influenced by “social clocks” that define the proper time for transition from one stage to the next To the extent the JOURNAL OF GLOBAL SCHOLARS OF MARKETING SCIENCE 37 transition occurs “on time” people are expected to engage in behaviors suitable to various roles (e.g grandparenthood, retirement) (e.g Elder, 1998) It is assumed in the FLC models that expenditures on various products are the results of a person’s on-time transition and occupation of a give stage, implying that earlier-in-life transitions to a given stage would lead to the consumption (expenditures) of stage-relevant products or services, prior to the expected transition, with such expenditures having a higher occurrence probability when transition events are experienced earlier than expected in life H1: The timing of a FLC stage-transition event affects the level of consumption spending, with early timing of transitions increasing the likelihood of stage-relevant consumption expenditures Effects of duration Although the traditional FLC models assumes that duration (time spent) in one stage has no effect on behavior, the LCP posits that the length of time in a stage may lead to stability in and continuity of behaviors (Moschis, 2019a) Most people are likely to change their behaviors upon assumption of a new role or occupation of a given stage, such as becoming a parent, than after occupying a life stage for a long time and adapting to it Thus, it is expected that: H2: Duration in a life stage affects the degree of change in consumption expenditures, with the greater length of time spent leading to fewer changes Effects of stage-transition events The traditional FLC model assumes behavior will not change before a transition to a new stage has occurred, whereas the LCP assumes that consumers may change their behaviors in anticipation of experiencing an upcoming event, such as parenthood or retirement (Moschis, 2019a) Therefore, it is hypothesized that: H3: Role changing events affect the degree of change in household consumption spending, so that consumers would be more likely to change their spending on major consumption categories to the extent they have recently experienced or in anticipation of transitions into a new role Effects of unexpected events There can also be unexpected events, such as divorce, losing one’s job or facing a chronic health issue Such events are likely to disrupt the equilibrium of consumer behaviors, leading to changes in consumption expenditures (Moschis, 2019a) H4: Unexpected events affect the degree of change in consumption spending across stages, with the experience of a larger number of unexpected events leading to more changes in consumption expenditures 38 R SHANNON ET AL Methods Sampling Data were collected from participants in the United States (N = 440), Turkey (N = 522), Thailand (N = 871), and Germany (N = 349), who were placed into stages according to the traditional FLC model The traditional FLC model focuses on the sequential order of stages in social structure along with age range Based on the traditional FLC, this study sampled consumers across three FLC stages along with age, as follows: young single stage (age 18–34), young married (age 18–34) and young-to-middle-age full nest stage (age 18–59), and middle-to-old-age empty nest stage (age 35 and over) All four countries utilized the same approach for data collection A retrospective self-administered online questionnaire was administered via convenience sampling Table shows the sample sizes obtained for each country Measures His study utilizes four variables which are hypothesized to have effects on consumer behavior across FLC stages: timing of the transitional FLC stage, duration of the FLC stage, recent role changing (programmed) events experienced in the past five years or anticipated to occur in the next five years (T ± 5), and recent nonprogrammed events (T-5) Respondents were presented with a list of events and were asked to indicate those events experienced and to indicate the year of their occurrence; and they were asked to indicate the events they anticipate and the approximate time frame (in years) they anticipated each event Timing represents the age of the respondent when they experienced a transition and moved to another stage of the FLC, and duration measures the time that an individual spends occupying a given the life stage Measures of anticipated role transitional events and unexpected events were constructed by creating summated indices (a list of events can be found in the Appendix) The normative perspective of the life course paradigm (Moschis, 2019a) suggests that people make gradual changes to their behavior in anticipation of expected changes in life The role changing events variable is the cumulation of the number of both experienced and anticipated events which occurred in the past five years or are expected to occur in the next five years Table Country-by country-FLC stage statistics Sample size Average age Age range USA Germany Thailand Turkey USA Germany Thailand Turkey USA Germany Thailand Turkey FLC Stage 110 134 228 48 27.10 25.64 28.11 27.94 19–34 18–34 20–34 21–34 FLC Stage 126 100 412 224 37.48 37.94 35.40 38.39 22–55 19–54 21–58 25–56 FLC Stage 204 115 231 250 61.27 59.27 64.42 62.58 39–76 41–78 45–85 41–89 Note: This study applied the traditional FLC concept For the definition of the traditional FLC stages, FLC stage is the young single stage, aged between 18 and 34 years old; FLC stage is the married stage comprised of young marrieds without a child (18–34 years old) and young-to-middle-age married with dependent child(ren) (age 18–59); and FLC stage is the empty nest stage, are those aged 35 and older JOURNAL OF GLOBAL SCHOLARS OF MARKETING SCIENCE 39 This study classified consumption into nine categories (see Appendix for details) of products and services posited by the FLC model (Wells & Gubar, 1966), grouped by proportion of spending based on household income The measure of change in spending (increased or decreased) was assessed by asking respondents to indicate whether their household expenditures for each product or service category changed in the past two years in comparison to the previous two years These measures were then used to create a summated scale, showing the degree of change or continuity A higher number of changes indicates a higher degree in recent changes in consumption expenditures Findings Data collected from the four countries allowed us to test each hypothesis using separate data bases Furthermore, each hypothesis was tested separately for each one of the FLC stage Due to small sample sizes of those married without children, FLC stage contained married respondents with or without children Hypothesis concerns the effects of timing of a transition into a FLC stage on the relative levels of household expenditures on products reportedly in demand by consumers at a particular stage Specifically, it was expected that those consumers who make a transition into a FLC stage in the earlier timing would be more likely to spend on products normally in demand by those at that particular or later FLC stage The partial correlations that were used for analyzing the relationships regarding this hypothesis, which could only be tested for transition from FLC stage to FLC stage and from FLC stage to FLC stage 3, did not provide strong support for H1 The expected negative relationship between timing (measured by the age at which the transition took place) and relative levels of household expenditures emerged as significant only for the Thai sample and only for the second transition (stage to stage 3) (r = −.187, p < 01) Hypotheses concerns the effects of duration on the degree of change (rather than relative levels) in consumption expenditures, expecting longer durations to lead to lower degree of change in household expenditures relevant to a particular FLC stage These hypotheses were tested across each country as well as across the three main FLC stages: Stage 1, duration at bachelorhood stage (number of years as unmarried young adults); stage 2, from bachelorhood to married; and stage 3, from married to empty nest stage Partial correlations were employed to test the hypotheses, and the results are shown in Table The results for FLC stage appear to provide a weak support for this hypothesis, as the expected relationship emerged as significant only for the Thai sample (r = −.118, p < 05); and they were in the opposite than expected direction for FLC stage for the Thai sample (r = 281, p < 001) as well as for the USA sample (r = 254, p < 01) Duration at FLC stage had no effect on the degree of change in household expenditures reported by consumers in all four countries (Table 2) Hypothesis concerns the degree of change in consumption expenditures within a particular FLC stage; it posits that consumers will be more likely to change their spending on major consumption categories to the extent that they have recently experienced or expect to experience new role transitions in the near future The data generally provides little support for this hypothesis, showing that recently experienced role-changing or anticipated role-transition events not influence the degree of change in consumption behavior within FLC stage and stage among consumers of the four countries sampled The data 40 R SHANNON ET AL Table Partial correlations between changes in household expenditures within a particular FLC stage and select variables for each country b a Changes in household USA expenditures within FLC stage Germany Thailand Turkey Changes in household USA expenditures within FLC stage Germany Thailand Turkey Changes in household USA expenditures within FLC stage Germany Thailand Turkey Duration in occupied FLC stage 0.157 −0.124 −0.118* −0.165 0.254** −0.060 0.281*** −0.056 0.030 0.093 0.074 0.064 b No of role changing events (T ± 5) −0.047 0.138 −0.100 −0.006 0.022 0.005 0.012 −0.080 0.058 −0.159* 0.008 0.136* No of recent unexpected events (T-5) −0.122 −0.109 −0.139* −0.268* 0.132 0.072 0.034 0.038 0.088 −0.117 −0.049 0.098 Note: *p < 0.05; **p < 0.01; ***p < 0.001 Control variable: social desirability, income, gender, and recent events (T ± 5) Control variables: social desirability, income, gender, and duration of the occupied FLC stage FLC stage = single stage (aged 18–34, unmarried; FLC stage = married stage (aged 18–35, with and without dependent children FLC stage = empty nest (aged 35 or older, with adult independent child(ren) aged 18 or above) a b show weak significant relationship for Turkey (r = 136, p < 05), for FLC stage 3, while the results for Germany were in the opposite direction (r = −.159, p < 05) Hypothesis concerns the effects of unexpected (nontransitional) life events on consumers’ expenditure patterns, expecting more changes in levels of consumption expenditures among consumers experiencing a greater number of such events at any one FLC stage The data appear to provide no support for this hypothesis, as shown in Table The degree of change in consumption behavior within FLC stage has a significant negative relationship with the number of unexpected life events experienced by consumers of both Thailand (r = −.139, p < 05) and Turkey (r = 268, p < 05), while no significant relationships emerge for consumers of the four countries in FLC stages and Discussion Although several versions of the original family life cycle model have been offered over several decades (e.g Schaninger & Danko, 1993), they all concur in their assumptions that large groups of people occupying different demographically-defined stages exhibit similar consumer behaviors after they make a transition into a given life stage, with little or no reference to the mechanism(s) that link(s) life transitions to consumption activities These models are descriptive, albeit useful, but they ignore within-group differences that may arise from the timing of a life transition (e.g age at marriage) or the length of time one has spent at a given stage They are also largely atheoretical, assuming that each individual occupying a particular stage has homogeneous needs with others in the same stage or group Stage-specific needs are viewed as the link between life changes and consumption, with little attention paid to the various contexts (e.g economic, technological) in which these consumers may be embedded over the course of their lives that could affect their behavior (e.g Oropesa, 1993) Such limitations inherent in the family life cycle models coupled with recent developments in life JOURNAL OF GLOBAL SCHOLARS OF MARKETING SCIENCE 41 course research “have resulted in the replacement of the term ‘life cycle’ with the more continuous concept of the ‘life course’” (Giele & Elder, 1998, p 19) This article asserts that the life course paradigm could help researchers explain differences in household expenditures between stages as well as within any given stage in the family life cycle (FLC) In addition to SES, which can serve as a contextual factor for explaining a household’s expenditure levels, expenditures on certain categories may not be at levels expected of a household occupying a particular stage in the life cycle because of anticipated transitions into the next life stage, a notion suggested by Wilkes’s (1995) analyses and supported empirically (Wagner & Hanna, 1983) Furthermore, the article argues that within-stage differences in consumer behavior at any given stage could be attributed to two types of factors The first reflects differences in transition from the previous stage to the present stage Some consumers may be better prepared for the transition, either because of their earlier timing of the onset of the anticipated transition to the next stage, or because of their greater familiarity with the next stage The second set of factors that may account for within-stage differences in consumer behavior could be event-graded changes in consumer experiences, such as abrupt changes in employment status, chronic impairment, or becoming a caregiver to an older relative Such factors likely affect a person’s or family’s consumption patterns, and differences in life circumstances likely lead to differences in consumption activities once consumers make the transition to the next life stage The authors attempt to test several of their assumptions derived from the LC paradigm as they may apply to FLC models using data collected from four countries However, their efforts are limited in that these data not permit the formation of refined FLC stages For example, the number of respondents married without children is too small to form a separate FLC stage, forcing them to combine two FLC stages into one, which may have affected results Such limitations, coupled with the study results that fall short of confirming the study’s hypotheses, raise more questions than provide answers It is not clear from the findings of this exploratory study the reason many of the study’s hypotheses were not confirmed Besides limitations inherent in the online data collection method (Goodman & Paolacci, 2017), the study raises issues related to the length of time people occupy the various stages Consumers may spend a lot more time at a given stage in life, posing questions as to the suitability of testing assumptions, such as those of duration effects, at any stage in the FLC There are also cultural issues that the study does not consider For example, Thailand is a collectivist culture that respects elders, thus some decision making may stem from older relatives, and many children live with their parents throughout adulthood, in contrast to Germany and the United States Buddhism in Thailand teaches people to live for the day and not dwell on the past or the future, which might influence savings and consumption Furthermore, there are issues concerning the measurement of variables, especially the individual consumer’s ability to provide valid estimates of aggregate family expenditures Thus, future research should consider factors relevant to the person’s rather than family’s consumption habits, such as changes in preferences for products and brands (e.g Mathur et al., 2008) Despite the study’s limitations that may have affected the results, the authors maintain that because the life course paradigm’s principles of timing and duration have developmental implications, better predictions of consumer needs can be made by incorporating variables that tap these principles into family life cycle models For example, upon making or anticipating a transition into a new family life stage, people are likely to be at a liminal 42 R SHANNON ET AL stage in their transition process and, as a result, more prone to changing their behaviors (Gentry, Kennedy, Paul, & Hill, 1995; Nobel & Walker, 1997); and they should be less likely to change their consumption habits with increasing time (duration) at the new stage (see rationale in Moschis, 2019a, Chapter, p 4) Conversely, consumers are expected to be increasingly more likely to change their consumption habits as they approach the anticipatory transition into the new life stage, a notion in line with LCP perspectives (Moschis, 2019a) and research findings reported by Wagner and Hanna (1983) and Wilkes (1995) However, given the wide landscape of limitations and issues raised by the results of this study, the present investigation should be considered purely exploratory And the application of theoretical and conceptual notions of the increasingly popular LCP to the study of FLC is suggested to future researchers not as a substitute but as a “sensitizing” conceptual framework for thinking how to improve previous FLC models Disclosure statement No potential conflict of interest was reported by the authors ORCID Randall Shannon http://orcid.org/0000-0001-6348-5576 Thuckavadee Sthienrapapayut http://orcid.org/0000-0002-3151-6160 George P Moschis http://orcid.org/0000-0003-1018-3106 Thorsten Teichert http://orcid.org/0000-0002-2044-742X Betul Balikcioglu http://orcid.org/0000-0001-7043-2544 References Bearden, W O., & Wilder, R P (2007) Household life-cycle effects on consumer wealth and well-being for the recently retired Journal of Macromarketing, 27(4), 389–403 Du, R Y., & Kamakura, W A (2006) Household life cycles and lifestyles in the United States Journal of Marketing Research, 43(1), 121–132 Elder, G H (1998) Life course and human development In W Damon & Lerner (Eds.), Handbook of child psychology (pp 939–991) New York, NY: John Wiley & Sons Elder, G H., & Johnson, M K (2002) The life course and aging: Challenges, lessons, and new directions In R A Settersen (Ed.), Invitation to the life course: Toward new understanding of later life, part ii (pp 49–81) Amityville, NY: Baywood Elder, G H., Johnson, M K., & Crosnoe, R (2003) The emergence and development of life course theory In J T Mortimer & M J Shanahan (Eds.), Handbook of the life course (pp 3–19) New York, NY: Plenum Publishers Gentry, J W., Kennedy, P F., Paul, C., & Hill, R P (1995) Family transitions during grief: Discontinuities in household consumption patterns Journal of Business Research, 34(1), 67–79 Giele, J Z., Glen, H., & Elder, G H (Eds.) (1998) Methods of life course research: Qualitative and quantitative approaches Thousand Oaks, CA: Sage Goodman, J K., & Paolacci, G (2017) Crowdsourcing consumer research Journal of Consumer Research, 44(1), 196–210 Lee, E., Mathur, A., Kwai Fatt, C., & Moschis, G P (2012) The timing and context of consumer decisions: Insights from the life course paradigm Marketing Letters, 23(3), 793–805 Mathur, A., Moschis, G P., & Lee, E (2003) Life events and brand preference changes Journal of Consumer Behavior, 3(2), 129–141 JOURNAL OF GLOBAL SCHOLARS OF MARKETING SCIENCE 43 Mathur, A., Moschis, G P., & Lee, E (2008) A Longitudinal study of the effects of life status changes on changes in consumer preferences Journal of the Academy of Marketing Science, 36(2), 234–246 Moschis, G P (2000) Consumer behavior in later life: Multidisciplinary approaches and methodological issues Research in Consumer Behavior, 9, 103–128 Moschis, G P (2012) Consumer behavior in later life: Current knowledge, issues, and new directions for research Psychology & Marketing, 29(2), 57–75 Moschis, G P (2017) Research frontiers on the dark side of consumer behavior: The case of materialism and compulsive buying Journal of Marketing Management, 33(15–16), 1384–1401 Moschis, G P (2019a) Consumer behavior over the life course: Research frontiers and new directions New York, NY: Springer Moschis, G P (2019b) Paths to successful academic research: A life course perspective Journal of Global Scholars of Marketing Science, 29(4), 372-408 Noble, C H., & Walker, B A (1997) Exploring the relationships among liminal transitions, symbolic consumption, and the extended self Psychology & Marketing, 14(1), 29–47 Oropesa, R S (1993) Female labor force participation and time-saving household technology: A case of the microwave from 1978–1989 Journal of Consumer Research, 19(4), 567–579 Pulkkinen, L., & Caspi, A (2002) Personality and paths to successful development: An overview In L Pulkkinen & A Caspi (Eds.), Paths to successful development: Personality in the life course (pp 1–16) Cambridge, MA: Cambridge University Press Rentz, J O., & Reynolds, F D (1983) Separating age, cohort, and period effects in consumer behavior Journal of Marketing Research, 20(1), 12–20 Salthouse, T A (2010) Major issues in cognitive aging New York, NY: Oxford University Press Schaninger, C M., & Danko, W D (1993) A conceptual and empirical comparison of alternative household life cycle models Journal of Consumer Research, 19(4), 580–594 Schewe, C D., & Meredith, G (2004) Segmenting global markets by generational cohorts: Determining motivations by age Journal of Consumer Behavior, 4(1), 51–63 Wagner, J., & Hanna, S (1983) The effectiveness of life cycle variables in consumer expenditure research Journal of Consumer Research, 10(3), 281–291 Wells, W., & Gubar, G (1966) Life cycle concept in marketing research Journal of Marketing Research, 3(4), 355–363 Wilkes, R E (1995) Household life-cycle stages, transitions, and product expenditures Journal of Consumer Research, 22(1), 27–42 Appendix Life events and consumption categories used in summated scales Role-changing-events scale (1) (2) (3) (4) (5) (6) (7) (8) Completion of schooling (EE) Leaving parents’ house (EE) Starting work for the first time or after not working for a long time (EE/AE) Becoming a grandparent (EE/AE) Retirement (EE/AE) Getting married (AE) Becoming a parent (AE) Becoming empty nester (AE) Note: EE denotes an experienced event, AE denotes an anticipated eventi Role-changing events were constructed by a summating scale to form a 0-to-8-point index Each rolechanging event that people “have experienced within the past five years” was coded as ‘1’ 44 R SHANNON ET AL and otherwise it was coded as ‘0,’ the same with “anticipated to experience within the next five years” items Unexpected (nonprogrammed) events scale (1) (2) (3) (4) (5) (6) (7) (8) Moving to a different location Divorce or separation Death of father Death of mother Life threatening illness, major injury/accident, or surgery Loss of job/business Death of a spouse/lifetime partner Chronic condition diagnosed Note: Each unexpected (nonprogrammed) event that people had experienced within the past five years was coded as ‘1’ otherwise it was coded as ‘0.’ Household expenditures classified in product/service categories (1) (2) (3) (4) (5) (6) (7) (8) (9) Clothing and personal care (FLC-stage-1 consumption category) Transportation expenses/Vehicles expenses (FLC-stage-2 consumption category) Travel and leisure* Housing (FLC-stage-2 consumption category) Investments/Savings (FLC-stage-2 consumption category) Education (FLC-stage-2 consumption category) Other everyday expenses/Food expenses (FLC-stage-2 consumption category) Healthcare services and drugs (FLC-stage-3 consumption category) Donations (FLC-stage-2 consumption category) Note: Asterisk (*) denotes an item that could not be represented in any FLC-stage-specific consumption category  ... products and brands (e.g Mathur et al., 2008) Despite the study? ??s limitations that may have a? ??ected the results, the authors maintain that because the life course paradigm’s principles of timing and. .. a list of events and were asked to indicate those events experienced and to indicate the year of their occurrence; and they were asked to indicate the events they anticipate and the approximate... of life stages, such as lifespan and growth models, the life course approach views age and social structure as contexts for understanding consumer behavior Life conditions and circumstances a? ??ect