Somebody has told you to reduce your product range, simplify your service tiers, or cut the options on your pricing page. The evidence they were relying on, whether or not they knew it, comes from a jam display in a Californian supermarket in 1995.
Key Takeaway
Iyengar and Lepper's field experiment found shoppers roughly ten times more likely to purchase from a six-jam display than a twenty-four-jam one[1]. A 2010 meta-analysis across roughly fifty studies found the mean effect of larger choice sets was approximately zero[2]. A 2015 meta-analysis of 99 observations reconciled the two by identifying four moderating conditions, and reported that accounting for them restored a significant overall effect[4][5]. And a six-nation survey of 7,436 people found that in five of the six, choice deprivation, not overload, was the dominant experience[7].
Our Grade For This Claim
Applying the scheme from the first article in this series.
The unmoderated claim, that more choice reduces purchasing, is Grade D. A meta-analysis across roughly fifty studies found a mean effect of approximately zero[2], and a subsequent field experiment with actual shoppers found the number of options did not affect the average probability of purchase[6]. As a general rule it is not supported.
The moderated claim, that choice overload occurs reliably under four specific conditions, is Grade B. It rests on a meta-analysis of 99 observations that reports the effect returning once moderators are modelled[4]. We did not obtain the effect sizes and do not state them.
The original jam study is Grade C. It is a real field experiment with a striking result on 242 participants, and commercial replications in grocery settings are reported to have failed to reproduce it[5].
The practical translation, ours: do not cut your range because of the jam study. Cut it, or do not, after checking whether your situation satisfies the four conditions set out below.
A Note On Method
Everything here is verified to August 2026 against the primary literature or its published abstracts.
Our sources conflict on the conversion figures of the original study, and we set that out in its own section rather than repeating the version that produces the neater number.
They also give the 2010 meta-analysis two different titles and two different descriptions of its scope. We report both.
We did not obtain the full text of Iyengar and Lepper (2000), Scheibehenne and colleagues (2010), or Reutskaja and colleagues (2022). We obtained portions of the Chernev, Böckenholt and Goodman review from the author's own hosted copy[9].
One claim about failed commercial replications comes from a commercial publication and is flagged where it appears[5].
Where we compute anything from published figures, we say so and show the working. This article is a review of consumer research and is not marketing, pricing or investment advice.
The Study Everyone Quotes
The original, described accurately.
Iyengar and Lepper published When choice is demotivating: Can one desire too much of a good thing? in the Journal of Personality and Social Psychology in 2000[1][8].
The field component was run at an upscale Bay-area grocery store, identified by one source as Draeger's Market[3], with another placing the experiment at a Palo Alto grocery store in 1995[5]. The design compared a tasting display of 24 jam varieties against one of 6.
The headline results as generally reported: the 24-jam display attracted more shoppers, with 60 percent stopping against 40 percent at the smaller display, while purchase rates reversed, at 30 percent from the six-jam display against 3 percent from the twenty-four[3]. That is the origin of the widely quoted ten-to-one ratio.
One source gives the field sample as n = 242, alongside two laboratory studies[5].
Two observations, ours, before the complications.
The attraction and conversion effects run in opposite directions, which is the genuinely interesting structure and is usually dropped from the retelling. More variety drew people in and fewer of them bought.
And the result is a real field experiment, not a laboratory artefact. Whatever else is true, shoppers in an actual store behaved this way on that occasion.
A Conflict In The Figures
Something our sources disagree about, in the single most-quoted number in consumer psychology.
One account reports the six-jam display converting at 30 percent against 3 percent, giving the ten-to-one ratio[3].
Another states that the six-jam display attracted 40 percent of shoppers and converted 40 percent[5].
Those cannot both be right. On our own arithmetic, a 40 percent conversion against 3 percent would give a ratio of roughly 13.3 to 1, not the ten-to-one that both sources report.
We did not obtain the paper and do not resolve which figure is correct.
Two observations, ours.
The internal inconsistency in the second source, quoting 40 percent while also reporting a tenfold difference, suggests a transcription error somewhere in the secondary literature rather than a genuine dispute about the data.
But the broader point stands and is worth sitting with. A finding cited in thousands of business presentations has its central numbers reported inconsistently by careful secondary sources. Anybody quoting it should be quoting the paper.
The Doctrine Built On It
What the business world did with the result. This section is our own analysis.
The finding travelled unusually well, for three reasons.
It was counterintuitive, which makes it memorable and quotable.
It was actionable in a way most psychology is not. Reducing an assortment is a decision a manager can make on a Tuesday.
And it licensed something people wanted to do anyway: simplify a product line, kill underperforming variants, reduce inventory complexity. Those are frequently good decisions for reasons of cost, focus and working capital that have nothing to do with consumer psychology.
Our own view is that the third factor explains most of the doctrine's durability. Range rationalisation is often correct on operational grounds. The jam study supplied a psychological justification for a conclusion that was independently defensible, and the justification then outlived scrutiny because nobody had cause to test it.
That is a general hazard worth naming. A behavioural finding that supports something you were already inclined to do receives far less scepticism than one that contradicts you.
Fifty Studies, Effect Of Zero
The challenge, published a decade later.
Scheibehenne, Greifeneder and Todd published a meta-analytic review of choice overload in the Journal of Consumer Research in 2010[2].
Our sources describe its scope in two ways. One says it covered 63 conditions from 50 experiments and reports the mean effect size as d = 0.02[3]. Another says the authors aggregated 50 published and unpublished studies covering approximately 5,000 participants, with the average effect approximately d = 0[8].
Our sources also give the paper two different titles, one rendering it as Can there ever be too many options?[3] and another as Can there ever be too much of a good thing?[8]. We report both and did not resolve it.
Two observations, ours.
The inclusion of unpublished studies, if accurate, is methodologically important. As the first article in this series described in the ego depletion case, the gap between published and unpublished results is frequently where an effect lives or dies.
And d = 0.02 is not a small effect. It is no effect. By conventional benchmarks a small effect begins around 0.2, an order of magnitude larger.
Zero On Average Is Not Zero Everywhere
The finding within the finding, and the reason this story does not end in 2010.
The 2010 meta-analysis did not report a literature quietly clustered around no effect. It reported one that was highly heterogeneous, with some studies showing strong choice-overload effects, some showing no effect, and some showing the opposite, more choice producing better outcomes[8].
That distinction is the whole article, and this framing is ours.
A mean of zero can arise two ways. Nothing is happening anywhere, or large effects in both directions are cancelling.
The reported heterogeneity points firmly at the second. Which means the correct conclusion in 2010 was not that choice overload is a myth. It was that the literature had been asking the wrong question: not whether more choice helps or hurts, but under what conditions it does each.
Three consequences.
A practitioner who took the 2010 result as a debunking, and concluded assortment size does not matter, drew an unsupported conclusion from it.
So did one who ignored it and carried on citing the jam study.
And the useful work after 2010 was necessarily about moderators, which is where the field went.
How Far From The Mean The Jam Study Sits
An arithmetic check, computed by us from figures the later literature quotes.
The Chernev review reproduces data from the third study in the original paper. Participants in the small assortment condition were more satisfied than those in the large assortment condition, at M = 6.28 (SD 0.54) against M = 5.46 (SD 0.82). On the binary measure, those given the smaller assortment were more likely to purchase, at 16 out of 33 against 4 out of 34[9].
Our own calculations from those figures.
The purchase rates are 48.5 percent against 11.8 percent, a ratio of about 4.1 to 1. That is a large effect and it is not the ten-to-one of the field study, which is worth noting because the two are frequently discussed as though they were the same result.
On the satisfaction measure, assuming equal group sizes and pooling the standard deviations, we calculate a standardised difference of approximately d = 1.18.
Set that against the meta-analytic mean of d = 0.02[3].
Two observations, ours.
A single study at roughly 1.18 sitting in a literature whose mean is 0.02 is either an outlier or evidence of a strongly moderated effect. Those are the only two readings available, and the subsequent literature took the second.
We flag that our d = 1.18 is our own calculation from two summary statistics, assumes equal group sizes, and is offered as an order-of-magnitude comparison rather than a precise estimate. It is not a figure from the paper.
The Four Conditions
The reconciliation, and the practically useful part of this entire literature.
Chernev, Böckenholt and Goodman published Choice overload: A conceptual review and meta-analysis in the Journal of Consumer Psychology in 2015, reanalysing 99 observations[4][10].
They identified four moderators of choice overload[3]:
Choice set complexity.
Decision task difficulty.
Preference uncertainty.
Decision goal.
A summary of the result states that when four conditions are present, being a complex choice set, a difficult decision task, uncertain preferences, and an effort-minimising decision goal, choice overload is reliably triggered; and that accounting for these moderators restored a significant overall effect, resolving the apparent contradiction with the near-zero finding[5].
We note that this characterisation comes from a commercial publication summarising the paper, and that we obtained the paper only in part. We did not obtain the restored effect size and state none.
Our own observation on why this matters more than either headline result. The 2010 and 2015 papers are usually presented as opponents. On this reading they are not. The first established that the effect is not general; the second established where it lives. Together they are a better answer than either alone, and the sequence is what a functioning research literature looks like.
Applying Them To A Real Business
Turning four academic moderators into four questions. This translation is ours.
Is the choice set complex? Options that differ on many attributes at once, or on attributes that are hard to compare directly, are complex. Six insurance policies differing on eight dimensions are more complex than sixty t-shirts differing on colour.
Is the decision task difficult? Difficulty is about the decision, not the product. Time pressure, an unfamiliar category, an irreversible commitment and a high stake all raise it.
Are the customer's preferences uncertain? A buyer who knows exactly what they want is largely immune. One who is discovering what they want as they look is not. First-time buyers of a category are the clearest case.
Is the customer's goal to minimise effort? Someone browsing for pleasure is in a different mode from someone trying to get a necessary purchase over with.
Two consequences, ours.
These conditions describe professional services and considered purchases considerably better than they describe retail shelves. An accounting firm's service tiers, an insurance product range, a software pricing page and a construction quote all tend to score high on complexity, difficulty and preference uncertainty.
Which suggests the doctrine may have been aimed at the wrong industry. It was derived from groceries, popularised for retail, and may apply most strongly to the complex, high-stakes, unfamiliar purchases where nobody thinks to apply it.
We offer that as an inference from the stated moderators, not as a finding from the literature.
The Moderator Problem
An honest complication, visible in the Chernev paper's own account of the field.
The review notes that researchers had already identified a substantial number of moderators of choice overload before its own analysis, listing attribute alignability, consumer expectations, availability of an ideal point, personality traits and cultural norms, option attractiveness, decision focus, construal level, time pressure, product type, consumer expertise, and variety seeking, each attributed to a separate study[9].
That is eleven moderators, before the four the 2015 paper settles on.
Two observations, ours, and the first is a caution against our own enthusiasm.
A literature that produces a long list of moderators for an effect whose main effect is approximately zero is in an uncomfortable position. Every moderator is a researcher degree of freedom, and the first article in this series described what those do to a literature.
The generous reading is that the effect is genuinely conditional and the field has been mapping the conditions. The sceptical reading is that a near-null effect will always yield moderators if enough are tested.
We think the generous reading is better supported here, because the 2015 paper reduced eleven-plus candidate moderators to four through meta-analysis rather than adding a twelfth. Consolidation is the opposite signature from proliferation. But a reader is entitled to the sceptical reading and should know it exists.
What Happened In The Field
A subsequent field experiment with actual shoppers, which is the strongest test available.
A study published in 2021 examined choice-averse and choice-loving behaviour with real shoppers, using video footage of shelf behaviour[6].
Its findings, in the author's own terms. Inconsistent with Iyengar and Lepper (2000), the reduction in variety had no net effect on the probability of stopping in front of the shelf. And consistent with the meta-studies and with earlier field work, the number of options did not affect the average probability of purchase[6].
The design detail matters: the author notes that the display for the product line was constant, ruling out the possibility that different display sizes attracted motivationally different shoppers as a confounder[6].
Two observations, ours.
That confound is a real one and it is worth understanding. In the original design, the size of the display itself differed along with the number of options. A larger, more eye-catching display could attract a different mix of shoppers, some of whom were never going to buy.
Separately, a commercial source reports that multiple commercial replications in grocery settings have failed to reproduce the six-versus-twenty-four effect, and describes the ecological validity of the original as contested[5]. We did not obtain those replications and report the claim as that source's.
Eight Hundred Thousand Employees
The strongest evidence in this literature, and it is on the other side.
Iyengar, Huberman and Jiang published How Much Choice is Too Much?, examining retirement plan participation, and reported that participation across nearly 800,000 employees falls as the number of fund options rises[11].
Three observations, ours.
The scale changes the evidentiary category. This is administrative field data on a population three orders of magnitude larger than the jam study, observing an actual financial decision with real consequences.
Under the grading scheme in the first article of this series, a consistent pattern in a large field dataset is exactly the kind of evidence that survives, because it does not depend on any manipulation working.
And it is worth noting that Iyengar co-authored both. This is not a rival camp; the original researcher extended the work into administrative data.
We did not obtain the paper, and we flag one important limitation on our own account: a correlation between plan characteristics and participation rates in observational data is not the same as an experiment, and plans offering more funds may differ systematically from plans offering fewer in ways that also affect participation.
Why That Case Fits The Conditions
Our own analysis, connecting the strongest evidence to the four moderators.
Score a retirement fund menu against the four conditions.
Choice set complexity: very high. Funds differ on strategy, fee, risk, holdings and historical return simultaneously, and several of those are difficult to compare directly.
Decision task difficulty: very high. The consequences are large, distant, and hard to evaluate.
Preference uncertainty: very high. Most employees do not have a settled preference over asset allocation and are forming one at the moment of choosing.
Effort-minimising goal: usually yes. This is a task most people are trying to complete rather than enjoy.
All four conditions are satisfied, strongly.
Two consequences.
The largest and best-evidenced choice overload effect we located occurs in precisely the setting the moderator framework predicts, which is a meaningful piece of internal consistency in a literature that has not had much of it.
And it reinforces the earlier inference. If the effect concentrates in complex, difficult, unfamiliar, effort-minimising decisions, then financial and professional services are where it matters, and groceries are close to the least likely place to find it.
Five Nations Out Of Six
The finding that reframes the entire doctrine, and it is recent.
Reutskaja, Cheek, Iyengar and Schwartz published a cross-national survey in the Journal of International Marketing in 2022, with n = 7,436 across six nations[7].
The reported result: in Brazil, China, India, Japan and Russia, choice deprivation, meaning wanting more options than were available, was the dominant experience, and was more strongly linked to reduced satisfaction. Only in the USA was choice overload commonly reported[7].
Three consequences, ours.
A body of consumer doctrine exported worldwide rests on a phenomenon that, on this evidence, is commonly experienced in one of the six nations studied.
The opposite problem is the more common one in five of them, and it is associated with worse satisfaction. A business in those markets that reduces its range on the strength of the jam study is acting against the local evidence.
And once again Iyengar is a co-author. The researcher whose 2000 study founded the field co-authored the 2022 study establishing its cultural boundary. That is how the process is supposed to work, and it is worth saying plainly, because the popular framing of replication disputes as adversarial obscures it.
We did not obtain this paper and rely on a secondary description of it[5]. Given how much weight the finding carries, anyone relying on it should obtain the original.
The Opposite Problem
An implication that almost nobody in business considers. This section is our own analysis.
If choice deprivation is a real and measurable phenomenon associated with reduced satisfaction[7], then range reduction has a cost as well as a benefit, and the cost is invisible in the way this series has repeatedly found costs to be invisible.
Three consequences.
A business that cuts its range and sees revenue hold has learned nothing about whether it lost customers who wanted the removed option, because those customers do not appear anywhere.
The customers most likely to want an unusual variant are frequently the ones with the most specific needs and the least price sensitivity, which is not the segment to shed by accident.
And the measurement asymmetry is stark. Inventory savings from a range cut are countable. Sales to a customer who did not find what they wanted are not.
This is the same structural point the second article in this series made about error reporting: a metric that improves may be measuring the disappearance of the evidence rather than the disappearance of the problem.
The Scale Asymmetry
A summary observation, computed by us.
Set the sample sizes side by side.
The jam study field experiment: 242 participants[5].
The 2010 meta-analysis: approximately 5,000 participants across roughly fifty studies[8].
The cross-national survey: 7,436[7].
The retirement plan study: nearly 800,000 employees[11].
The single most-quoted study in this literature is the smallest by roughly three orders of magnitude.
Two observations, ours.
Sample size is not everything, and a well-run field experiment on 242 people can be more informative than a large observational dataset for causal purposes. We are not arguing from size alone.
But the inverse relationship between how often a study is cited and how large it is is a pattern worth noticing, and it is not specific to this literature. Memorability and evidentiary weight are close to uncorrelated, and the business world selects on the former.
What To Actually Do
Do not reduce your range because of the jam study. A meta-analysis across roughly fifty studies put the mean effect at approximately zero, and a later field experiment found no effect of option count on purchase probability.
Score your situation against the four conditions. Complex choice set, difficult decision task, uncertain preferences, effort-minimising goal. Choice overload is reported as reliably triggered when all four are present.
Expect it in professional services, not on shelves. The strongest effect we located is in retirement fund menus, which satisfy all four conditions strongly.
Reduce the difficulty before reducing the number. If the mechanism runs through complexity and task difficulty, better comparison tools, clearer attribute framing and a sensible default may address the same problem without removing options.
Count what a range cut costs, not only what it saves. Inventory savings are countable; the customer who did not find what they wanted is not.
Do not assume this travels internationally. In five of six nations surveyed, choice deprivation rather than overload was the dominant experience.
Separate the operational case from the psychological one. Range rationalisation is frequently correct for cost, focus and working capital reasons. Those arguments stand on their own and do not need this literature.
If you cut, test it. An assortment change is one of the few behavioural interventions a business can run as a genuine experiment, by region, by channel or by period.
Treat first-time buyers differently. Preference uncertainty is one of the four conditions, and it concentrates in people new to your category.
Quote the paper, not the retelling. Our sources disagree on this study's central conversion figures and on the title of the meta-analysis that challenged it.
The Honest Version Of The Advice
Where we come out, stated plainly.
The popular claim is more choice reduces sales. On the evidence we located, that is not supported as a general proposition.
The defensible claim is narrower and more useful. Where a decision is complex, difficult, and being made by someone whose preferences are unsettled and who wants it over with, adding options can reduce the probability that they decide at all.
Two things follow.
The failure mode in that situation is not that customers buy less. It is that they defer, and deferral is frequently invisible to the seller, who sees an enquiry that went quiet rather than a decision not to buy.
And the intervention that follows is not necessarily fewer options. It is reducing the difficulty of the decision, of which cutting options is one method among several and not obviously the best.
That is a smaller claim than the one usually made. It is also one we can support, which in this literature turns out to be the harder standard.
The Limits Of This Analysis
Several caveats matter. This article reviews consumer research and is not marketing, pricing or investment advice. Everything is verified to August 2026. We did not obtain the full text of Iyengar and Lepper (2000), Scheibehenne and colleagues (2010), Reutskaja and colleagues (2022), or Iyengar, Huberman and Jiang (2004), and obtained the Chernev and colleagues review only in part from the author's hosted copy. Our sources conflict on the original study's conversion figures, one giving 30 percent and another 40 percent for the six-jam display, and we do not resolve it; we note the second source is internally inconsistent, since 40 percent against 3 percent would not produce the tenfold ratio it also reports. Our sources give the 2010 meta-analysis two different titles and two different descriptions of its scope, and we report both. Our calculation of approximately d = 1.18 for the satisfaction measure in Study 3 is our own, derived from two summary statistics, assumes equal group sizes, and is an order-of-magnitude comparison rather than a precise estimate; it is not a figure from any paper. We did not obtain the effect size the 2015 meta-analysis reports after moderation and state none. The claims that commercial grocery replications failed, and the four-condition summary, come from a commercial publication and are flagged as such. The retirement plan finding is observational, and plans offering more funds may differ systematically from those offering fewer in ways that also affect participation. The inference that the effect should concentrate in professional and financial services, the deprivation-cost analysis, the four business questions and the scale-asymmetry observation are our own reasoning, not findings from the literature.
Frequently Asked Questions
Should we reduce the number of options we offer?
So is choice overload a myth?
What are the four conditions?
What is the strongest evidence either way?
Does this apply outside North America?
What is the safest thing to do with this research?
References
- Iyengar, S. S., & Lepper, M. R. (2000). When choice is demotivating: Can one desire too much of a good thing? Journal of Personality and Social Psychology, 79(6), 995–1006. DOI 10.1037/0022-3514.79.6.995. Note: we did not obtain the full text and rely on descriptions in the later literature. arxiv.org
- Scheibehenne, B., Greifeneder, R., & Todd, P. M. (2010). Meta-analytic review of choice overload. Journal of Consumer Research, 37(3), 409–425. DOI 10.1086/651235. Note: our sources render the title two ways, as Can there ever be too many options? and as Can there ever be too much of a good thing?, and we did not resolve it; we did not obtain the full text. atticusli.com
- The Behavioral Scientist. Choice Architecture: How the Design of Decisions Shapes What People Do, on the jam study's reported figures of 60 percent stopping at the 24-jam display against 40 percent at the six, with purchase rates of 30 percent and 3 percent respectively; on Scheibehenne, Greifeneder and Todd (2010) covering 63 conditions from 50 experiments with a mean effect size of d = 0.02; and on Chernev, Böckenholt and Goodman (2015) identifying four moderators, being choice set complexity, decision task difficulty, preference uncertainty and decision goal. Note: a specialist glossary resource, not peer-reviewed. thebehavioralscientist.com
- Chernev, A., Böckenholt, U., & Goodman, J. (2015). Choice overload: A conceptual review and meta-analysis. Journal of Consumer Psychology, 25(2), 333–358. DOI 10.1016/j.jcps.2014.08.002, on research having moved beyond documenting choice overload to identifying its antecedents and boundary conditions. Note: publisher record; we obtained portions of the paper via reference 9. sciencedirect.com
- HPC. What Is Choice Overload? Do Too Many Options Really Backfire?, on the jam study having been run at a Palo Alto grocery store in 1995 with a field sample of n = 242 plus two laboratory studies; on the reported figures of a 24-jam display attracting 60 percent and converting 3 percent against a six-jam display attracting 40 percent and converting 40 percent; on multiple commercial replications in grocery settings having failed to reproduce the effect, with ecological validity described as contested; on the four conditions of complex choice set, difficult decision task, uncertain preferences and effort-minimising decision goal reliably triggering overload, with accounting for these moderators restoring a significant overall effect; and on Reutskaja, Cheek, Iyengar and Schwartz (2022), Journal of International Marketing, n = 7,436 across six nations, finding choice deprivation dominant in five. Note: a commercial publication. Its conversion figure of 40 percent is internally inconsistent with the tenfold ratio it also reports, and its claims about failed commercial replications were not obtained by us. hiperformanceculture.com
- Journal of Economic Behavior and Organization. (2021). Predicting choice-averse and choice-loving behaviors in a field experiment with actual shoppers, on the finding, inconsistent with Iyengar and Lepper (2000), that reduction in variety had no net effect on the probability of stopping in front of the shelf; on the display for the product line having been held constant, ruling out different display sizes inducing selection for motivationally different shoppers as a confounder; and on the finding, consistent with the meta-studies and with the field study of Boatwright and Nunes, that the number of options does not affect the average probability of purchase. Note: a peer-reviewed field experiment; we obtained the abstract. sciencedirect.com
- Reutskaja, E., Cheek, N. N., Iyengar, S., & Schwartz, B. (2022). Journal of International Marketing, cross-national survey with n = 7,436 across six nations, reporting that in Brazil, China, India, Japan and Russia choice deprivation, meaning wanting more options than available, was the dominant experience and was more strongly linked to reduced satisfaction, and that only in the USA was choice overload commonly reported. Note: we did not obtain this paper and rely on the description at reference 5; given the weight this finding carries, a reader relying on it should obtain the original. hiperformanceculture.com
- Li, A. The Jam Study and Choice Overload: When the Moderators Matter More Than the Main Effect, on Scheibehenne, Greifeneder and Todd (2010) aggregating 50 published and unpublished studies covering approximately 5,000 participants; on the average effect of larger choice sets on conversion, satisfaction or other downstream outcomes being approximately d = 0; and on the literature being highly heterogeneous, with some studies showing strong choice-overload effects, some showing no effect, and some showing the opposite. Note: a commercial publication, not peer-reviewed; its rendering of the meta-analysis title differs from reference 3. atticusli.com
- Chernev, A., Böckenholt, U., & Goodman, J. (2015), author's hosted copy, on researchers having identified a number of moderators of choice overload including attribute alignability, consumer expectations, availability of an ideal point, personality traits and cultural norms, option attractiveness, decision focus, construal level, time pressure, product type, consumer expertise and variety seeking; and reproducing data from Iyengar and Lepper (2000) Study 3, in which participants in the small assortment condition were more satisfied than those in the large assortment condition (M = 6.28, SD = 0.54 versus M = 5.46, SD = 0.82), and those given the smaller assortment were more likely to purchase (16 of 33 versus 4 of 34). Note: the author's own hosted copy of the paper; we obtained portions only. chernev.com
- Source listing describing the Chernev, Böckenholt and Goodman (2015) meta-analysis as covering 99 observations and identifying four conditions triggering overload, and identifying Iyengar, Huberman and Jiang (2004) and Schwartz and colleagues (2002) as related work. Note: a social media post citing sources, used only to corroborate the observation count reported at reference 5; it is not authority for anything else. x.com
- Iyengar, S. S., Huberman, G., & Jiang, W. (2004). How Much Choice is Too Much? Contributions to 401(k) Retirement Plans, reported as finding that participation across nearly 800,000 employees falls as the number of fund options rises. Note: we did not obtain this paper and rely on the description at reference 10. The finding is observational, and plans offering more funds may differ systematically from those offering fewer. x.com
This article reviews consumer research and is not marketing, pricing or investment advice. No primary paper discussed was obtained in full. Sources conflict on the original study's conversion figures and on the title and scope of the 2010 meta-analysis; both conflicts are reported and neither is resolved. The standardised effect size calculated in this article is the authors' own, derived from summary statistics under an equal-group assumption, and appears in no paper. Several sources are commercial publications rather than peer-reviewed, and one is a social media post used solely to corroborate a single figure.