  Let $V$ be a set of $n$ points in $\mathbb{R}^d$, called voters. A point
$p\in \mathbb{R}^d$ is a plurality point for $V$ when the following holds: for
every $q\in\mathbb{R}^d$ the number of voters closer to $p$ than to $q$ is at
least the number of voters closer to $q$ than to $p$. Thus, in a vote where
each $v\in V$ votes for the nearest proposal (and voters for which the
proposals are at equal distance abstain), proposal $p$ will not lose against
any alternative proposal $q$. For most voter sets a plurality point does not
exist. We therefore introduce the concept of $\beta$-plurality points, which
are defined similarly to regular plurality points except that the distance of
each voter to $p$ (but not to $q$) is scaled by a factor $\beta$, for some
constant $0<\beta\leq 1$. We investigate the existence and computation of
$\beta$-plurality points, and obtain the following.
  * Define $\beta^*_d := \sup \{ \beta : \text{any finite multiset $V$ in
$\mathbb{R}^d$ admits a $\beta$-plurality point} \}$. We prove that $\beta^*_2
= \sqrt{3}/2$, and that $1/\sqrt{d} \leq \beta^*_d \leq \sqrt{3}/2$ for all
$d\geq 3$.
  * Define $\beta(p, V) := \sup \{ \beta : \text{$p$ is a $\beta$-plurality
point for $V$}\}$. Given a voter set $V \in \mathbb{R}^2$, we provide an
algorithm that runs in $O(n \log n)$ time and computes a point $p$ such that
$\beta(p, V) \geq \beta^*_2$. Moreover, for $d\geq 2$ we can compute a point
$p$ with $\beta(p,V) \geq 1/\sqrt{d}$ in $O(n)$ time.
  * Define $\beta(V) := \sup \{ \beta : \text{$V$ admits a $\beta$-plurality
point}\}$. We present an algorithm that, given a voter set $V$ in
$\mathbb{R}^d$, computes an $(1-\varepsilon)\cdot \beta(V)$ plurality point in
time $O(\frac{n^2}{\varepsilon^{3d-2}} \cdot \log \frac{n}{\varepsilon^{d-1}}
\cdot \log^2 \frac {1}{\varepsilon})$.
