1 Introduction
Cooperation is not without conflict. This tension results from the negotiation process on how to share the collective earnings. In some cases, cooperation is enforced; that is, economic gains are only achieved when all of us cooperate. The construction and maintenance of public goods generally require the cooperation of many economic agents. These situations represent instances where cooperation is not a choice but a necessity, as the achievement of societal goals relies on it. In other cases, cooperation may be voluntary and agents increase their benefits simply by cooperating. For instance, this is the case when several agents jointly invest their funds, getting a higher yield the larger is the amount invested. In such instances, cooperation becomes a mutually beneficial strategy, where individuals recognize that their collective efforts yield greater rewards, aligning their individual interests with the broader societal benefit.
In this study, we examine a society represented as a coalition of n individuals engaged in a cooperative problem. To model this scenario, we employ a cooperative game with transferable utility and its characteristic function, which delineates the gains of the entire society and the potential gains of subcoalitions of individuals. The central issue is how to distribute the overall gain among the n agents.
In some societies, social equity is considered a desirable goal and a social value in itself. At this point, individual interests, where maximizing personal earnings is paramount, may enter into conflict with the societal objective of promoting an equitable distribution. How to reconcile these two contrasting positions?
Consider, for example, an egalitarian and equitable extreme distribution, such as the equal division of gains. From an egalitarian perspective, there is no better distribution. However, from the cooperation standpoint, this distribution may conflict with the individual or coalitional interests that would require a distribution within the core of the cooperative game associated.
At this point, let us remark that each individual may have their own interpretation of the egalitarian concept. Within the context of cooperative game theory, various solutions related to egalitarianism have already been proposed: the equal division core (Selten
1972), the constrained egalitarian solution (Dutta and Ray
1989), the strong constrained egalitarian solution (Dutta and Ray
1991), the stable egalitarian set (Arin and Iñarra (
2001,
2002)), and the split-off set (Branzei et al.
2006).
A standard way to compare distributions that allocate the same total amount (with same efficiency) among agents, and assess their quality concerning the equality of their payoffs, is to use the Lorenz criterion (Lorenz
1905). For our purposes, one allocation of gains Lorenz dominates another one when, upon arranging the payoffs to agents from smallest to largest, the cumulative sums in the first allocation exceed those in the second. The Lorenz criterion, or Lorenz dominance, has been used in various economic contexts to provide some justification for certain distributions over others. As a result, there is a vast body of literature on the application of Lorenz dominance: in bankruptcy problems (see Miras-Calvo et al.
2023; Thomson
2019,
2012; Bosmans and Lauwers
2011), in taxation analysis (see Ju and Moreno Ternero
2008; Moreno-Ternero and Villar
2006; Mitra and Ok
1997; Eichorn et al.
1984; Jakobsson
1976), and in general cooperative games (see Sànchez-Soriano et al.
2010; Arin and Feltkamp
2002). Furthermore, experiments have been carried out with the result that agents prefer allocations where payoffs between agents do no differ too much, reinforcing from a positive point of view egalitarian criteria (see Traub et al.
2003). In this line, we can quote Moulin (
1988), page 24:
Experimental evidence strongly supports egalitarianism when utilities are perceived as representing objective needs; seeYaari and Bar-Hillel (
1984),
where utilities are measured by the amount of certain vitamins metabolized by the agents. When utilities represent different tastes, the experimental outcome is much less easy to read.
The Lorenz domination has been extended and used to compare vectors with different efficiency. In Moulin (
1988, p. 48), Arin and Feltkamp
1 (2002) or Marshall
2 et al. (
2011), an allocation of gains Lorenz dominates another one with smaller efficiency when, upon arranging the payoffs to agents from smallest to largest, the cumulative sums in the first allocation exceed those in the second. This way, Lorenz domination can be interpreted as a social welfare ordering that compares two allocation vectors with different efficiency where the more preferred vector correspond to a society with a larger welfare, e.g. see Endriss et al. (
2006).
Within the context of cooperatives games, Sprumont (
1990) introduces Population Monotonic Allocation Schemes (PMAS). An allocation scheme proposes an allocation for each subcoalition of agents. These allocations serve to justify the final allocation for the whole society showing that the more agents join a coalition (and thus the population grows) the larger can be the payoffs to agents. As a consequence of the definition of a PMAS, it is evident that not only individual payoffs, but social welfare of any subgroup of agents increases, leading to an allocation in the core of the associated cooperative game. However, not for all games with a non-empty core we can describe such an allocation scheme. For instance, as Sprumont remarks, an assignment game with at least two sellers and two buyers, where each buyer-seller pair derives a positive gain from trade, lacks a PMAS.
In this paper we propose a new cooperative TU-game concept, namely Population Lorenz-Monotonic Allocation Scheme (PLMAS). This concept encompasses the concept of PMAS and proposes an allocation scheme such that if new agents join a coalition the initial group of agents becomes socially better (in the Lorenz sense). As we have commented, societal interests may enter in conflict with individual or coalitional interests. However, a non-negligible consequence of adopting a PLMAS is that the final allocation proposed for the whole society turns out to be an allocation in the core of the game. This way PLMAS could be interpreted as a method to select a Pareto efficient allocation in the core of the game.
The remainder of the paper is organized as follows. In Sect.
2, we define the main concepts of cooperative games. In Sect.
3, we introduce the concept of PLMAS and Lorenz-monotonic core (the set of all the PLMAS). We show that this set can be discrete, and thus a non-convex set (see Example
1), which makes it different from the case of PMAS. In Proposition
1, we point out that a PMAS can be reinterpreted as a PLMAS, and thus the individual incentive point of view makes the allocation compatible with the social point of view. However, the converse is not true. In fact, in Example
4, we exhibit a four-person game with PLMAS, but without PMAS, demonstrating that there are cases where the social point of view is appropriate to justify allocations. Indeed, in Theorem
1, we introduce a sufficient condition for having PLMAS that includes games with no PMAS. In Theorem
2, we discuss the case of glove games, a particular case of assignment games, and show that even though they do not have PMAS, any core allocation can be supported by a PLMAS.
In Sect.
4, we discuss concepts related to PLMAS. We state that convex games are PLMAS-extendable (Theorem
3) and are the unique class of games that are PLMAS-exact (Theorem
4). In Sect.
5 we conclude.
2 Notations
A cooperative game with transferable utility (a game) is a pair \(\left( N,v\right) \) (in short v), where \(N=\left\{ 1,2,\ldots ,n\right\} \) is a finite set of players and \(v:2^{N}\rightarrow \mathbb {R}\) is the characteristic function with \(v(\varnothing )=0\). A subset S of N, \(S\in 2^{N}\), is a coalition of players,|S| denotes its cardinality, and v(S) is interpreted as the worth of coalition S. We denote by \(P(N)=\left\{ S\subseteq N\mid S\ne \varnothing \right\} \) the set of nonempty coalitions of N. Given \(S\in P(N)\), we denote by \(\left( S,v_{S}\right) \) the subgame of \(\left( N,v\right) \) related to coalition S (i.e. \(v_{S}\left( R\right) =v\left( R\right) \) for all \(R\subseteq S)\).
A payoff allocation is a vector \(z=\left( z_{i}\right) _{i\in N}\in \mathbb {R}^{N}\), where \(z_{i}\) is the payoff to player i, and for \(S\in P(N)\) we write \(z\left( S\right) =\sum \limits _{i\in S}z_{i}\), \(z(\varnothing )=0\) and \(\left. z\right| _{S}=\left( z_i\right) _{i\in S}\). The core of a game (N, v) is the set \(C\left( N,v\right) =\left\{ z\in \mathbb {R}^{N}\mid z(N)=v(N),\ z\left( S\right) \ge v\left( S\right) \forall S\in P(N)\right\} \).
A game (
N,
v) is
balanced if it has a nonempty core, it is
totally balanced if the subgame
\(\left( S,v_{S}\right) \) is balanced for all
\(S\in P(N)\), and it is
convex (Shapley
1971) if
\(v(S)+v(T)\le v(S\cup T)+v(S\cap T)\) for all
\(S,T\subseteq N\).
A
Population Monotonic Allocation Scheme (PMAS) of a game (
N,
v) (Sprumont
1990) is a vector
\(x=\left( x^{S}\right) _{S\in P(N)}\), where
\(x^{S}=\left( x^{S}_{i}\right) _{i \in S} \in \mathbb {R}^{S}\), that satisfies the following conditions:
(i)
Efficiency in each coalition: \(\sum \limits _{i\in S} x_{i}^{S}=v(S)\) for all \(S\in P(N)\).
(ii)
Monotonicity: \(x^{S}\le \left. x^{T}\right| _{S}\) (\(\ x_{i}^{S}\le x_{i}^{T} \hbox { for all } i\in S\)) for all \(S, T\,\in P(N),\ S\subseteq T\).
We also use the notation
\(x=\left( x_{i}^{S}\right) _{S \in P(N),\ i\in S}\) to describe a PMAS. The above definition implies that a PMAS
x selects a core allocation
\(x^{S}=\left( x_{i}^{S}\right) _{i\in S} \in C\left( S, v_{S}\right) \) for every subgame
\(\left( S, v_{S}\right) \) in such a way that the payoff to any player cannot decrease when the coalition to which he/she belongs becomes larger. Thus every game having a PMAS is totally balanced. Sprumont shows that all convex games have a PMAS.
The
monotonic core of a game
\(v\in G^{N}\), denoted by
MC(
N,
v), is the set of all its PMAS (Moulin
1990). This set always coincides with the core of a certain game associated to the initial game (Getán et al.
2009).
PMAS-extendability
A balanced game (
N,
v) is
core-extendable (Kikuta and Shapley
1986) when for every
\(S\in P(N)\) and
\(y\in C\left( S, v_{S}\right) \) there exists
\(z\in C(N,v)\) such that
\(z_{i}=y_{i}\) for all
\(i\in S\). Each convex game is core-extendable, but the converse is not necessarily true (Sharkey
1982; Kikuta and Shapley
1986).
A game (
N,
v) is
PMAS-extendable (Getán et al.
2014) if for every
\(S\in P(N)\) and for every
\(y=\left( y^{R} \right) _{R \in P(S)} \in MC\left( S, v_{S}\right) \) there exists
\(x=\left( x^{R} \right) _{R \in P(N)}\in MC(N,v)\) such that
\(y^{R}=x^{R}\) for all
\(R \in P(S)\). Notice that every PMAS-extendable game has at least one PMAS. Moreover, we know that a game (
N,
v) is convex if and only if it is PMAS-extendable (Getán et al. (
2014)). In particular, every PMAS-extendable game is core-extendable.
PMAS-exactness
A game (
N,
v) is called
exact (Schmeidler
1972) if for every
\(S\in P(N)\) there exists
\(z\in C(N,v)\) with
\(z(S)=v(S)\). It is evident that all exact games are totally balanced. Additionally, it is easy to observe that every convex game is exact. However, in general, the converse statement does not hold.
A game (
N,
v) is
PMAS-exact (Getán et al.
2014) when for every
\(S\in P(N)\) there exists
\(x=(x^{R})_{R \in P(N)} \in MC(N,v)\) such that
\(x^{N}\left( S \right) = v\left( S \right) \). It is important to note that every PMAS-exact game is also exact, and any subgame of a PMAS-exact game is also PMAS-exact. Moreover, it is known that a game (
N,
v) is convex if and only if it is PMAS-exact (Getán et al.
2014).
Lorenz domination
A standard of fairness is the one provided by the
Lorenz domination criterion (Lorenz
1905). To define it, consider a fixed population of individuals denoted as
\(N=\left\{ 1,2,\dots ,n\right\} \). Given a vector
\(x=(x_1,\cdots ,x_n)\in \mathbb {R}^{N}\), we can interpret
\(x_i\) as the income of individual
\(i\in N\) and we can order the individuals from the poorest to the richest to obtain
\(x_{(1)}\le \ldots \le x_{(n)}\). Now, given
\(x=(x_{1},\ldots ,x_{n})\in \mathbb {R}^{N}\) and
\(y=(y_{1},\ldots ,y_{n})\in \mathbb {R}^{N}\), we say that
y weakly Lorenz dominates x, and we denote it by
\(x\preccurlyeq _{\mathcal {L}} y\) or by
\(y\succcurlyeq _{\mathcal {L}} x\), if:
$$\begin{aligned} \begin{array}{rcl} x_{(1)} &{} \le &{} y_{(1)}, \\ x_{(1)}+x_{(2)} &{} \le &{} y_{(1)}+y_{(2)}, \\ \cdots &{} \cdots &{} \cdots \\ x_{(1)}+x_{(2)}+ \cdots +x_{(n)} &{} \le &{} y_{(1)}+y_{(2)}+\cdots + y_{(n)}. \\ \end{array} \end{aligned}$$
An equivalent way to express the Lorenz domination criterion is by means of a function
\(\varphi :\mathbb {R}^{N}{\rightarrow }\mathbb {R}^{n}\) (
\(n=|N|\)), defined as follows. Let
\(x\in \mathbb {R}^{N}\) and
\(1\le k\le n\), then we define the function
\(\varphi _{k}(x)\) as
$$ \varphi _{k}(x)=\min \left\{ x(S)| S\subseteq N \hbox { and }|S|=k \right\} =x_{(1)}+\cdots +x_{(k)}. $$
For
\(x,y\in \mathbb {R}^{N}\), we have that
\(x\preccurlyeq _{\mathcal {L}} y\) if
\(\varphi _{k}(x)\le \varphi _{k}(y)\) for all
\(k=1,\ldots ,n\). It is said that
y Lorenz dominates x, denoted by
\(x\prec _{\mathcal {L}} y\), if
\(x\preccurlyeq _{\mathcal {L}} y\) and
\(\varphi (x)\ne \varphi (y)\) (i.e.
\(\varphi _{k}(x)\ne \varphi _{k}(y)\) for some
\(k=1,\ldots ,n\)).
The relation
\(\preccurlyeq _{\mathcal {L}}\) is a preorder on
\(\mathbb {R}^{N}\) but not a partial order, as it satisfies the following properties:
(i)
Reflexivity: \(x\preccurlyeq _{\mathcal {L}}x \) for all \(x \in \mathbb {R}^{N}\).
(ii)
Transitivity: For \(x,y,z \in \mathbb {R}^{N}\) with \(x\preccurlyeq _{\mathcal {L}}y \) and \(y\preccurlyeq _{\mathcal {L}}z\) we have \(x\preccurlyeq _{\mathcal {L}}z\).
(iii)
Non anti symmetry
3: For
\(x,y \in \mathbb {R}^{N}\) we have
$$\begin{array}{l} x\preccurlyeq _{\mathcal {L}}y\hbox { and } y\preccurlyeq _{\mathcal {L}}x \\ \Longleftrightarrow x_{(k)}=y_{(k)}\hbox { for all } k=1,\ldots ,n \\ \Longleftrightarrow x=y\Pi \hbox { for some permutation matrix } \Pi . \end{array}$$
However, the relation
\(\preccurlyeq _{\mathcal {L}}\) is a partial order on the commutative monoid
\(\mathcal {D}=\left\{ x=(x_1,\ldots ,x_n)\in \mathbb {R}^{N}\mid x_1\le \ldots \le x_n \right\} \). Moreover,
\(\preccurlyeq _{\mathcal {L}}\) is compatible with the sum "+" of
\(\mathcal {D}\):
$$ x\preccurlyeq _{\mathcal {L}}y\Longrightarrow x+z\preccurlyeq _{\mathcal {L}}y+z \hbox { for all }x,y,z\in \mathcal {D}. $$
Notice that for
\(x,y\in \mathbb {R}^{N}\) we have the implications:
$$\begin{aligned} x\le y \quad \Rightarrow \quad x\preccurlyeq _{\mathcal {L}}y \quad \Rightarrow \quad x(N)\le y(N) \quad \end{aligned}$$
(1)
where
\(x\le y\) means
\(x_i\le y_i\) for all
\(i\in N\). Moreover, notice that the egalitarian allocation
\(\alpha :=\left( \frac{\nu }{n},\dots ,\frac{\nu }{n}\right) \in \mathbb {R}^{N}\), where
\(\nu \in \mathbb {R}\), satisfies
$$\begin{aligned} \alpha \succcurlyeq _{\mathcal {L}}x \quad {\text { for all }} x\in \mathbb {R}^{N} {\text { with }} x(N)=\nu ; \end{aligned}$$
(2)
in others words, the egalitarian allocation
\(\alpha =\left( \frac{\nu }{n},\dots ,\frac{\nu }{n}\right) \in \mathbb {R}^{N}\) weakly Lorenz dominates any efficient allocation
\(x\in \mathbb {R}^{N}\) with
\(x(N)=\nu \).
3 Population Lorenz-monotonic allocation schemes
In this section, we use the Lorenz domination criterion to introduce a new concept for a cooperative game. This concept aims to mimic and generalize the notion of PMAS.
Notice that, by (
1), the Lorenz-monotonicity condition relaxes the monotonicity condition of Sprumont. After providing the definition of PLMAS, we present several results regarding PLMAS for general cooperative games.
The set of PLMAS of the game (
N,
v) is denoted by
$$\mathcal {L}MC(N,v)=\{x \mid x \hbox { is a PLMAS of } (N,v) \},$$
and its projection to
\(\mathbb {R}^{N}\) is denoted by
$$ \mathcal {L}MC^N(N,v)=\left\{ x^{N}\mid x=\left( x^{S}\right) _{S\in P(N)}\in \mathcal {L}MC(N,v) \right\} . $$
Notice that the set
\(\mathcal {L}MC(N,v)\) is compact, but is not convex in general, as illustrated in the following example where the
\(\mathcal {L}MC(N,v)\) is a discrete set. This is a significant difference between PLMAS and PMAS, which makes it difficult to state a general existence theorem for PLMAS.
We collect some basic facts about PLMAS in the following proposition. Proofs are left to the reader.
Part (a) in Proposition
1 states that all cooperative games having a PLMAS are totally balanced. However, it is not true that all totally balanced games have a PLMAS, as shown in the following example. Since every three-player totally balanced game has a PMAS (Sprumont
1990), we need to consider games with at least four players.
Note that for the game (
N,
v) in Example
2 every game
\((N,v')\) such that
\(v'(S)=v(S)\) for all
\(S\subseteq N\),
\(S\ne N\), and
\(v'(N)\ge v(N)\) lacks a PMAS, as
\(v(123)+v(134)<v(12)+v(13)+v(34)\) (Norde and Reijnierse
2002). However, if we take
\(v'(N)\ge \frac{4}{3}a\) it can be shown that
\((N,v')\) has a PLMAS. In fact, we can state a more general result for totally balanced four-player games.
We remark that the previous proposition is not valid in the case of games with five or more players as the following example shows.
Now we introduce a class of games having PLMAS, but not PMAS in general as Example
4 illustrates.
We can interpret these games as follows. Consider a game (
N,
v) and a coalition of players
\(T\subseteq N\), where one specific player, denoted as
\(i_T\), assumes the role of the leader within the group. Player
\(i_T\) contributes a unique set of assets, including know-how, capital, networking contacts, and prestige, while also organizing the collaborative efforts of the remaining members. The remaining group members contribute symmetrically through their work efforts. To establish a structured framework, we impose the following conditions:
(i)
The equal distribution of the total output should be a core allocation of the game.
(ii)
The productivity of each worker diminishes as the workforce size decreases and the leader stays in the coalition, i.e. \(\frac{v(T)}{t-1}\ge \frac{v(S)}{s-1}\). On the other hand, if some group of workers \(S\subseteq T\) opt to leave the group, the per capita value they could generate by working elsewhere as a collective, \(\frac{v(S)}{s}\), is lower than the productivity they achieve under the leadership of \(i_T\).
In general, a leadership game does not have a PMAS, as the following example illustrates.
In the next theorem we demonstrate the existence of PLMAS for every glove game (Shapley
1959). In fact, we show that every core allocation in a glove game can be reached by a PLMAS.
Proof
We write
\(y=\left( \left. y\right| _{S\cap L}; \left. y\right| _{S\cap R}\right) \) for all
\(S\in P(N)\) and
\(y=\left( y_{i}\right) _{i \in S} \in \mathbb {R}^{S}\). Without loss of generality, let us suppose that
\(|L|\le |R|\) and let
\(z\in C(N,v)\). We next prove that there exists
\(x=\left( x^S\right) _{S\in P(N)}\in \mathcal {L}MC(N,v)\) such that
\(x^N=z\). To this aim, for every
\(S\in P(N)\) we denote
\(l_S=|S\cap L|\) and
\( r_S=|S\cap R|\). Then, define
\(x^S\) as follows:
$$ x^S= \left\{ \begin{array}{ll} z &{}\hbox {if } S=N, \\ (0,\overset{(s)}{\dots \dots },0) &{}\hbox {if } S\subseteq L \hbox { or } S\subseteq R, \\ (1,\overset{(l_s)}{\dots \dots },1;0,\overset{(r_s)}{\dots \dots },0) &{}\hbox {if } S \ne N \hbox { and } 1 \le l_S \le r_S, \\ (0,\overset{(l_s)}{\dots \dots },0;1,\overset{(r_s)}{\dots \dots },1) &{}\hbox {if } 1\le r_S < l_S. \\ \end{array} \right. $$
Notice that
\(x^N=z\) and
\(x^S\in C(S,v_S)\) for all
\(S\in P(N)\), Thus,
\(x=\left( x^S \right) _{S\in P(N)}\) satisfies efficiency in each coalition.
To prove that x is a PLMAS of (N, v), it remains only to check the Lorenz monotonocity of x. Let \(S,T\in P(N)\) be two coalitions such that \(S\subseteq T, S\ne T\). We claim that \(x^S\preccurlyeq _{\mathcal {L}} \left. x^{T}\right| _{S}\). Indeed, to prove it, we need to differentiate between several cases based on the previous definition of \(x^S\):
Case 1. If \(S\subseteq L\) or \(S\subseteq R\), then it is straightforward since \(x^S=(0,\overset{(s)}{\dots \dots },0)\).
Case 2. If \(T=N\) and \(l=|L|<r=|R|\), then \(z=(1,\overset{(l)}{\dots \dots },1;0,\overset{(r)}{\dots \dots },0)\) and \(x^S\preccurlyeq _{\mathcal {L}} \left. z\right| _{S}\) since the number of components equal to 1 in \(x^S\) is at most the number of components equal to 1 in \(\left. z\right| _{S}\), which is equal to \(l_s\).
Case 3. If \(T=N\) and \(l=|L|=r=|R|\), then \(z=(\lambda ,\overset{(l)}{\dots \dots },\lambda ; 1-\lambda ,\overset{(r)}{\dots \dots },1-\lambda )\) for some \(0\le \lambda \le 1\) and we must see that \(x^S\preccurlyeq _{\mathcal {L}} \left. z\right| _{S}\). Suppose that \(1 \le l_S \le r_S\) (the other case \(l_S>r_S\ge 1\) is similar and it is left to the reader), and thus \(x^S=(1,\overset{(l_s)}{\dots \dots },1;0,\overset{(r_s)}{\dots \dots },0)\). For \(k=1,...,r_S\), we have \(\varphi _{k}\left( x^S\right) =0\le \varphi _{k}\left( \left. z\right| _{S}\right) \). For \(k=r_S+1,...,r_S+l_S=s\), we have \(\varphi _{k}\left( x^S\right) =k-r_S\le \varphi _{k}\left( \left. z\right| _{S}\right) \) since \(\varphi _{k}\left( \left. z\right| _{S}\right) = \left( k-r_S\right) \lambda + r_S(1-\lambda )\) when \(\lambda \ge 1/2\), and \(\varphi _{k}\left( \left. z\right| _{S}\right) = l_S\lambda + \left( k-l_S\right) (1-\lambda )\) when \(\lambda \le 1/2\).
Case 4. If \(T\ne N\), \(S\cap L\ne \emptyset \) and \(S\cap R\ne \emptyset \), then \(x^S\preccurlyeq _{\mathcal {L}} \left. x^T\right| _{S}\), as the number of components equal to 1 in \(x^S\) is at most the number of components equal to 1 in \(\left. x^T\right| _{S}\) since \(S\subseteq T\). \(\square \)
Next we show the existence of PLMAS for every assignment game (Shapley and Shubik
1971) with at most five players.
The player set is
\(N=M\cup M'\) where
\(M,M'\) are two disjoints finite sets with respective cardinality
\(m,m'\ge 1\), named set of buyers and set of sellers respectively; so
\(n=m+m'\). Given a matrix
\(A=(a_{ij})_{i\in M,j\in M'}\in \textrm{M}_{m\times m'}(\mathbb {R}_{+})\), where each entry of the matrix
\(a_{ij}\ge 0\), we can associate a cooperative game
\((N,w_A)\), named
assignment game defined by the matrix
A, defining the worth of any coalition
\(S\cup S'\subseteq N\), with
\(S\subseteq M\) and
\(S'\subseteq M'\), by:
$$ w_A(S\cup S')=\max \left\{ \sum _{(i,j)\in \mu } a_{ij} \mid \mu \in \mathcal {M}(S,S') \right\} , $$
where
\(\mathcal {M}(S,S')\) is the set of all matchings
\(\mu \) between
S and
\(S'\); i.e.
\(\mu \subseteq S\times S'\) is a bijection from
\(S_0\subseteq S\) to
\(S_0'\subseteq S'\) such that
\(|S_0|=|S_0'|=\min \{ s,s'\}\). A matching
\(\mu \in \mathcal {M}(M,M')\) is
optimal w.r.t. the matrix
A when it satisfies
$$ \sum _{(i,j)\in \mu } a_{ij}\ge \sum _{(i,j)\in \mu '} a_{ij} {\text { for all }}\mu '\in \mathcal {M}(M,M'). $$
We denote by
\(\mathcal {M}_{A}^{*}\) the set of optimal matchings for the grand coalition. So, we have
\(\sum _{(i,j)\in \mu } a_{ij}=w_{A}(N)\) for all
\(\mu \in \mathcal {M}_{A}^{*}\).
Shapley and Shubik (
1971) prove that the core of the assignment game
\((N,w_{A})\) is nonempty and it is enough to impose coalitional rationality for one-player coalitions and mixed-pair coalitions:
$$\begin{aligned} C(N,w_{A})= & {} \left\{ (u;v)\in \mathbb {R}_{+}^{M}\times \mathbb {R}_{+}^{M'}\left| \begin{array}{l} \sum _{i\in M}u_i+\sum _{j\in M'}v_j =w_A(N),\\ u_i+ v_j \ge a_{ij}\,\forall i\in M\,\forall j\in M' \end{array}\right. \right\} . \end{aligned}$$
Therefore if
\((u;v) \in C(N,w_{A})\), then for every optimal matching
\(\mu \in \mathcal {M}_{A}^{*}\) we have:
$$ \begin{array}{l} u_i+ v_j= a_{ij} \hbox { if } (i,j)\in \mu , \\ u_{i}=0 \hbox { if } i\in M \hbox { is not mached by } \mu , \\ v_{j}= 0 \hbox { if } j\in M' \hbox { is not mached by } \mu . \end{array} $$
There exists a
sellers-optimal core allocation,
\((\underline{u};\overline{v})=\left( \underline{u}^A;\overline{v}^A\right) \in C(N,w_{A})\), where each seller attains his maximum core payoff. For every seller
\(j\in M'\) is
$$ \overline{v}_j:=w_A(N)-w_A(N{\setminus }\{j\}), $$
and given an optimal matching
\(\mu \in \mathcal {M}_{A}^{*}\) for every buyer
\(i\in M\) is
$$ \underline{u}_{i}:= \left\{ \begin{array}{ll} a_{i\mu (i)}+ w_{A}(N\setminus \{\mu (i)\} )-w_{A}(N) &{}\hbox {if } i\hbox { is matched by } \mu ; \\ 0 &{}\hbox {if } i\hbox { is not matched by } \mu . \end{array} \right. $$
A survey on assignment games is given in Núñez and Rafels (
2015).
We would like to remark that in general (\(n\ge 6\)), assignment games could lack PLMAS, as the following example illustrates.
Now we show the existence of PLMAS in another interesting model. Shapley and Shubik (
1967) introduces a model of a production economy involving a landowner and
\(m\ge 1\) peasants. The profit that arises if
p peasants work for the landowner is denoted by
f(
p), where
\(f:\{0,1,2,\ldots ,m\}\rightarrow \mathbb {R}\) is a production function such that:
-
\(f(0)=0\),
-
if \(0\le p_1<p_2\le m\), then \(f(p_1)\le f(p_2)\) (increasing function),
-
if \(0\le p_1<p_2<p_3\le m\), then \(f(p_2)-f(p_1)\le f(p_3)-f(p_2)\) (concavity).
Then, the associated cooperative game between the landowner (player 0) and the
m peasants is defined as follows: for any coalition
\(\varnothing \ne S\subseteq N:=\{0,1,2,\ldots ,m\}\),
$$\begin{aligned} v(S):= \left\{ \begin{array}{ll} f(|S|-1) &{} \hbox {if }0\in S \\ 0 &{} \hbox {otherwise.} \end{array} \right. \end{aligned}$$
(3)
In this model, the marginal productivity of any peasant when working for the landowner is equal to
\(\Delta := f(m) - f(m-1)\ge 0\). The allocation
\(z\in \mathbb {R}^N\) such that
\(z_0:= f(m) - m\Delta \) and
\(z_i:= \Delta \) for all
\(i=1,\ldots ,m\) is a core allocation since
f is a concave function. In next proposition we prove this core allocation
z is supported by a PLMAS.
We finish this section with another interesting example. Moretti and Norde (
2021) analyze
weighted multi-glove games. They generalize the model of glove markets, a two-sector production economy, by introducing several sectors, all of which are necessary to extract some positive profit. Each member of a sector has a certain number of units of an input. The production process requires using one unit of input from each sector to obtain one unit of output.
Formally, given a player set
N and a partition of
N into
k sectors,
\(P=\{ P_1, P_2, \ldots , P_k\}\), each member
i is endowed with
\(w_i\) units of input. The vector
\(w \in \mathbb {N}^N\) is the vector of inputs. Then, the worth of a coalition
\(S \subseteq N\),
\(S\ne \varnothing \) (the amount of output), is given by
$$ v^{P,w}(S)=\min \left\{ \sum _{i\in S\cap P_r} w_i: r=1,\ldots ,k\right\} . $$
The authors demonstrate that the corresponding game is totally balanced and provide a characterization of when the game admits PMAS. However, in Example 3.6 of their paper (page 728), they present an example of a five-player game with a core element that cannot be extended by a PMAS. The specific game is as follows.
4 PLMAS-extendability and PLMAS-exactness
In this section, we provide a characterization of the convexity of a game in terms of PLMAS. To do this, we introduce two new concepts related to the Lorenz-monotonic core:
PLMAS-extendability and
PLMAS-exactness. These notions are inspired by the concepts of PMAS-extendability and PMAS-exactness introduced by Getán et al. (
2014).
It is worth noting that every PLMAS-extendable game possesses at least one PLMAS, as every game contains subgames with PLMAS. For example, one can consider the restriction of the game to individual coalitions.
The following theorem proves that PLMAS-extendability is implied by the convexity of the game.
Since a game is PMAS-extendable if and only if it is convex (Getán et al.
2014) we obtain the following result.
It is generally not true that every PLMAS-extendable game is convex.
Next, we approach the notion of convexity from a different perspective by introducing the concept of PLMAS-exactness. In simple terms, PLMAS-exactness implies that the worth of any coalition of players is achieved in at least one PLMAS of the entire game.
It is evident that a game which is PLMAS-exact is also exact. Furthermore, it can be easily demonstrated that any subgame of a PLMAS-exact game is also PLMAS-exact. Next theorem establishes that PLMAS-exactness is a characterization of the convexity of the game.
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