Corporate social responsibility: the organizational view

Designing strategies for corporate social responsibility (CSR)-practice nowadays has become essential for organizations. Notwithstanding, how organizations appear internally in a socially responsible context toward their employees has been insufficiently investigated. This study aims at ascertaining how Internal CSR can be conceptualized as well as how it affects employees’ commitment. To do so, the manifestations of Internal CSR are discussed based on social identity theory and further literature, while the developed research model is checked for suitability through a survey generating 2081 employee responses from an international pharmaceutical company. As one result, it can be stated that the factors proposed to constitute Internal CSR are confirmed. Further, the findings entail the following conclusions: Internal CSR has a notable influence on employees’ Affective Organizational Commitment whilst relatively moderate impacting Normative Organizational Commitment. Additionally, Affective Organizational Commitment adopts a mediating function regarding Normative Organizational Commitment.     

Estimating hybrid frequency moments of data streams

We consider the problem of estimating hybrid frequency moments of two dimensional data streams. In this model, data is viewed to be organized in a matrix form (A _i,j )_1≤i,j,≤n . The entries A _i,j are updated coordinate-wise, in arbitrary order and possibly multiple times. The updates include both increments and decrements to the current value of A _i,j . The hybrid frequency moment F _p,q (A) is defined as \(\sum_{j=1}^{n}(\sum_{i=1}^{n}{A_{i,j}}^{p})^{q}\) and is a generalization of the frequency moment of one-dimensional data streams.We present the first \(\tilde{O}(1)\) space algorithm for the problem of estimating F _p,q for p∈[0,2] and q∈[0,1] to within an approximation factor of 1±ε. The \(\tilde{O}\) notation hides poly-logarithmic factors in the size of the stream m, the matrix size n and polynomial factors of ε ^?1. We also present the first \(\tilde{O}(n^{1-1/q})\) space algorithm for estimating F _p,q for p∈[0,2] and q∈(1,2].     

Practical implications of the resource-based view

Managers use many decision making tools when developing a firm’s strategic direction. Ideally, such tools yield a good solution for an acceptable amount of application effort. This paper presents the results of an experimental research project that compares the effectiveness of a theory-based strategic decision making tool, theVRIO-framework, with two alternative decision making heuristics for predicting the stock-market performance of different companies. First, we assess how the predictions of theVRIO-framework contrast with decisions based on “gut feeling” using the forecasts derived from a recognition-based decision making tool, theRecognition Heuristic. Secondly, theVRIO-framework’spredictive power is compared to predictions derived fromAnalyst Ratings. Our results suggest that the predictions of theVRIO-framework are superior to those of theRecognition Heuristic and theAnalyst Ratings, supporting the practical usefulness of resource-based theory. We conclude that resource analysis is important to strategic decision making and discuss the implications of our findings for future research and management practice.     

Approximating capacitated tree-routings in networks

Let G=(V,E) be a connected graph such that each edge e∈E is weighted by a nonnegative real w(e). Let s be a vertex designated as a sink, M?V be a set of terminals with a demand function q:M→R ⁺, κ>0 be a routing capacity, and λ≥1 be an integer edge capacity. The capacitated tree-routing problem (CTR) asks to find a partition ?={Z ₁,Z ₂,…,Z _? } of M and a set \({\mathcal{T}}=\{T_{1},T_{2},\ldots,T_{\ell}\}\) of trees of G such that each T _i contains Z _i ∪{s} and satisfies \(\sum_{v\in Z_{i}}q(v)\leq \kappa\). A single copy of an edge e∈E can be shared by at most λ trees in \({\mathcal{T}}\); any integer number of copies of e are allowed to be installed, where the cost of installing a copy of e is w(e). The objective is to find a solution \(({\mathcal{M}},{\mathcal{T}})\) that minimizes the total installing cost. In this paper, we propose a (2+ρ _ST )-approximation algorithm to CTR, where ρ _ST is any approximation ratio achievable for the Steiner tree problem.     

Religion,governance and performance: evidence from Islamic and conventional stock exchanges

Based on a dataset of 31 conventional and Islamic stock exchanges we compare financial performance across these two groups for 2007–2011 period. Our results suggest that CEs and IEs are differently exposed to institutional constraints and have different drivers of profitability. Islamic stock exchanges’ performances are essentially driven by traditional listing and trading services and are affected by institutional factors such as the degree of foreign trading openness of their economies and measures of society development. Furthermore, they ensure greater stability during crisis, although Shari’ah compliant investments don’t affect their revenue generation. Conventional stock exchanges have higher trading intensity, higher level of revenues’ diversification and high capital investments, as they operate with different business models. Our results could have relevant business and strategic implications for further convergence between the two groups. Moreover our analysis could be significant for firms wishing to list their shares into Shari’ah Compliant Stock Exchanges or into Conventional ones and traders choosing the most convenient trading venue.     

The <Emphasis Type="Italic">w</Emphasis>-centroids and least <Emphasis Type="Italic">w</Emphasis>-central subtrees in weighted trees

Let T be a weighted tree with a positive number w(v) associated with each vertex v. A subtree S is a w-central subtree of the weighted tree T if it has the minimum eccentricity \(e_L(S)\) in median graph \(G_{LW}\). A w-central subtree with the minimum vertex weight is called a least w-central subtree of the weighted tree T. In this paper we show that each least w-central subtree of a weighted tree either contains a vertex of the w-centroid or is adjacent to a vertex of the w-centroid. Also, we show that any two least w-central subtrees of a weighted tree either have a nonempty intersection or are adjacent.     

Distance domination in graphs with given minimum and maximum degree

For an integer \(k \ge 1\), a distance k-dominating set of a connected graph G is a set S of vertices of G such that every vertex of V(G) is at distance at most k from some vertex of S. The distance k-domination number \(\gamma _k(G)\) of G is the minimum cardinality of a distance k-dominating set of G. In this paper, we establish an upper bound on the distance k-domination number of a graph in terms of its order, minimum degree and maximum degree. We prove that for \(k \ge 2\), if G is a connected graph with minimum degree \(\delta \ge 2\) and maximum degree \(\Delta \) and of order \(n \ge \Delta + k - 1\), then \(\gamma _k(G) \le \frac{n + \delta - \Delta }{\delta + k - 1}\). This result improves existing known results.     

Covering directed graphs by in-trees

Given a directed graph D=(V,A) with a set of d specified vertices S={s ₁,…,s _d }?V and a function f : S→? where ? denotes the set of positive integers, we consider the problem which asks whether there exist ∑ _i=1 ^d f(s _i ) in-trees denoted by \(T_{i,1},T_{i,2},\ldots,T_{i,f(s_{i})}\) for every i=1,…,d such that \(T_{i,1},\ldots,T_{i,f(s_{i})}\) are rooted at s _i , each T _i,j spans vertices from which s _i is reachable and the union of all arc sets of T _i,j for i=1,…,d and j=1,…,f(s _i ) covers A. In this paper, we prove that such set of in-trees covering A can be found by using an algorithm for the weighted matroid intersection problem in time bounded by a polynomial in ∑ _i=1 ^d f(s _i ) and the size of D. Furthermore, for the case where D is acyclic, we present another characterization of the existence of in-trees covering A, and then we prove that in-trees covering A can be computed more efficiently than the general case by finding maximum matchings in a series of bipartite graphs.     

On list <Emphasis Type="Italic">r</Emphasis>-hued coloring of planar graphs

A list assignment of G is a function L that assigns to each vertex \(v\in V(G)\) a list L(v) of available colors. Let r be a positive integer. For a given list assignment L of G, an (L, r)-coloring of G is a proper coloring \(\phi \) such that for any vertex v with degree d(v), \(\phi (v)\in L(v)\) and v is adjacent to at least \( min\{d(v),r\}\) different colors. The list r-hued chromatic number of G, \(\chi _{L,r}(G)\), is the least integer k such that for every list assignment L with \(|L(v)|=k\), \(v\in V(G)\), G has an (L, r)-coloring. We show that if \(r\ge 32\) and G is a planar graph without 4-cycles, then \(\chi _{L,r}(G)\le r+8\). This result implies that for a planar graph with maximum degree \(\varDelta \ge 26\) and without 4-cycles, Wagner’s conjecture in [Graphs with given diameter and coloring problem, Technical Report, University of Dortmund, Germany, 1977] holds.     

Note on incidence chromatic number of subquartic graphs

An incidence in a graph G is a pair (v, e) where v is a vertex of G and e is an edge of G incident to v. Two incidences (v, e) and (u, f) are adjacent if at least one of the following holds: \((a) v = u, (b) e = f\), or \((c) vu \in \{e,f\}\). An incidence coloring of G is a coloring of its incidences assigning distinct colors to adjacent incidences. In this note we prove that every subquartic graph admits an incidence coloring with at most seven colors.     

A linear-time algorithm for clique-coloring problem in circular-arc graphs

A maximal clique of G is a clique not properly contained in any other clique. A k-clique-coloring of a graph G is an assignment of k colors to the vertices of G such that no maximal clique with at least two vertices is monochromatic. The smallest integer k admitting a k-clique-coloring of G is called clique-coloring number of G. Cerioli and Korenchendler (Electron Notes Discret Math 35:287–292, 2009) showed that there is a polynomial-time algorithm to solve the clique-coloring problem in circular-arc graphs and asked whether there exists a linear-time algorithm to find an optimal clique-coloring in circular-arc graphs or not. In this paper we present a linear-time algorithm of the optimal clique-coloring in circular-arc graphs.     

An improved time-space lower bound for tautologies

We show that for all reals c and d such that c ² d<4 there exists a positive real e such that tautologies of length n cannot be decided by both a nondeterministic algorithm that runs in time n ^c , and a nondeterministic algorithm that runs in time n ^d and space n ^e . In particular, for every \(d<\sqrt[3]{4}\) there exists a positive e such that tautologies cannot be decided by a nondeterministic algorithm that runs in time n ^d and space n ^e .     

On irreducible no-hole <Emphasis Type="Italic">L</Emphasis>(2, 1)-coloring of subdivision of graphs

An L(2, 1)-coloring (or labeling) of a graph G is a mapping \(f:V(G) \rightarrow \mathbb {Z}^{+}\bigcup \{0\}\) such that \(|f(u)-f(v)|\ge 2\) for all edges uv of G, and \(|f(u)-f(v)|\ge 1\) if u and v are at distance two in G. The span of an L(2, 1)-coloring f, denoted by span f, is the largest integer assigned by f to some vertex of the graph. The span of a graph G, denoted by \(\lambda (G)\), is min {span \(f: f\text {is an }L(2,1)\text {-coloring of } G\}\). If f is an L(2, 1)-coloring of a graph G with span k then an integer l is a hole in f, if \(l\in (0,k)\) and there is no vertex v in G such that \(f(v)=l\). A no-hole coloring is defined to be an L(2, 1)-coloring with span k which uses all the colors from \(\{0,1,\ldots ,k\}\), for some integer k not necessarily the span of the graph. An L(2, 1)-coloring is said to be irreducible if colors of no vertices in the graph can be decreased and yield another L(2, 1)-coloring of the same graph. An irreducible no-hole coloring of a graph G, also called inh-coloring of G, is an L(2, 1)-coloring of G which is both irreducible and no-hole. The lower inh-span or simply inh-span of a graph G, denoted by \(\lambda _{inh}(G)\), is defined as \(\lambda _{inh}(G)=\min ~\{\)span f : f is an inh-coloring of G}. Given a graph G and a function h from E(G) to \(\mathbb {N}\), the h-subdivision of G, denoted by \(G_{(h)}\), is the graph obtained from G by replacing each edge uv in G with a path of length h(uv). In this paper we show that \(G_{(h)}\) is inh-colorable for \(h(e)\ge 2\), \(e\in E(G)\), except the case \(\Delta =3\) and \(h(e)=2\) for at least one edge but not for all. Moreover we find the exact value of \(\lambda _{inh}(G_{(h)})\) in several cases and give upper bounds of the same in the remaining.     

A note on (<Emphasis Type="Italic">s</Emphasis>, <Emphasis Type="Italic">t</Emphasis>)-relaxed <Emphasis Type="Italic">L</Emphasis>(2, 1)-labeling of graphs

Let \(G=(V, E)\) be a graph. For two vertices u and v in G, we denote \(d_G(u, v)\) the distance between u and v. A vertex v is called an i-neighbor of u if \(d_G(u,v)=i\). Let s, t and k be nonnegative integers. An (s, t)-relaxed k-L(2, 1)-labeling of a graph G is an assignment of labels from \(\{0, 1, \ldots , k\}\) to the vertices of G if the following three conditions are met: (1) adjacent vertices get different labels; (2) for any vertex u of G, there are at most s 1-neighbors of u receiving labels from \(\{f(u)-1,f(u)+1\}\); (3) for any vertex u of G, the number of 2-neighbors of u assigned the label f(u) is at most t. The (s, t)-relaxed L(2, 1)-labeling number \(\lambda _{2,1}^{s,t}(G)\) of G is the minimum k such that G admits an (s, t)-relaxed k-L(2, 1)-labeling. In this article, we refute Conjecture 4 and Conjecture 5 stated in (Lin in J Comb Optim. doi: 10.1007/s10878-014-9746-9, 2013).     

Reconstruction of hidden graphs and threshold group testing

Classical group testing is a search paradigm where the goal is the identification of individual positive elements in a large collection of elements by asking queries of the form “Does a set of elements contain a positive one?”. A graph reconstruction problem that generalizes the classical group testing problem is to reconstruct a hidden graph from a given family of graphs by asking queries of the form “Whether a set of vertices induces an edge”. Reconstruction problems on families of Hamiltonian cycles, matchings, stars and cliques on n vertices have been studied where algorithms of using at most 2nlg?n,(1+o(1))(nlg?n),2n and 2n queries were proposed, respectively. In this paper we improve them to \((1+o(1))(n\lg n),(1+o(1))(\frac{n\lg n}{2}),n+2\lg n\) and n+lg?n, respectively. Threshold group testing is another generalization of group testing which is to identify the individual positive elements in a collection of elements under a more general setting, in which there are two fixed thresholds ? and u, with ?<u, and the response to a query is positive if the tested subset of elements contains at least u positive elements, negative if it contains at most ? positive elements, and it is arbitrarily given otherwise. For the threshold group testing problem with ?=u?1, we show that p positive elements among n given elements can be determined by using O(plg?n) queries, with a matching lower bound.     

The matching extension problem in general graphs is co-NP-complete

A simple connected graph G with 2n vertices is said to be k-extendable for an integer k with \(0<k<n\) if G contains a perfect matching and every matching of cardinality k in G is a subset of some perfect matching. Lakhal and Litzler (Inf Process Lett 65(1):11–16, 1998) discovered a polynomial algorithm that decides whether a bipartite graph is k-extendable. For general graphs, however, it has been an open problem whether there exists a polynomial algorithm. The new result presented in this paper is that the extendability problem is co-NP-complete.     

Is there any polynomial upper bound for the universal labeling of graphs?

A universal labeling of a graph G is a labeling of the edge set in G such that in every orientation \(\ell \) of G for every two adjacent vertices v and u, the sum of incoming edges of v and u in the oriented graph are different from each other. The universal labeling number of a graph G is the minimum number k such that G has universal labeling from \(\{1,2,\ldots , k\}\) denoted it by \(\overrightarrow{\chi _{u}}(G) \). We have \(2\Delta (G)-2 \le \overrightarrow{\chi _{u}} (G)\le 2^{\Delta (G)}\), where \(\Delta (G)\) denotes the maximum degree of G. In this work, we offer a provocative question that is: “Is there any polynomial function f such that for every graph G, \(\overrightarrow{\chi _{u}} (G)\le f(\Delta (G))\)?”. Towards this question, we introduce some lower and upper bounds on their parameter of interest. Also, we prove that for every tree T, \(\overrightarrow{\chi _{u}}(T)={\mathcal {O}}(\Delta ^3) \). Next, we show that for a given 3-regular graph G, the universal labeling number of G is 4 if and only if G belongs to Class 1. Therefore, for a given 3-regular graph G, it is an \( {{\mathbf {N}}}{{\mathbf {P}}} \)-complete to determine whether the universal labeling number of G is 4. Finally, using probabilistic methods, we almost confirm a weaker version of the problem.     

A sufficient condition for planar graphs to be (3, 1)-choosable

A (k, d)-list assignment L of a graph is a function that assigns to each vertex v a list L(v) of at least k colors satisfying \(|L(x)\cap L(y)|\le d\) for each edge xy. An L-coloring is a vertex coloring \(\pi \) such that \(\pi (v) \in L(v)\) for each vertex v and \(\pi (x) \ne \pi (y)\) for each edge xy. A graph G is (k, d)-choosable if there exists an L-coloring of G for every (k, d)-list assignment L. This concept is known as choosability with separation. In this paper, we will use Thomassen list coloring extension method to prove that planar graphs with neither 6-cycles nor adjacent 4- and 5-cycles are (3, 1)-choosable. This is a strengthening of a result obtained by using Discharging method which says that planar graphs without 5- and 6-cycles are (3, 1)-choosable.     

On (<Emphasis Type="Italic">s</Emphasis>, <Emphasis Type="Italic">t</Emphasis>)-relaxed strong edge-coloring of graphs

In this paper, we introduce a new relaxation of strong edge-coloring. Let G be a graph. For two nonnegative integers s and t, an (s, t)-relaxed strong k-edge-coloring is an assignment of k colors to the edges of G, such that for any edge e, there are at most s edges adjacent to e and t edges which are distance two apart from e assigned the same color as e. The (s, t)-relaxed strong chromatic index, denoted by \({\chi '}_{(s,t)}(G)\), is the minimum number k of an (s, t)-relaxed strong k-edge-coloring admitted by G. This paper studies the (s, t)-relaxed strong edge-coloring of graphs, especially trees. For a tree T, the tight upper bounds for \({\chi '}_{(s,0)}(T)\) and \({\chi '}_{(0,t)}(T)\) are given. And the (1, 1)-relaxed strong chromatic index of an infinite regular tree is determined. Further results on \({\chi '}_{(1,0)}(T)\) are also presented.     

Hamiltonian numbers in oriented graphs

A hamiltonian walk of a digraph is a closed spanning directed walk with minimum length in the digraph. The length of a hamiltonian walk in a digraph D is called the hamiltonian number of D, denoted by h(D). In Chang and Tong (J Comb Optim 25:694–701, 2013), Chang and Tong proved that for a strongly connected digraph D of order n, \(n\le h(D)\le \lfloor \frac{(n+1)^2}{4} \rfloor \), and characterized the strongly connected digraphs of order n with hamiltonian number \(\lfloor \frac{(n+1)^2}{4} \rfloor \). In the paper, we characterized the strongly connected digraphs of order n with hamiltonian number \(\lfloor \frac{(n+1)^2}{4} \rfloor -1\) and show that for any triple of integers n, k and t with \(n\ge 5\), \(n\ge k\ge 3\) and \(t\ge 0\), there is a class of nonisomorphic digraphs with order n and hamiltonian number \(n(n-k+1)-t\).