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.     

Corporate ethics: evidence from Islamic banks

The purpose of this study is to investigate whether banks’ management behavior is related to corporate ethics. We employ earnings-management and expense-preference measures to evaluate management behavior. Using a very large sample of banks from 15 countries and controlling for a number of bank- and country-level factors, we find that managers in Islamic banks are less likely to engage in unethical business practices compared to those in commercial banks. We also document that Shari’ah supervisory boards embedded in Islamic banks affect and shape managerial behavior and mitigate agency problems. These results establish a link between corporate ethics and management behavior through Shari’ah and Shari’ah supervisory boards.     

Strategic networks of discovery and creation entrepreneurs

Current research favors diversity within strategic networks as a source of idea generation and opportunity pursuit. However, diversity may not always be advantageous. Drawing from literature on entrepreneurial opportunities, social network theory, and cognitive psychology, it is argued in this paper that the level of diversity in entrepreneurial strategic networks differs based on the nature of the entrepreneurial opportunity context—discovery or creation. Competing hypotheses are developed for the nature of strategic networks in the discovery and creation opportunity contexts. The results from our two studies (using PSED II dataset and data collected from women entrepreneurs in India) show that entrepreneurial strategic networks differ based on whether entrepreneurs are pursuing discovery or creation opportunities, i.e., entrepreneurs operating in ‘discovery’ contexts tend to use networks ties with individuals who are relatively similar to themselves, while entrepreneurs in ‘creation’ contexts tend to use network ties with individuals who are relatively different from themselves. Further, the results also show that the diversity in strategic networks is not unidirectional in discovery and/or creation contexts but varies depending on the specific matters for which the entrepreneur seeks advice. Discussion and future research directions outline the unique findings of this study and potential implications for theory development.     

The micro-foundations of the returnee liability: The interpersonal challenges of returnee entrepreneurs in Kenya

Although it is known that returnee entrepreneurs can contribute to technological and economic upgrading in their home countries, there is also evidence of a returnee liability where returnee entrepreneurs perform worse than locals. Apart from mismatches between home and host country institutional environments, this liability is argued to stem from interpersonal factors like cultural difficulties and the diminished social capital of returnees at home. Using interviews exploring the experiences of twenty Nairobi-based technology-enabled returnee entrepreneurs, we theorize the micro-foundations of the returnee liability: mismatched expectations, cultural tension and mutual suspicion. Returnees who sent remittances while abroad expect locals to support their return and entrepreneurial vision, but locals expect continued financial support. Returnees who had become more individualistic while fending for themselves in Western economies experience tension with the collectivism of locals, even while they seek to readjust to their home culture. The suspicion of returnees about unethical local business practices and frustration about locals’' apparent inability to value proposed innovations further complicate the ability of returnees to access local knowledge and networks. We discuss how the community support addresses these micro-foundations of the returnee liability and thus help developing countries better benefit from the knowledge and innovations of their returnees.     

Darwinism,organizational evolution and survival: key challenges for future research

How do social organizations evolve? How do they adapt to environmental pressures? What resources and capabilities determine their survival within dynamic competition? Charles Darwin’s seminal work The Origin of Species (1859) has provided a significant impact on the development of the management and organization theory literatures on organizational evolution. This article introduces the JMG Special Issue focused on Darwinism, organizational evolution and survival. We discuss key themes in the organizational evolution research that have emerged in recent years. These include the increasing adoption of the co-evolutionary approach, with a particular focus on the definition of appropriate units of analysis, such as routines, and related challenges associated with exploring the relationship between co-evolution, re-use of knowledge, adaptation, and exaptation processes. We then introduce the three articles that we have finally accepted in this Special Issue after an extensive, multi-round, triple blind-review process. We briefly outline how each of these articles contributes to understanding among scholars, practitioners and policy makers of the continuous evolutionary processes within and among social organizations and systems.     

Brokerage and governance for business networks: a metasynthesis-based discussion

This article reviews and discusses empirical literature on the micro-mechanisms of Burt’s concept of brokerage for inter-firm business networks from a governance perspective. Using a combination of a literature review and a qualitative metasynthesis, research gaps are first identified in the literature about these micro-mechanisms and then filled with interpretations, stemming from a qualitative metasynthesis of 13 in-depth case studies on brokerage for business network environments. The paper discusses three related elements and their inter-relationship in the brokerage process: the enabling factors for brokerage in business networks; the brokerage activities, particularly the combination of “bonding”, “bridging”, exclusion, and moderation/negotiation in different network configurations; and the outcomes of brokerage for business networks. We argue that network managers should take care of these elements when using brokerage to govern business networks. For example, the positional factors of agents in the network who take over brokerage functions need to be monitored and a balance of their embeddedness in the network and independence of focal firms should be safeguarded. Moreover, activities associated with brokerage should be steered and controlled in order to generate network benefits such as a higher collaborative stance of the partaking firms or learning processes amongst them.     

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.     

Directed Steiner trees with diffusion costs

Given a directed arc-weighted graph G with n nodes, a root r and k terminals, the directed steiner tree problem (DST) consists in finding a minimum-weight tree rooted at r and spanning all the terminals. If this problem has several applications in multicast routing in packet switching networks, the modeling is not adapted anymore in networks based upon the circuit switching principle in which some nodes, called non diffusing nodes, are unable to duplicate packets. We define a more general problem, namely the directed steiner tree with a limited number of diffusing nodes (DSTLD), that enables us to model multicast in a network containing at most d diffusing nodes. We show that DSTLD is XP with respect to d, and use this result to build a \(\left\lceil \frac{k-1}{d} \right\rceil \)-approximation algorithm for DST that is XP in d. We deduce from that result a strong inapproximability property. In particular, we prove that, under the assumption that NP \(\not \subseteq \) ZTIME \([n^{\log ^{O(1)}n}]\), there is no polynomial-time approximation algorithm for DSTLD with ratio \(\varOmega \left( \frac{k}{d}\right) \). We finally give an evaluation of performances of an exact algorithm dedicated to the case \(d \le 3\).     

Approximating <Emphasis Type="Italic">k</Emphasis>-generalized connectivity via collapsing HSTs

An instance of the k -generalized connectivity problem consists of an undirected graph G=(V,E), whose edges are associated with non-negative costs, and a collection \({\mathcal{D}}=\{(S_{1},T_{1}),\ldots,(S_{d},T_{d})\}\) of distinct demands, each of which comprises a pair of disjoint vertex sets. We say that a subgraph ??G connects a demand (S _i ,T _i ) when it contains a path with one endpoint in S _i and the other in T _i . Given an integer parameter k, the goal is to identify a minimum cost subgraph that connects at least k demands in \({\mathcal{D}}\).Alon, Awerbuch, Azar, Buchbinder and Naor (SODA ’04) seem to have been the first to consider the generalized connectivity paradigm as a unified machinery for incorporating multiple-choice decisions into network formation settings. Their main contribution in this context was to devise a multiplicative-update online algorithm for computing log-competitive fractional solutions, and to propose provably-good rounding procedures for important special cases. Nevertheless, approximating the generalized connectivity problem in its unconfined form, where one makes no structural assumptions about the underlying graph and collection of demands, has remained an open question up until a recent O(log?² nlog?² d) approximation due to Chekuri, Even, Gupta and Segev (SODA ’08). Unfortunately, the latter result does not extend to connecting a pre-specified number of demands. Furthermore, even the simpler case of singleton demands has been established as a challenging computational task, when Hajiaghayi and Jain (SODA ’06) related its inapproximability to that of dense k -subgraph.In this paper, we present the first non-trivial approximation algorithm for k-generalized connectivity, which is derived by synthesizing several techniques originating in probabilistic embeddings of finite metrics, network design, and randomization. Specifically, our algorithm constructs, with constant probability, a feasible subgraph whose cost is within a factor of O(n ^2/3?polylog(n,k)) of optimal. We believe that the fundamental approach illustrated in the current writing is of independent interest, and may be applicable in other settings as well.     

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.     

Reconfiguration of dominating sets

We explore a reconfiguration version of the dominating set problem, where a dominating set in a graph G is a set S of vertices such that each vertex is either in S or has a neighbour in S. In a reconfiguration problem, the goal is to determine whether there exists a sequence of feasible solutions connecting given feasible solutions s and t such that each pair of consecutive solutions is adjacent according to a specified adjacency relation. Two dominating sets are adjacent if one can be formed from the other by the addition or deletion of a single vertex. For various values of k, we consider properties of \(D_k(G)\), the graph consisting of a node for each dominating set of size at most k and edges specified by the adjacency relation. Addressing an open question posed by Haas and Seyffarth, we demonstrate that \(D_{\varGamma (G)+1}(G)\) is not necessarily connected, for \(\varGamma (G)\) the maximum cardinality of a minimal dominating set in G. The result holds even when graphs are constrained to be planar, of bounded tree-width, or b-partite for \(b \ge 3\). Moreover, we construct an infinite family of graphs such that \(D_{\gamma (G)+1}(G)\) has exponential diameter, for \(\gamma (G)\) the minimum size of a dominating set. On the positive side, we show that \(D_{n-\mu }(G)\) is connected and of linear diameter for any graph G on n vertices with a matching of size at least \(\mu +1\).     

A novel approach for detecting multiple rumor sources in networks with partial observations

Locating source of information diffusion in networks has very important applications such as locating the sources of epidemics, news/rumors in social networks or online computer virus. In this paper, we consider detecting multiple rumor sources from a deterministic point of view by modeling it as the set resolving set (SRS) problem. Let G be a network on n nodes. A node subset K is an SRS of G if all detectable node sets are distinguishable by K. The problem of multiple rumor source detection (MRSD) in the network can be modeled as finding an SRS K with the smallest cardinality. In this paper, we propose a polynomial-time greedy algorithm for finding a minimum SRS in a general network, achieving performance ratio \(O(\ln n)\). This is the first work establishing a relation between the MRSD problem and a deterministic concept of SRS, and a first work to give the minimum SRS problem a polynomial-time performance-guaranteed approximation algorithm. Our framework suggests a robust and efficient approach for estimating multiple rumor sources independent of diffusion models in networks.     

Fehlerkultur,Fehlermanagement und ihre Bedeutung für Maßnahmen der Personalentwicklung in Kliniken

Error culture, error management and the significance in personnel development The author picks up themes about error culture and error management. As a first step are discussed the relationships between error culture and education and error management and economics. After this the main view of the article lies on high security systems like the atomic industries and the air transportation business. Especially the error reporting in the cockpit may be a model for developing good error cultures in clinics. In the end the author gives some recommendations in personnel work for clinics.     

On the best possible competitive ratio for the multislope ski-rental problem

The multislope ski-rental problem is an extension of the classical ski-rental problem, where the player has several lease options besides the pure rent and buy options. In this problem the hardness of an instance, which is the setting of options, significantly affects the player’s performance. There is an algorithm that for a given instance, computes the best possible strategy. However, the output is given as numerical values and therefore the relational nature between an instance and the best possible performance for it has not been known. In this paper we prove that even for the easiest instance, a competitive ratio smaller than \(e/(e - 1) \approx 1.58\) cannot be achieved. More precisely, a tight lower bound on the best possible performance is obtained in a closed form parametrized by the number of options. Furthermore, we establish a matching upper and lower bound on the competitive ratio each for the 3-option and 4-option problems.     

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 popular matching and condensation problems under matroid constraints

The popular matching problem introduced by Abraham, Irving, Kavitha, and Mehlhorn is a matching problem in which there exist applicants and posts, and applicants have preference lists over posts. A matching M is said to be popular, if there exists no other matching N such that the number of applicants that prefer N to M is larger than the number of applicants that prefer M to N. The goal of this problem is to decide whether there exists a popular matching, and find a popular matching if one exists. In this paper, we first consider a matroid generalization of the popular matching problem with strict preference lists, and give a polynomial-time algorithm for this problem. In the second half of this paper, we consider the problem of transforming a given instance of a matroid generalization of the popular matching problem with strict preference lists by deleting a minimum number of applicants so that it has a popular matching. This problem is a matroid generalization of the popular condensation problem with strict preference lists introduced by Wu, Lin, Wang, and Chao. By using the results in the first half, we give a polynomial-time algorithm for this problem.     

Possible winner problems on partial tournaments: a parameterized study

We study possible winner problems related to the uncovered set and the Banks set on partial tournaments from the viewpoint of parameterized complexity. We first study a problem where given a partial tournament D and a subset X of vertices, we are asked to add some arcs to D such that all vertices in X are included in the uncovered set. We focus on two parameterizations: parameterized by |X| and parameterized by the number of arcs to be added. In addition, we study a parameterized variant of the problem which is to determine whether all vertices of X can be included in the uncovered set by reversing at most k arcs. Finally, we study some parameterizations of a possible winner problem on partial tournaments, where we are given a partial tournament D and a distinguished vertex p, and asked whether D has a maximal transitive subtournament with p being the 0-indegree vertex. These parameterized problems are related to the Banks set. We achieve \(\mathcal {XP}\) results, \(\mathcal {W}\)-hardness results as well as \(\mathcal {FPT}\) results along with a kernelization lower bound for the problems studied in this paper.     

Serve or skip: the power of rejection in online bottleneck matching

We consider the online matching problem, where n server-vertices lie in a metric space and n request-vertices that arrive over time each must immediately be permanently assigned to a server-vertex. We focus on the egalitarian bottleneck objective, where the goal is to minimize the maximum distance between any request and its server. It has been shown that while there are effective algorithms for the utilitarian objective (minimizing total cost) in the resource augmentation setting where the offline adversary has half the resources, these are not effective for the egalitarian objective. Thus, we propose a new Serve-or-Skip (SoS) bicriteria analysis model, where the online algorithm may reject or skip up to a specified number of requests, and propose two greedy algorithms: GriNN(t) and \({{\textsc {Grin}}^*(t)}\). We show that the SoS model of resource augmentation analysis can essentially simulate the doubled-server-capacity model, and then examine the performance of GriNN(t) and \({\textsc {Grin}^*(t)}\).     

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.     

Incremental Facility Location Problem and Its Competitive Algorithms

We consider the incremental version of the k-Facility Location Problem, which is a common generalization of the facility location and the k-median problems. The objective is to produce an incremental sequence of facility sets F ₁?F ₂?????F _n , where each F _k contains at most k facilities. An incremental facility sequence or an algorithm producing such a sequence is called c -competitive if the cost of each F _k is at most c times the optimum cost of corresponding k-facility location problem, where c is called competitive ratio. In this paper we present two competitive algorithms for this problem. The first algorithm produces competitive ratio 8α, where α is the approximation ratio of k-facility location problem. By recently result (Zhang, Theor. Comput. Sci. 384:126–135, 2007), we obtain the competitive ratio \(16+8\sqrt{3}+\epsilon\). The second algorithm has the competitive ratio Δ+1, where Δ is the ratio between the maximum and minimum nonzero interpoint distances. The latter result has its self interest, specially for the small metric space with Δ≤8α?1.