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.     

Approximation algorithms for minimum weight partial connected set cover problem

In the Minimum Weight Partial Connected Set Cover problem, we are given a finite ground set \(U\), an integer \(q\le |U|\), a collection \(\mathcal {E}\) of subsets of \(U\), and a connected graph \(G_{\mathcal {E}}\) on vertex set \(\mathcal {E}\), the goal is to find a minimum weight subcollection of \(\mathcal {E}\) which covers at least \(q\) elements of \(U\) and induces a connected subgraph in \(G_{\mathcal {E}}\). In this paper, we derive a “partial cover property” for the greedy solution of the Minimum Weight Set Cover problem, based on which we present (a) for the weighted version under the assumption that any pair of sets in \(\mathcal {E}\) with nonempty intersection are adjacent in \(G_{\mathcal {E}}\) (the Minimum Weight Partial Connected Vertex Cover problem falls into this range), an approximation algorithm with performance ratio \(\rho (1+H(\gamma ))+o(1)\), and (b) for the cardinality version under the assumption that any pair of sets in \(\mathcal {E}\) with nonempty intersection are at most \(d\)-hops away from each other (the Minimum Partial Connected \(k\)-Hop Dominating Set problem falls into this range), an approximation algorithm with performance ratio \(2(1+dH(\gamma ))+o(1)\), where \(\gamma =\max \{|X|:X\in \mathcal {E}\}\), \(H(\cdot )\) is the Harmonic number, and \(\rho \) is the performance ratio for the Minimum Quota Node-Weighted Steiner Tree problem.     

Resistance to Change and the Language of Public Organizations: A Look at “Clashing Grammars” in Large-Scale Information Technology Projects

The management environment of large-scale agency information technology (IT) projects is used as a framework for examining the notion of clashing grammars as a form of resistance to change within public organizations. Such projects, rooted in new management disciplines from the private sector, are being initiated in broad mimetic fashion by agencies seeking improved performance. The common problems with these projects may be manifestations of resistance to the very management tools developed for their implementation. This resistance may occur inadvertently when new grammars characteristic to modern IT projects clash with more traditional grammars embedded in the culture of public organizations.     

A Cross-national Analysis of Global E-government

To explore the determinants of global e-government performance, this paper examines the aggregate data of 163 different countries by conducting multivariate statistical analysis. The results of multivariate regression analysis indicate that the performance of digital government is likely to be determined by economic wealth, education, urbanization, civil liberties, government effectiveness, and the interaction between Internet usage and economic wealth, while the extent of internet penetration alone does not determine e-government performance. More importantly, this study indicates that government effectiveness is much more important than any other factors in determining global e-government performance. The countries with high e-government performance are likely to be the wealthy, developed, and Western countries or the rapidly developing Asian countries.

Strategic benchmarking at ICI Fibres

Learning from comparison has two generic forms in business, at the strategic or business level, and at the level of individual processess. Most literature has discussed the ‘micro’ form—focused on specific practices or processes. The case of ICI Fibres shows that:

• 1.1. business performance benchmarks are just as measurable as those for processes,
• 2.2. there is a clear hierarchy of strategic/operating/ micro-process benchmarks which managers need to understand,
• 3.3. effective strategic management brings together benchmarks for business strengths and benchmarks for process capabilities,
• 4.4. you cannot benchmark your way to profit with the wrong strategy.

     

Supply chain management in the US and Taiwan: An empirical study

This study uses an empirical survey of middle-line managers in the US and Taiwan to study the association of supply chain management components and organizational performance. Through structural equation modeling, critical components of supply chain management are found to have considerable effects on organizational performance. The findings of the study are summarized as follows:

•$•$

Supply chain competencies have positive effects on organizational performance in both the US and Taiwan. Supply chain competencies are developed around quality and service, operations and distribution, and design effectiveness. The goal of supply chain competencies is to satisfy customer requirements.     

The Effect of Female Strategic Managers on Organizational Performance

Little empirical work explores the impact of female managers on organizational performance. This paper uses Miles and Snow’s management strategies to empirically determine if female and male managers use different strategies and what influence these strategies have on organizational performance. Using data and superintendent survey responses from Texas school districts from the years 2000 through 2005, differences between male and female managers are discovered. Female managers and the strategies they use have a positive influence on performance. These results are discussed in the context of the gender and management literature and in the general field of public management.

Substitution, availability and preferences in earnings management: empirical evidence from China

Our study analyzes financial reporting data on earnings management from a rapidly changing economy—the PRC. Some Chinese regulatory reforms allow for an easy identification of incentives to engage in both accounting and real earnings management activities. In addition, straightforward economic reasoning suggests that firms incur different costs for pursuing these strategies, which leads to the possibility of a hierarchy or ranking of different earnings management practices. Our results show that accounting and real earnings management activities were significantly higher for firms in danger of missing a regulation imposed performance threshold. After controlling for the availability of the different instruments, our results provide weak evidence for a ranking of different earnings management activities.

An approximation algorithm for the <Emphasis Type="Italic">k</Emphasis>-level capacitated facility location problem

We consider the k-level capacitated facility location problem (k-CFLP), which is a natural variant of the classical facility location problem and has applications in supply chain management. We obtain the first (combinatorial) approximation algorithm with a performance factor of \(k+2+\sqrt{k^{2}+2k+5}+\varepsilon\) (ε>0) for this problem.     

Improved approximation algorithms for the max-bisection and the disjoint 2-catalog segmentation problems

We consider the max-bisection problem and the disjoint 2-catalog segmentation problem, two well-known NP-hard combinatorial optimization problems. For the first problem, we apply the semidefinite programming (SDP) relaxation and the RPR² technique of Feige and Langberg (J. Algorithms 60:1–23, 2006) to obtain a performance curve as a function of the ratio of the optimal SDP value over the total weight through finer analysis under the assumption of convexity of the RPR² function. This ratio is shown to be in the range of [0.5,1]. The performance curve implies better approximation performance when this ratio is away from 0.92, corresponding to the lowest point on this curve with the currently best approximation ratio of 0.7031 due to Feige and Langberg (J. Algorithms 60:1–23, 2006). For the second problem, similar technique results in an approximation ratio of 0.7469, improving the previously best known result 0.7317 due to Wu et al. (J. Ind. Manag. Optim. 8:117–126, 2012).     

Can institutional investors fix the corporate governance problem? Some Danish evidence

It has been advocated within corporate governance that institutional investors may discipline management in listed firms and thereby alleviate the free rider problem associated with dispersed ownership. This article tests this hypothesis using a sample of Danish listed firms during 1998–2001 determining, whether ownership by institutional investors impacts performance, measured by Tobin’s q. Using three stage least squares, it is shown that aggregate ownership by institutional investors does not influence firm performance. However, when decomposing the results, it is found that joint ownership by the largest two Danish institutional investors, has a significant negative impact firm performance. Ownership by banks and to a lesser extent insurance companies significantly influences firm performance positively. The results somehow challenge the conventional wisdom, arguing that the black box view of institutional investors should be abandon. Therefore it is suggested that a more careful analysis should be devoted to each institutional investors own legal environment.

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 \(d \le 3\).     

Single-machine batch delivery scheduling with an assignable common due window

This paper addresses a batch delivery single-machine scheduling problem in which jobs have an assignable common due window. Each job will incur an early (tardy) penalty if it is early (tardy) with respect to the common due window under a given schedule. There is no capacity limit on each delivery batch, and the cost per batch delivery is fixed and independent of the number of jobs in the batch. The objective is to find the optimal size and location of the window, the optimal dispatch date for each job, as well as an optimal job sequence to minimize a cost function based on earliness, tardiness, holding time, window location, window size, and batch delivery. We show that the problem can be optimally solved in O(n⁸)$O(n^8)$ time by a dynamic programming algorithm under a reasonable assumption on the relationships among the cost parameters. A computational experiment is also conducted to evaluate the performance of the proposed algorithm. We also show that some special cases of the problem can be optimally solved by lower order algorithms.     

Finding a contra-risk path between two nodes in undirected graphs

Given an undirected graph with a source node s and a sink node t. The anti-risk path problem is defined as the problem of finding a path between node s to node t with the least risk under the assumption that at most one edge of each path may be blocked. Xiao et al. (J Comb Optim 17:235–246, 2009) defined the problem and presented an \(O(mn+n^2 \log n)\) time algorithm to find an anti-risk path, where n and m are the number of nodes and edges, respectively. Recently, Mahadeokar and Saxena (J Comb Optim 27:798–807, 2014) solved the problem in \(O(m+n \log n)\) time. In this paper, first, a new version of the anti-risk path (called contra-risk path) is defined, which is more effective than an anti-risk path in many networks. Then, an algorithm to find a contra-risk path is presented, which runs in \(O(m+n \log n)\) time.     

An integrative approach to assess environmental and economic sustainability in multi-tier supply chains

Abstract

Multi-tier supply chain sustainability is paramount to achieve corporate sustainability, due to the significant impacts from organisations beyond the focal firm boundaries and its direct suppliers. However, including environmental considerations within the dominant profit-centric logic of supply chain related decisions is prone to generate sustainability tensions. This work aims to support organisations address tensions between sustainability dimensions by adopting an integrative approach for sustainable supply chain management performance assessment thanks to an innovative eco-intensity based performance assessment method, which achieves a balanced consideration of environmental and economic performance in a weak sustainability perspective. The method, using primary data sourced from actual practice and featuring an indirect multi-tier approach with decentralised responsibilities across organisations, is applied to a case study of a machinery supply chain. The proposed integrative approach can support addressing sustainability tensions in the area of sustainable supply chain management, facilitate sustainable supplier evaluation and identify supply chain hotspots for operational improvement.     

Optimal on-line algorithms for one batch machine with grouped processing times

In this paper, we study on-line scheduling problems on a batch machine with the assumption that all jobs have their processing times in [p, (1+φ)p], where p>0 and \(\phi=(\sqrt{5}-1)/2\). Jobs arrive over time. First, we deal with the on-line problem on a bounded batch machine with the objective to minimize makespan. A class of algorithms with competitive ratio \((\sqrt{5}+1)/2\) are given. Then we consider the scheduling on an unbounded batch machine to minimize the time by which all jobs have been delivered, and provide a class of on-line algorithms with competitive ratio \((\sqrt{5}+1)/2\). The two class of algorithms are optimal for the problems studied here.     

On the performance of mildly greedy players in cut games

We continue the study of the performance of mildly greedy players in cut games initiated by Christodoulou et al. (Theoret Comput Sci 438:13–27, 2012), where a mildly greedy player is a selfish agent who is willing to deviate from a certain strategy profile only if her payoff improves by a factor of more than \(1+\epsilon \), for some given \(\epsilon \ge 0\). Hence, in presence of mildly greedy players, the classical concepts of pure Nash equilibria and best-responses generalize to those of \((1+\epsilon )\)-approximate pure Nash equilibria and \((1+\epsilon )\)-approximate best-responses, respectively. We first show that the \(\epsilon \)-approximate price of anarchy, that is the price of anarchy of \((1+\epsilon )\)-approximate pure Nash equilibria, is at least \(\frac{1}{2+\epsilon }\) and that this bound is tight for any \(\epsilon \ge 0\). Then, we evaluate the approximation ratio of the solutions achieved after a \((1+\epsilon )\)-approximate one-round walk starting from any initial strategy profile, where a \((1+\epsilon )\)-approximate one-round walk is a sequence of \((1+\epsilon )\)-approximate best-responses, one for each player. We improve the currently known lower bound on this ratio from \(\min \left\{ \frac{1}{4+2\epsilon },\frac{\epsilon }{4+2\epsilon }\right\} \) up to \(\min \left\{ \frac{1}{2+\epsilon },\frac{2\epsilon }{(1+\epsilon )(2+\epsilon )}\right\} \) and show that this is again tight for any \(\epsilon \ge 0\). An interesting and quite surprising consequence of our results is that the worst-case performance guarantee of the very simple solutions generated after a \((1+\epsilon )\)-approximate one-round walk is the same as that of \((1+\epsilon )\)-approximate pure Nash equilibria when \(\epsilon \ge 1\) and of that of subgame perfect equilibria (i.e., Nash equilibria for greedy players with farsighted, rather than myopic, rationality) when \(\epsilon =1\).