Technology-based total factor productivity and benchmarking: New proposals and an application

The present study fills a gap between the benchmarking literature and multi-output based efficiency and productivity studies by proposing a benchmarking framework to analyze total factor productivity (TFP). Different specifications of the Hicks–Moorsteen TFP index are tailored for specific benchmarking perspectives: (1) static, (2) fixed base and unit, and (3) dynamic TFP change. These approaches assume fixed units and/or base technologies as benchmarks. In contrast to most technology-based productivity indices, the standard Hicks–Moorsteen index always leads to feasible results. Through these specifications, managers can assess different facets of the firm's strategic choices in comparison with firm-specific relevant benchmarks and thus have a broad background for decision making. An empirical application for the Spanish banking industry between 1998 and 2006 illustrates the managerial implications of the proposed framework.     

Productivity drift in extended learning curves

The pattern of changes in the Extended Learning Curves representing the performance of 114 assembly workers in an electronics firm is examined in terms of changes in productivity drift over long periods of time. It is shown that 2 types of discontinuities can occur. The first consists of a temporary levelling off in productivity followed by a recovery to new higher levels of productivity; the second has a sustained period of negative productivity drift. A number of work facets are statistically tested as possible causes of these patterns of productivity drift, but, the only significant relationship (at P ≤ 0.05 level) is with length of service in job. Some evidence is presented to show that conventional work measurement methods are not effective in terms of assessing the true work output of experienced workers since such workers are able to beat the system by claiming those allowances which are most difficult to cross-check.     

Pathways to productivity improvement

A study of productivity in the Machine Tool industry has just been published by the Engineering Employers Federation (EEF). As a member of the Productivity Steering Group, information was available to one of the authors, in an unusually detailed and validated form for the twenty or so individual companies, (though they remain anonymous). It was thought worthwhile to apply methods developed in the Economics and Statistics Department of British Aerospace to this data in order to give pointers to the factors explaining productivity differences. The particular methods referred to were those of the Diagnostic Chart, though considerably simplified to match the data available, and multiple regression analysis. Particular care is necessary in applying the latter technique in productivity analysis if spurious results are to be excluded. The conclusions were as follows: the most favoured path to improved productivity is via increased turnover; changes in productivity are reflected mainly in changes in the ‘profit’ element of value added rather than in the labour cost element; the major factor distinguishing low from high productivity companies is an excess of the manual work force in relation to turnover; increased fixed assets favours increased labour productivity; increased commitment to R & D favours increased labour productivity; these conclusions are, of course, deduced from a study of the machine tool industry in particular, but may well be of applicability to other industries.     

How can MNEs benefit from internationalizing their R&D across countries with both weak and strong IPR protection?

Although MNEs internationalize their R&D not only in developed countries but also in emerging economies that typically feature weak protection of intellectual property rights (IPR), it remains unclear how this strategic decision affects their productivity performance. This limitation has resulted in a rather incomplete understanding of why some MNEs become more productive through R&D internationalization while others do not. This study develops a new explanation, suggesting that R&D internationalization does not affect the productivity of all MNEs equally because of differences in the idiosyncratic way in which MNEs geographically distribute their R&D units across weak and strong IPR protection countries. In advancing this explanation, the study challenges the view that weak IPR protection is disadvantageous for MNEs by showing that (and specifying how) it: 1) increases the efficacy of MNEs' internal R&D, 2) strengthens the advantages of accessing globally dispersed knowledge, and (3) improves MNEs' ability to exploit cross-country differences in IPR protection. The study enhances understanding of the complex role of IPR protection, shifts scholarly attention from the degree of R&D internationalization to how MNEs should internationalize their R&D, and clarifies how the IPR context of their location choices matters.     

Using Data Envelopment Analysis (DEA) for monitoring efficiency-based performance of productivity-driven organizations: Design and implementation of a decision support system

The competitive nature of the business environment requires the productivity-driven organization to be aware of its relative level of effectiveness and efficiency vis-à-vis its competitors. This suggests the need, first, for an effective mechanism that allows for discovering appropriate productivity models for improving overall organizational performance, and, second for a feedback-type mechanism that allows for evaluating multiple productivity models in order to select the most suitable one. In this paper our focus is on organizations that consider the states of their internal (e.g., possibly exemplified by resource-based view) and external (e.g., possibly exemplified by positioning) organizational environment in the formulation of their strategies. We propose and test a DEA-centric Decision Support System (DSS) that aims to assess and manage the relative performance of such organizations.     

Parkinson,Peter and probability: Implications for productivity

Improving productivity and effectiveness in society and organizations is a need which is not being met satisfactorily in most countries. Goals of society and organizations are defined in circular and spiral terms, one leading to the other, as encouraging the development of individual capabilities, achieving greater effectiveness, attaining a better quality of life, and enhancing human dignity. Parkinson's Law, Peter's Principle and Robinson's Law (“in a bureaucracy, work alters upon advancement”) illustrate in satirical form many truths about why organizations and society are not increasing their levels of goal attainment. Clues for overcoming this adversity are the treatment of such laws as probability concepts to demonstrate that future performance of a specific organization cannot be predicted, and the recognition that unstated assumptions—we know how to apply accumulated knowledge and the research approach should be followed—need to be converted to much different explicit ones. Evidence demonstrating why this is so and what ought to be done is reviewed. A planning and design approach based on an orientation of purposes-target-results is presented, and some different change principles that result from the approach are described.     

Multi-valued measures in DEA in the presence of undesirable outputs

Data envelopment analysis (DEA) evaluates the relative efficiency of a set of comparable decision making units (DMUs) with multiple performance measures (inputs and outputs). Classical DEA models rely on the assumption that each DMU can improve its performance by increasing its current output level and decreasing its current input levels. However, undesirable outputs (like wastes and pollutants) may often be produced together with desirable outputs in final products which have to be minimized. On the other hands, in some real-world situations, we may encounter some specific performance measures with more than one value which are measured by various standards. In this study, we referee such measures as multi-valued measures which only one of their values should be selected. For instance, unemployment rate is a multi-valued measure in economic applications since there are several definitions or standards to measure it. As a result, selecting a suitable value for a multi-valued measure is a challenging issue and is crucial for successful application of DEA. The aim of this study is to accommodate multi-valued measures in the presence of undesirable outputs. In doing so, we formulate two individual and summative selecting directional distance models and develop a pair of multiplier- and envelopment-based selecting approaches. Finally, we elaborate applicability of the proposed method using a real data on 183 NUTS 2 regions in 23 selected EU-28 countries.     

Harnessing Diversity and Collective Action in the Top Management Team

Diversity has become an important issue at all levels of the company from the boardroom to the back office. It is increasingly apparent that diversity is vital to productivity, with academic research indicating an important link between diverse top management team (TMT) composition and corporate performance. However, the nature of this link remains elusive, as there is little accessible research that can help top teams to evaluate how diversity impacts on their strategic capacity. This paper seeks to fill this gap by developing a conceptual framework, illustrated with case examples, to explain the relationships between TMT diversity and TMT collective action. As collective action is difficult to attain from top teams that are high in diversity, six practical processes are developed from this framework for establishing and exploiting top team strategic capacity. The paper concludes by outlining the theoretical implications of the framework.

It is the range of skills and attributes acquired through a diversity of experiences and backgrounds that combine to create a cohesive and effective board.¹

     

Perceived Ambiguity and Relevant Measures

We axiomatize preferences that can be represented by a monotonic aggregation of subjective expected utilities generated by a utility function and some set of i.i.d. probability measures over a product state space, S^∞. For such preferences, we define relevant measures, show that they are treated as if they were the only marginals possibly governing the state space, and connect them with the measures appearing in the aforementioned representation. These results allow us to interpret relevant measures as reflecting part of perceived ambiguity, meaning subjective uncertainty about probabilities over states. Under mild conditions, we show that increases or decreases in ambiguity aversion cannot affect the relevant measures. This property, necessary for the conclusion that these measures reflect only perceived ambiguity, distinguishes the set of relevant measures from the leading alternative in the literature. We apply our findings to a number of well‐known models of ambiguity‐sensitive preferences. For each model, we identify the set of relevant measures and the implications of comparative ambiguity aversion.     

Largest area convex hull of imprecise data based on axis-aligned squares

In recent years, more and more algorithms related to imprecise data have been proposed. Specifically, some algorithms on computing the maximum area convex hull are designed recently when the imprecise data are modeled as non-overlapping axis-aligned squares or as equal size squares. The time complexity of the best known algorithm based on non-overlapping axis-aligned squares is O(n ⁷). If the squares have equal size and can overlap, the time complexity of the best known algorithm is O(n ⁵). In this paper, we improve the former from O(n ⁷) to O(n ⁵) and improve the latter from O(n ⁵) to O(n ²). These results are obtained by exploiting the non-trivial geometric properties of the problems.     

Max-coloring paths: tight bounds and extensions

The max-coloring problem is to compute a legal coloring of the vertices of a graph G=(V,E) with vertex weights w such that $\sum_{i=1}^{k}\max_{v\in C_{i}}w(v_{i})$ is minimized, where C ₁,??,C _k are the various color classes. For general graphs, max-coloring is as hard as the classical vertex coloring problem, a special case of the former where vertices have unit weight. In fact, in some cases it can even be harder: for example, no polynomial time algorithm is known for max-coloring trees. In this paper we consider the problem of max-coloring paths and its generalization, max-coloring skinny trees, a broad class of trees that includes paths and spiders. For these graphs, we show that max-coloring can be solved in time O(|V|+time for sorting the vertex weights). When vertex weights are real numbers, we show a matching lower bound of ??(|V|log?|V|) in the algebraic computation tree model.     

Productivity gains by cellular manufacturing

This paper discusses some of the major factual results and discussions of the effects of implementation of a cellular manufacturing environment on the productivity of people, management and facilities, as was experienced in this study. It is suggested that significant improvements at very low costs are possible at managerial, and other work force levels, by introduction of appropriate production management systems. This is based on analysis of the changes in production costs and more importantly the behaviour of employees brought about by a first time implementation of cellular manufacturing in a company.     

Du pont decision support system (DSS) for expenditure budgeting

The objective of this project is to develop a decision support system (DSS) for expenditure budgeting. The system will support current expenditure budgeting according to the same principles as the fixed expenditure (capital) budgeting. The framework of the analysis is based on an ex ante version of the traditional (ex post) du Pont system presenting the profitability of the firm as a function of asset turnover and profit margin. The present approach depicts the relationships between sales and the alternative classes of expenditure, expenses and assets by means of a mathematical model expressed as a DSS in an EXCEL spreadsheet framework. The model assumes that the average absorption time and revenue lag structure for expenditure classes are constant in time. However, the monetary productivity of expenditures is a second-order parabola of the amount of expenditure. The use of the model is demonstrated in two illustrative cases (SIEMENS and ABB) using published financial statement data. The estimation of the revenue function is based on an interactive analysis and simulation with past data.     

Ranking using η-efficiency and relative size measures based on DEA

In this paper, we propose a new way to define the size of organizations or Decision Making Units (DMUs) based on Data Envelopment Analysis (DEA). A great number of managerial decisions, social and economic activities, political analysis and engineering process include in their analysis some information about the size of corporations. Usually, organizations consider particular attributes such as revenues, employees, number of clients, profit and so forth to evaluate their sizes, which could result on an incomplete and/or partial size evaluation. Here, we investigate this question more deeply and propose a non-parametric approach for ranking size. To address this issue, we first construct a DEA super-efficiency target vector defined over an extended Technology set and find a common set of weights to determine new efficiencies and sizes, possibly greater than one. After, we define rotation and translation of DMUs and show how to construct a range area, associated to η-efficiencies and relative sizes that are less than or equal to one. Additionally, based on managerial decisions, we show how to use these ideas to achieve new η-efficiency and relative size goals for one or more DMUs in the set. We consider an empirical application to illustrate our approach on a dataset of international airlines and conclude the paper with some final remarks and future directions.     

Die Auswirkungen von Neid auf individuelle Leistungen: Ergebnisse einer Panelanalyse

Relative income differences are likely to lead to envy within a reference group. Envy in turn influences social behavior and individual performance. While positional concerns are apparent in daily life, empirical evidence is rare in the economic literature. This paper investigates the impact of the relative income position on individuals’ performance or productivity. As ?performance“ is difficult to measure we turn to soccer players whose performance has been well documented. The broad sample covers eight seasons of the German premier soccer league (Bundesliga) between 1995 and 2004, and includes 1040 players, a salary proxy and several performance variables. The results show that player performance is strongly affected by relative income position. A disadvantage in the relative income position reduces productivity. The larger the income differences within a team, the stronger are the effects of positional concern. Team composition also significantly affects behaviour.     

Returns to scale vs. damages to scale in data envelopment analysis: An impact of U.S. clean air act on coal-fired power plants

This study proposes a use of Data Envelopment Analysis (DEA) to measure Returns to Scale (RTS) of US coal-fired power plants. The power plants produce not only desirable outputs (e.g., electricity) but also undesirable outputs (e.g., CO₂ and NO_x) as a result of their plant operations. Therefore, the proposed use of DEA also measures a new concept, or “DTS: Damages to Scale” (corresponding to RTS for undesirable outputs). Both scale measures discussed in this study are a quick-and-easy approach for assessing RTS and DTS, but not an exact method, because it does not consider a direct linkage between the two measures. This study applies the proposed approach to examine the legal validity of U.S. Clean Air Act (CAA). We find that the CAA has been legally effective and influential on the operation of coal-fired power plants in the United States because their plant operations belong to increasing RTS on a desirable output and increasing DTS on three undesirable outputs. The increasing DTS indicates a need for managerial improvement and/or engineering innovation such as advanced clean coal technology. This empirical result implies that U.S. federal and state governments need to expand the legal scope of CAA to the emission control of CO₂ because the current CAA excludes the regulation on CO₂ emission that is now considered as a main source of the global warming and climate change.     

Online scheduling on uniform machines with two hierarchies

In this paper we study online scheduling problem on m parallel uniform machines with two hierarchies. The objective is to minimize the maximum completion time (makespan). Machines are provided with different capability. The machines with speed s can schedule all jobs, while the other machines with speed 1 can only process partial jobs. Online algorithms for any 0<s<∞ are provided in the paper. For the case of k=1 and m=2, and the case of some values of s, k=1 and m=3, the algorithms are the best possible, where k is the number of machines with hierarchy 1, and m is the number of machines. Lower bounds for some special cases are also presented.     

The computational complexity of QoS measures for orchestrations

We consider Web services defined by orchestrations in the Orc language and two natural quality of services measures, the number of outputs and a discrete version of the first response time. We analyse first those subfamilies of finite orchestrations in which the measures are well defined and consider their evaluation in both reliable and probabilistic unreliable environments. On those subfamilies in which the QoS measures are well defined, we consider a set of natural related problems and analyse its computational complexity. In general our results show a clear picture of the difficulty of computing the proposed QoS measures with respect to the expressiveness of the subfamilies of Orc. Only in few cases the problems are solvable in polynomial time pointing out the computational difficulty of evaluating QoS measures even in simplified models.     

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.