27 resultados para Expected profit
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The tendency of managers to focus on short-term results rather than on sustained company success is of particular importance to retail marketing managers, because marketing activities involve expenditures which may only pay off in the longer term. To address the issue of myopic management, our study shows how the complexity of the service profit chain (SPC) can cause managers to make suboptimal decisions. Hence, our paper departs from past research by recognizing that understanding the temporal interplay between operational investments, employee satisfaction, customer satisfaction, and operating profit is essential to achieving sustained success. In particular, we intend to improve understanding of the functioning of the SPC with respect to time lags and feedback loops. Results of our large-scale longitudinal study set in a multi-outlet retail chain reveal time-lag effects between operational investments and employee satisfaction, as well as between customer satisfaction and performance. These findings, along with evidence of a negative interaction effect of employee satisfaction on the relationship between current performance and future investments, show the substantial risk of mismanaging the SPC. We identify specific situations in which the dynamic approach leads to superior marketing investment decisions, when compared to the conventional static view of the SCP. These insights provide valuable managerial guidance for effectively managing the SPC over time. © 2012 New York University.
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The majority of research on the pharmaceutical sector has focused on an overall micro economic, medical oriented welfare issues, whereas the marketing management role of the innovative drug manufacturer has to a large extent been disregarded. Using the case of Turkey, through a series of in-depth interviews with highly innovative companies, other marketing management possibilities are explored based on broader definitions of value and transparency. Our results suggest that pharmaceutical companies as well as the government might have a too narrow focus of value and underestimate the potential long term benefits of a broader approach to marketing management and long term relationships between the various stakeholders.
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This paper aims to broaden the present corporate social responsibility (CSR) reporting literature by extending its focus to the absence of CSR reporting within a developing country, an area which, to date, is relatively under researched in comparison to the more widely studied presence of CSR reporting within developed Western countries. In particular this paper concentrates upon the lack of disclosure on three particular eco-justice issues: child labour, equal opportunities and poverty alleviation. We examine why this is the case and thereby illuminate underlying motives behind corporate unwillingness to address these issues. For this purpose, 23 semi-structured interviews were undertaken with senior corporate managers in Bangladesh. The findings suggest that the main reasons for non-disclosure include lack of resources, the profit imperative, lack of legal requirements, lack of knowledge/awareness, poor performance and the fear of bad publicity. Given these findings the paper raises some serious concerns as to why corporations would ever be expected to voluntarily report on eco-justice issues where performance is poor and negative publicity would be generated and profit impaired. Further research is still required to uncover current injustices and to imagine what changes can be made.
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The aim of this paper is to illustrate the measurement of productive efficiency using Nerlovian indicator and metafrontier with data envelopment analysis techniques. Further, we illustrate how profit efficiency of firms operating in different regions can be aggregated into one overarching frontier. Sugarcane production in three regions in Kenya has been used to illustrate these concepts. Results show that the sources of inefficiency in all regions are both technical and allocative, but allocative efficiency contributes more to the overall Nerlovian (in)efficiency indicator. © 2011 Springer-Verlag.
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Although crisp data are fundamentally indispensable for determining the profit Malmquist productivity index (MPI), the observed values in real-world problems are often imprecise or vague. These imprecise or vague data can be suitably characterized with fuzzy and interval methods. In this paper, we reformulate the conventional profit MPI problem as an imprecise data envelopment analysis (DEA) problem, and propose two novel methods for measuring the overall profit MPI when the inputs, outputs, and price vectors are fuzzy or vary in intervals. We develop a fuzzy version of the conventional MPI model by using a ranking method, and solve the model with a commercial off-the-shelf DEA software package. In addition, we define an interval for the overall profit MPI of each decision-making unit (DMU) and divide the DMUs into six groups according to the intervals obtained for their overall profit efficiency and MPIs. We also present two numerical examples to demonstrate the applicability of the two proposed models and exhibit the efficacy of the procedures and algorithms. © 2011 Elsevier Ltd.
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Today's market conditions require nonprofit leaders to act in an increasingly business-like fashion. This study asks whether NPO leaders have a similar disposition to act entrepreneurially as for-profit entrepreneurs, but hold different underlying motives. For this purpose, the study contrasts a sample of 72 leaders of nonprofit organizations with 117 entrepreneurs on their personality traits and explicit motives using standard personality tests and interviews. Both groups exhibit similar general and entrepreneurship-specific personality traits but differ significantly regarding their motivation. While nonprofit leaders' motivation stems primarily from the meaningfulness of their work; entrepreneurs are mainly motivated by the independence as well as by the income and profit provided by their work. This paper helps us understand who leaders of nonprofit organizations are.
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Smart grid technologies have given rise to a liberalised and decentralised electricity market, enabling energy providers and retailers to have a better understanding of the demand side and its response to pricing signals. This paper puts forward a reinforcement-learning-powered tool aiding an electricity retailer to define the tariff prices it offers, in a bid to optimise its retail strategy. In a competitive market, an energy retailer aims to simultaneously increase the number of contracted customers and its profit margin. We have abstracted the problem of deciding on a tariff price as faced by a retailer, as a semi-Markov decision problem (SMDP). A hierarchical reinforcement learning approach, MaxQ value function decomposition, is applied to solve the SMDP through interactions with the market. To evaluate our trading strategy, we developed a retailer agent (termed AstonTAC) that uses the proposed SMDP framework to act in an open multi-agent simulation environment, the Power Trading Agent Competition (Power TAC). An evaluation and analysis of the 2013 Power TAC finals show that AstonTAC successfully selects sell prices that attract as many customers as necessary to maximise the profit margin. Moreover, during the competition, AstonTAC was the only retailer agent performing well across all retail market settings.
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This paper aims to analyse the impact of regulation in the financial performance of the Water and Sewerage companies (WaSCs) in England and Wales over the period 1991–2008. In doing so, a panel index approach is applied across WaSCs over time to decompose unit-specific index number-based profitability growth as a function of the profitability, productivity and price performance growth achieved by benchmark firms, and the catch up to the benchmark firm achieved by less productive firms. The results indicated that after 2000 there is a steady decline in average price performance, while productivity improves resulting in a relatively stable economic profitability. It is suggested that the English and Welsh water regulator is now more focused on passing productivity benefits to consumers, and maintaining stable profitability than it was in earlier regulatory periods. This technique is of great interest for regulators to evaluate the effectiveness of regulation and companies to identify the determinants of profit change and improve future performance, even if sample sizes are limited.
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Fuzzy data envelopment analysis (DEA) models emerge as another class of DEA models to account for imprecise inputs and outputs for decision making units (DMUs). Although several approaches for solving fuzzy DEA models have been developed, there are some drawbacks, ranging from the inability to provide satisfactory discrimination power to simplistic numerical examples that handles only triangular fuzzy numbers or symmetrical fuzzy numbers. To address these drawbacks, this paper proposes using the concept of expected value in generalized DEA (GDEA) model. This allows the unification of three models - fuzzy expected CCR, fuzzy expected BCC, and fuzzy expected FDH models - and the ability of these models to handle both symmetrical and asymmetrical fuzzy numbers. We also explored the role of fuzzy GDEA model as a ranking method and compared it to existing super-efficiency evaluation models. Our proposed model is always feasible, while infeasibility problems remain in certain cases under existing super-efficiency models. In order to illustrate the performance of the proposed method, it is first tested using two established numerical examples and compared with the results obtained from alternative methods. A third example on energy dependency among 23 European Union (EU) member countries is further used to validate and describe the efficacy of our approach under asymmetric fuzzy numbers.