Sustainability, epistemology, ecocentric business and marketing strategy:ideology, reality and vision

This conceptual article examines the relationship between marketing and sustainability through the dual lenses of anthropocentric and ecocentric epistemology. Using the current anthropocentric epistemology and its associated dominant social paradigm, corporate ecological sustainability in commercial practice and business school research and teaching is difficult to achieve. However, adopting an ecocentric epistemology enables the development of an alternative business and marketing approach that places equal importance on nature, the planet, and ecological sustainability as the source of human and other species' well-being, as well as the source of all products and services. This article examines ecocentric, transformational business, and marketing strategies epistemologically, conceptually and practically and thereby proposes six ecocentric, transformational, strategic marketing universal premises as part of a vision of and solution to current global un-sustainability. Finally, this article outlines several opportunities for management practice and further research. © 2012 Springer Science+Business Media Dordrecht.

Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector

Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.

Semantic annotation for knowledge management:requirements and a survey of the state of the art

While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. In the emerging Semantic Web, search, interpretation and aggregation can be addressed by ontology-based semantic mark-up. In this paper, we examine semantic annotation, identify a number of requirements, and review the current generation of semantic annotation systems. This analysis shows that, while there is still some way to go before semantic annotation tools will be able to address fully all the knowledge management needs, research in the area is active and making good progress.

Business sustainability through successful integration of marketing and operations

Special Issue on Integrating marketing and operations for business sustainability

Management interventions and prosocial behaviours:understanding the mediating mechanisms

Previous research suggests that the attitudes and behaviours of front-line employees (FLEs) significantly influence customers’ evaluations of service quality and customer satisfaction. Therefore, it becomes important to identify the variables that influence FLEs job attitudes and Prosocial ServiceBehaviours (PSBs). The conceptual framework developed from extant literature is presented, which proposes that management interventions (internal communication, training and development and empowerment) have a direct effect on PSBs. In addition, these relationships are mediated by role stress and job attitudes. Implications for service management and future research directions are discussed.

The legacy of climategate:revitalizing or undermining climate science and policy?

The release of emails from a server at the University of East Anglia's Climate Research Unit (CRU) in November 2009 and the following climategate controversy have become a topic for interpretation in the social sciences. This article picks out some of the most visible social science comments on the affair for discussion. These comments are compared to an account of what can be seen as problematic practices by climate scientists. There is general agreement in these comments that climate science needs more openness and transparency. But when evaluating climategate a variety of responses is seen, ranging from the apologetic to the highly critical, even condemning the practices in question. It is argued that reluctance to critically examine the climategate affair, including suspect practices of scientists, has to do with the nature of the debate which is highly politicized. A call is made for more reflection on this case which should not be closed off because of political expediency. © 2012 John Wiley & Sons, Ltd.

A solution for information management in logistics operations of modern manufacturing chains

One dominant feature of the modern manufacturing chains is the movement of goods. Manufacturing companies would remain an unprofitable investment if the supplies/logistics of raw materials, semi-finished products or final goods are not handled in an effective way. Both levels of a modern manufacturing chain-actual production and logistics-are characterized by continuous data creation at a much faster rate than they can be meaningfully analyzed and acted upon manually. Often, instant and reliable decisions need to be taken based on huge, previously inconceivable amounts of heterogeneous, contradictory or incomplete data. The paper will highlight aspects of information flows related to business process data visibility and observability in modern manufacturing networks. An information management platform developed in the framework of the EU FP7 project ADVANCE will be presented.

Green manufacturing supply chain design and operations decision support

This special issue of International Journal of Production Research provides a platform for sharing the knowledge base, recent research outputs and a review of recent developments highlighting the critical aspects of green manufacturing supply chain design and operations decision support. The special issue includes 15 contributions presenting new and significant research in the relevant area. Contributions mainly present either a novel green/sustainable manufacturing supply chain design and operations decision support approach applied to a problem, or a state-of-the-art method on green/sustainable factors in supply chain design and operations. The article delineates an overview of the contributions and their significance, and an introspection on the ‘green’ factors involved.

Supporting and Enhancing Research on Cultural Heritage in France: the PATRIMA Project

In this paper, we first overview the French project on heritage called PATRIMA, launched in 2011 as one of the Projets d'investissement pour l'avenir, a French funding program meant to last for the next ten years. The overall purpose of the PATRIMA project is to promote and fund research on various aspects of heritage presentation and preservation. Such research being interdisciplinary, research groups in history, physics, chemistry, biology and computer science are involved in this project. The PATRIMA consortium involves research groups from universities and from the main museums or cultural heritage institutions in Paris and surroundings. More specifically, the main members of the consortium are the two universities of Cergy-Pontoise and Versailles Saint-Quentin and the following famous museums or cultural institutions: Musée du Louvre, Château de Versailles, Bibliothèque nationale de France, Musée du Quai Branly, Musée Rodin. In the second part of the paper, we focus on two projects funded by PATRIMA named EDOP and Parcours and dealing with data integration. The goal of the EDOP project is to provide users with a data space for the integration of heterogeneous information about heritage; Linked Open Data are considered for an effective access to the corresponding data sources. On the other hand, the Parcours project aims at building an ontology on the terminology about the techniques dealing with restoration and/or conservation. Such an ontology is meant to provide a common terminology to researchers using different databases and different vocabularies.

The complements towards developing a new risk management framework and Its applicability to the Nigerian power sector

The availability of regular supply has been identified as one of the major stimulants for the growth and development of any nation and is thus important for the economic well-being of a nation. The problems of the Nigerian power sector stems from a lot of factors culminating in her slow developmental growth and inability to meet the power demands of her citizens regardless of the abundance of human and natural resources prevalent in the nation. The research therefore had the main aim of investigating the importance and contributions of risk management to the success of projects specific to the power sector. To achieve this aim it was pertinent to examine the efficacy of risk management process in practice and elucidate the various risks typically associated with projects (Construction, Contractual, Political, Financial, Design, Human resource and Environmental risk factors) in the power sector as well as determine the current situation of risk management practice in Nigeria. To address this factors inhibiting the proficiency of the overarching and prevailing issue which have only been subject to limited in-depth academic research, a rigorous mixed research method was adopted (quantitative and qualitative data analysis). A review of the Nigeria power sector was also carried out as a precursor to the data collection stage. Using purposive sampling technique, respondents were identified and a questionnaire survey was administered. The research hypotheses were tested using inferential statistics (Pearson correlation, Chi-square test, t-test and ANOVA technique) and the findings revealed the need for the development of a new risk management implementation Framework. The proposed Framework was tested within a company project, for interpreting the dynamism and essential benefits of risk management with the aim of improving the project performances (time), reducing the level of fragmentation (quality) and improving profitability (cost) within the Nigerian power sector in order to bridge a gap between theory and practice. It was concluded that Nigeria’s poor risk management practices have prevented it from experiencing strong growth and development. The study however, concludes that the successful implementation of the developed risk management framework may help it to attain this status by enabling it to become more prepared and flexible, to face challenges that previously led to project failures, and thus contributing to its prosperity. The research study provides an original contribution theoretically, methodologically and practically which adds to the project risk management body of knowledge and to the Nigerian power sector.

Menedzsmentképességek és döntéshozatali közelítésmódok longitudinális elemzése a versenyképesség-kutatások alapján (Longitudinal analysis of management capabilities and decision making approaches based on the competitiveness researches)

Számos korábbi kutatás – köztük a szerzők korábbi vizsgálatai is – azt mutatja, hogy a menedzsmentképességek és a vállalatok versenyképessége között pozitív kapcsolat áll fenn, a jobban teljesítő és a proaktívabb vállalatok rendre felkészültebb, jobb vezetői képességekkel bíró, kockázatvállalóbb vezetőkkel rendelkeznek. Az is megfigyelhető, hogy az ebből a nézőpontból sikeresebben működő vállalatok döntéseiben az átlagosnál is erősebben érvényesül a racionális közelítésmód, melynek alkalmazásával a menedzserek az optimális cselekvési alternatíva kiválasztására törekszenek. A cikkben a szerzők az elmúlt 15 év versenyképességi kutatásainak tapasztalatait összegzik, kiemelt hangsúlyt helyezve a legfrissebb felmérés eredményeire. ________________ The article summarizes the main findings of the Competitiveness Research Program with respect to the skills and capabilities of the Hungarian managers and the decision making approaches they use during their work. The results of the four surveys conducted in 1996, 1999, 2004 and 2009 are fairly stable over time: practice minded behavior, professional expertise, and problem solving skills are on the top of the list of the most developed skills of the Hungarian executives. The rational approach is the most popular among the most widespread decision making models in the authors’ sample which is rather alarming since the present turbulent economic environment may demand more adaptive and intuitive approaches.

Tudásmenedzsment: problémák és veszélyek (Knowledge management: problems and dangers)

A tudásmenedzsment több terület metszeteként is értelmezhető új megközelítése a vállalatok vezetésének. A megközelítés napjaink slágertémája, ugyanakkor egy olyan gyógyszerre hasonlíthatjuk, melyek kockázatait és mellékhatásait még nem ismerjük. Ebben a cikkben néhány nehézségre, problémára kívánom a figyelmet ráirányítani. ______ Knowledge management is interpretable as the intersection of different management research areas. KM is one of the most popular topic of management literature and practice, but it is similar to a medicine, which is effective, although its risks and side-effects are not known. In this paper I present some problems and difficulties in this area.

The effect of cooperative learning on the attitudes toward science and the achievement of students in a non-science majors' general biology laboratory course at an urban community college

The purpose of this study was to evaluate the effect of cooperative learning strategies on students' attitudes toward science and achievement in BSC 1005L, a non-science majors' general biology laboratory course at an urban community college. Data were gathered on the participants' attitudes toward science and cognitive biology level pre and post treatment in BSC 1005L. Elements of the Learning Together model developed by Johnson and Johnson and the Student Team-Achievement Divisions model created by Slavin were incorporated into the experimental sections of BSC 1005L.^ Four sections of BSC 1005L participated in this study. Participants were enrolled in the 1998 spring (January) term. Students met weekly in a two hour laboratory session. The treatment was administered to the experimental group over a ten week period. A quasi-experimental pretest-posttest control group design was used. Students in the cooperative learning group (n$\sb1$ = 27) were administered the Test of Science-Related Attitudes (TOSRA) and the cognitive biology test at the same time as the control group (n$\sb2$ = 19) (at the beginning and end of the term).^ Statistical analyses confirmed that both groups were equivalent regarding ethnicity, gender, college grade point average and number of absences. Independent sample t-tests performed on pretest mean scores indicated no significant differences in the TOSRA scale two or biology knowledge between the cooperative learning group and the control group. The scores of TOSRA scales: one, three, four, five, six, and seven were significantly lower in the cooperative learning group. Independent sample t-tests of the mean score differences did not show any significant differences in posttest attitudes toward science or biology knowledge between the two groups. Paired t-tests did not indicate any significant differences on the TOSRA or biology knowledge within the cooperative learning group. Paired t-tests did show significant differences within the control group on TOSRA scale two and biology knowledge. ANCOVAs did not indicate any significant differences on the post mean scores of the TOSRA or biology knowledge adjusted by differences in the pretest mean scores. Analysis of the research data did not show any significant correlation between attitudes toward science and biology knowledge. ^

An agent-based model of team coordination and performance

This research is based on the premises that teams can be designed to optimize its performance, and appropriate team coordination is a significant factor to team outcome performance. Contingency theory argues that the effectiveness of a team depends on the right fit of the team design factors to the particular job at hand. Therefore, organizations need computational tools capable of predict the performance of different configurations of teams. This research created an agent-based model of teams called the Team Coordination Model (TCM). The TCM estimates the coordination load and performance of a team, based on its composition, coordination mechanisms, and job’s structural characteristics. The TCM can be used to determine the team’s design characteristics that most likely lead the team to achieve optimal performance. The TCM is implemented as an agent-based discrete-event simulation application built using JAVA and Cybele Pro agent architecture. The model implements the effect of individual team design factors on team processes, but the resulting performance emerges from the behavior of the agents. These team member agents use decision making, and explicit and implicit mechanisms to coordinate the job. The model validation included the comparison of the TCM’s results with statistics from a real team and with the results predicted by the team performance literature. An illustrative 26-1 fractional factorial experimental design demonstrates the application of the simulation model to the design of a team. The results from the ANOVA analysis have been used to recommend the combination of levels of the experimental factors that optimize the completion time for a team that runs sailboats races. This research main contribution to the team modeling literature is a model capable of simulating teams working on complex job environments. The TCM implements a stochastic job structure model capable of capturing some of the complexity not capture by current models. In a stochastic job structure, the tasks required to complete the job change during the team execution of the job. This research proposed three new types of dependencies between tasks required to model a job as a stochastic structure. These dependencies are conditional sequential, single-conditional sequential, and the merge dependencies.