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The purpose of this paper is to propose the use of graph theoretic structural modeling for assessing the possible reduction in complexity of the work flow procedures in an organization due to lean initiatives. A tool to assess the impact of lean initiative on complexity of the system at an early stage of decision making is proposed.

First, the permanent function-based graph theoretic structural model has been applied to understand the complex structure of a manufacturing system under consideration. The model helps by systematically breaking it into different sub-graphs that identify all the cycles of interactions among the subsystems in the organization in a systematic manner. The physical interpretation of the existing quantitative methods linked to graph theoretic methodology, namely two types of coefficients of dissimilarity, has been used to evolve the new measures of organizational complexity. The new methods have been deployed for studying the impact of different lean initiatives on complexity reduction in a case industrial organization.

The usefulness and the application of new proposed measures of complexity have been demonstrated with the help of three cases of lean initiatives in an industrial organization. The new measures of complexity have been proposed as a credible tool for studying the lean initiatives and their implications.

The paper may lead many researchers to use the proposed tool to model different cases of lean manufacturing and pave a new direction for future research in lean manufacturing.

The paper demonstrates the application of new tools through cases and the tool may be used by practitioners of lean philosophy or total quality management to model and investigate their decisions.

The proposed measures of complexity are absolutely new addition to the tool box of graph theoretic structural modeling and have a potential to be adopted by practical decision makers to steer their organizations though such decisions before the costly interruptions in manufacturing systems are tried on ground.

The purpose of this paper is to study the impact of restructuring in the manufacturing system at the conceptual stage using graph theoretic model.

Some restructuring decisions are conceptualized which reflect the aim of the organization to gradually evolve the manufacturing system towards a leaner structure. This is achieved by way of defining simplified procedures so that lesser hindrance in terms of cycles of interactions is encountered. The restructuring decisions are represented by five restructured configurations of the manufacturing system, through gradual removal of appropriate interaction links. The graph theoretic models are developed for original configuration and each of the new restructured configurations and the resulting structural characterization information is used to compare the structure of restructured configurations with the original configuration. The value of the coefficient of dissimilarity of each of the new configurations with respect to the original configuration is obtained to have a quantitative estimate of the simplification that may be achieved by different contemplated restructuring decisions.

The present work shows that the restructuring decisions can be represented by different configurations in the form of schematic diagrams involving minor changes in the interaction structure among subsystems of the manufacturing system. The quantitative analysis using coefficient of dissimilarity for restructuring decisions indicated that there are varying levels of impact created by five comparable restructuring decisions considered in the study. The findings have a potential to guide the restructuring efforts by identifying a focus area that can produce greater impact of restructuring.

The findings are valid for a particular case manufacturing organization which does not involve itself in extensive design activity. The study is based on the assumption that the schematic diagram and graph theoretic model captured all the relevant influencing factors of the manufacturing system.

The study provides an easy to use methodology for the practical decision makers in manufacturing industry striving to improve the performance of their organization. It can provide the analysis of restructuring decisions at the conceptual stage itself without the necessity of disturbing the normal functioning of the organization. There is a scope for identifying focus areas where the restructuring may yield comparatively greater dividends.

The study of restructuring by representing it in the form of changes in interactions among subsystems of a manufacturing system and investigation of the impact of such restructuring efforts at the conceptual stage using graph theoretic model has been carried out for the first time.

To ascertain the diffusion and influence of Savolainen's ELIS model and its use as a theoretical and/or methodological basis for research.

A context citation analysis was made of the work where this researcher published his model. Analysis covered the year of publication, the type of work and the subject matter of the citing documents concerned. In-context citations were analysed for their frequency in each citing text, style, location and content cited.

The ELIS model received 18.5 cites/year. 20.2 per cent of them corresponded to papers published in journals in other areas, mainly computer science. The average of cites per paper was 1.8; 64.5 percent of the citing works cited them only once. 60 per cent of the cites were considered essential. Only 13.7 per cent of these cites appear in theory or methods. 37 per cent of the citing documents contained no concept relating to the model.

The method used focuses on the most direct context of a cite (sentence or paragraph), but isolates it from the general context (full document, other documents by the author or their social capital). It has, however, allowed this research issue to be dealt with under laboratory conditions and revealed nuances hidden by the absolute number of cites.

It has become evident that the dissemination and influence of the ELIS model are less than what the total number of cites indicates and that it has scarcely been incorporated into research design. Despite its popularity, it is not being validated and/or refuted by way of empirical data.

This study chooses the content perception perspective to develop a theoretical model portraying the psychological activities of Web surfers exposed to content Web sites. After collecting 549 empirical observations in a controlled lab environment, tests the theoretical relationships by using the structural equation modelling (SEM) technique. The results strongly indicate that effective content perceptual dimensions can help content Web surfers to develop positive attitudes toward content sites, which in turn induce favorable behavioral outcomes such as frequent site usage and loyalty. Such a proposed theoretical model not only has the potential to enrich the theoretical underpinning of Internet studies but also presents a practical framework to guide content strategy formulations for the online content industry. Detailed implications for both managerial research and practice are discussed.

Past efforts to model freight transport‐choice decision making as a behavioural process have resulted in the development of models which may not reflect the actual steps, activities, decision rules, and interactions in the typical freight transport‐choice decision process in the detail needed for various applications. Script‐theoretic research, which is based on the modelling of sequential activities, is proposed as an alternative approach for the study of this process. The methodology for empirical investigations and practical applications of script‐theoretic research is discussed.

In the last four years, since Volume I of this Bibliography first appeared, there has been an explosion of literature in all the main functional areas of business. This wealth of material poses problems for the researcher in management studies — and, of course, for the librarian: uncovering what has been written in any one area is not an easy task. This volume aims to help the librarian and the researcher overcome some of the immediate problems of identification of material. It is an annotated bibliography of management, drawing on the wide variety of literature produced by MCB University Press. Over the last four years, MCB University Press has produced an extensive range of books and serial publications covering most of the established and many of the developing areas of management. This volume, in conjunction with Volume I, provides a guide to all the material published so far.

The research practice in management research is dominantly based on structural equation modeling (SEM), but almost exclusively, and often misguidedly, on covariance-based SEM. The purpose of this paper is to question the current research myopia in management research, because the paper adumbrates theoretical foundations and guidance for the two SEM streams: covariance-based and variance-based SEM; and improves the conceptual knowledge by comparing the most important procedures and elements in the SEM study, using different theoretical criteria.

The study thoroughly analyzes, reviews and presents two streams using common methodological background. The conceptual framework discusses the two streams by analysis of theory, measurement model specification, sample and goodness-of-fit.

The paper identifies and discusses the use and misuse of covariance-based and variance-based SEM utilizing common topics such as: first, theory (theory background, relation to theory and research orientation); second, measurement model specification (type of latent construct, type of study, reliability measures, etc.); third, sample (sample size and data distribution assumption); and fourth, goodness-of-fit (measurement of the model fit and residual co/variance).

The paper questions the usefulness of Cronbach's α research paradigm and discusses alternatives that are well established in social science, but not well known in the management research community. The author presents short research illustration in which analyzes the four recently published papers using common methodological background. The paper concludes with discussion of some open questions in management research practice that remain under-investigated and unutilized.

The purpose of this paper is to close the gap between the theoretical nature of existing contributions in customer engagement value (CEV) and its need to practically empower business decisions. This is done by proposing a framework that consists of three techniques, each of which combines the components of CEV to make it more comprehensive and applicable. The paper also reviews and analyzes the work that has been done so far in the area of CEV whether in business to business (B2B), business to consumer (B2C) or consumer to consumer (C2C) markets.

CEV is a comprehensive term that measures the total value of the customer through capturing his transactional and non-transactional behaviors. Hence, it is an essential term for measuring the value of the customer in direct marketing. This motivates researchers to compete in developing models to maximize CEV. Meanwhile, most of the existing models are conceptual and the majority of them lack applicability due to many reasons. First, these models relied on a linear version of the CEV model, hence double-counting the value of the customer; also they weighted the components of CEV equally, which is unrealistic. Finally, the effect of the environmental components in determining the engagement level of each customer was almost ignored. In this paper, two main contributions are presented. First, a summary and analysis of the contributions of the literature in the CEV field for different market types whether in B2C, B2B or C2C. Furthermore, three modifications are added to the existing models. The first model introduces a non-linear relationship of the components of CEV. The second model is a weighted linear model of these components. Finally, the third model adds the environmental factors to the CEV components. All the proposed models are theoretical in nature, however, these models are expected to show superiority when being applied to real data sets due to their ability to capture the complexity in the relationship between the firm and its customers in real-life situations. The proposed models are expected to attract the practitioners and other researchers and they both are encouraged to apply the proposed models on real-life data sets, test their performance, compare them against each other, to be able to apply each of them on the best suitable data set and business scenario.

Based on the review and analysis that has been done on about 87 papers, it is found that the majority of the contributions that have been done in the area of CEV are theoretical in nature, in spite of the effectiveness of CEV in empowering business decision. It is also found that few researchers proposed a set of theoretical comprehensive frameworks that combined CEV’s components together. Meanwhile, those frameworks are not practically applicable.

Although the contribution of the proposed models expected to attract both researchers and practitioners, these are not applied to real-life case studies to prove their effectiveness.

The research in this paper has many industrial and managerial implications. First, it helps managers and decision takers to treat the customers as assets and cost-free resources who can work with the firm to achieve what’s both aims to (i.e. increase customer satisfaction and firm’s profitability). Second, it helps the firm to determine the total value of each customer and treat its customers accordingly. Third, it empowers the managers to do target marketing, based on grouping the customers upon their total engagement. This would save time and cost and for sure increase the profitability and customer satisfaction. Forth, the proposed models take into consideration not only the transactional behavior of the customers but also the non-transactional factors that play a significant role in formulating the relationship between the firm and its customers.

This is hereby to certify that the paper is original, neither the paper nor a part of it is under consideration for publication anywhere else. Also, this study has no conflicts of interest to disclose.

The purpose of this paper is to provide a new way of rethinking banking models by using qualitative research on intangibles. This is required because the banking sector has been transformed significantly by the changing environment over the past two decades. The 2007-2009 financial crisis also added to concerns about existing bank business models.

Using qualitative data collected from interviews with bank managers and analysts in the UK, this paper develops a grounded theory of bank intangibles.

The model reveals how intangibles and tangible/financial resources interact in the bank value creation process, how they actively respond to environmental changes, how bank intangibles are understood by external observers such as analysts, and how bankers and analysts differ in their views.

Grounded theory provides the means to further develop bank models as business models and theoretical models. This provides the means to think beyond conventional finance constructs and to relate bank models to a wider theoretical literature concerning intellectual capital, organisational and social systems theory, and “performativity”.

Such development of bank models and of a systems perspective is critical to the understanding of banks by bankers, by observers and for their “critical and reflexive performativity”. It also has implications for systemic risk and bank regulation.

The paper reveals the core role of intellectual capital (IC) in banks, in markets, and in developing theory and research at firm and system levels.

The purpose of this paper is to apply the situational theory of publics and framing theory in the context of environmental corporate social responsibility (CSR) communication research to determine how message frames impact information seeking and processing.

Using a 3 (message frame: diagnostic, prognostic, or motivational) × 2 (environmental issue: general vs specific) plus control between subjects experimental design, the study examines the attitudes, cognitions, and behavioral intentions different publics may form about two different environmental responsibility issues presented in this study. Furthermore, the study aims to examine how different types of message frames (diagnostic, prognostic, or motivational) and topics may impact how a company can move a public toward information seeking behaviors.

Based on theoretical considerations, structural equation modeling was used to examine significant paths between variables, thus creating a proposed new theoretical model that can be applied to CSR, public relations, and strategic communication literature.

The study offers a proposed new integrated theoretical model that can be applied to strategic communication literature and used to assist companies with enhancing their CSR communication and strategic communication planning efforts to determine how to move a public toward information seeking behaviors.