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The purpose of this paper is to develop a guideline of the control procedure and tools depending on dominance pattern. In Lean Six Sigma (LSS) implementation, the control phase plays a vital role in sustaining the gains achieved from the improvement phase. The process control schemes should be developed by studying the process dominance pattern as suggested by Juran.

Discussion has been made on identification of various methods with the help of a few real life examples for effective LSS implementation.

The dominance pattern helps in identifying the control mechanism. However, with the advent of new business processes, the dominance pattern needs a little bit of modification.

The case studies mainly are from the manufacturing sector and one from the service sector, where authors have studied the control mechanism. There exists scope of future research in service sector for adequate representation.

The treatise provides a road map to the practitioners for an effective implementation of the control phase in LSS. It is also expected to provide the scope of future work in this direction for both researchers and practitioners.

The purpose of the paper is to introduce a systemic approach to organizational learning “triple loop learning” (TLL) that addresses processes of power. Three equally important foci in our TLL are processes of design, processes of debate and processes of power. The focus on power aims to shift “power over” (power as domination) to “power to” enact empowering designs, “power to” co-develop responsible decision-making and “power to” transform our relations with each other and with life on Earth.

The organizational learning literature is reviewed in the context of power dynamics and its shortcomings are highlighted. The authors introduce their understanding of TLL, and how it engages with power dynamics in organizations.

Peter Senge’s conceptualization of systems thinking is unable to recognize processes of power in organizations and offers limited support to transformative learning. Conceptualizations of TLL aim to enhance learning in organizations but none satisfactorily address the processes of power. The learning organization literature as a whole does not satisfactorily address processes of power or reflect our way of envisaging “looping between loops of learning” in TLL to better design, better debate and better develop relationality in the social fabric of organizations.

The authors introduce an original approach to TLL that directly addresses the processes of power in organizations. It offers researchers, learning facilitators and practitioners of the learning organization a way to engage with the processes of power without neglecting other important organizational and environmental issues.

Dominance complementarity, which is the tendency for people to respond oppositely to others along the control dimension of interpersonal behavior, is a means by which people create and perpetuate informal forms of interpersonal hierarchy within social relationships (Tiedens, Unzueta, & Young, 2007b). In the present chapter, I explore the likely effects of such complementarity on group creativity. I propose specifically that expressions of dominance, even those borne not out of formal hierarchy but rather out of such factors as expertise and enthusiasm for the task, are likely to elicit submissive responses from fellow group members when the group is trying to generate creative ideas. As group members behaving submissively are likely to contribute fewer ideas to group discussion, I argue that group members who behave dominantly may, through their influence on other group members, reduce both the number and diversity of ideas generated within the group. I, therefore, propose that dominance complementarity may impair groups' abilities to generate creative ideas.

The main goal of this research work is the optimization of the purchasing business process in the Moroccan public sector in terms of transparency and budgetary optimization. The authors have worked on the public university as an implementation field.

The design of the research work followed the design science research (DSR) methodology for information systems. DSR is a research paradigm wherein a designer answers questions relevant to human problems through the creation of innovative artifacts, thereby contributing new knowledge to the body of scientific evidence. The authors have adopted a techno-functional approach. The technical part consists of the development of an intelligent recommendation system that supports the choice of optimal information technology (IT) equipment for decision-makers. This intelligent recommendation system relies on a set of functional and business concepts, namely the Moroccan normative laws and Control Objectives for Information and Related Technology's (COBIT) guidelines in information system governance.

The modeling of business processes in public universities is established using business process model and notation (BPMN) in accordance with official regulations. The set of BPMN models constitute a powerful repository not only for business process execution but also for further optimization. Governance generally aims to reduce budgetary wastes, and the authors' recommendation system demonstrates a technical and methodological approach enabling this feature. Implementation of artificial intelligence techniques can bring great value in terms of transparency and fluidity in purchasing business process execution.

Business limitations: First, the proposed system was modeled to handle one type products, which are computer-related equipment. Hence, the authors intend to extend the model to other types of products in future works. Conversely, the system proposes optimal purchasing order and assumes that decision makers will rely on this optimal purchasing order to choose between offers. In fact, as a perspective, the authors plan to work on a complete automation of the workflow to also include vendor selection and offer validation. Technical limitations: Natural language processing (NLP) is a widely used sentiment analysis (SA) technique that enabled the authors to validate the proposed system. Even working on samples of datasets, the authors noticed NLP dependency on huge computing power. The authors intend to experiment with learning and knowledge-based SA and assess the' computing power consumption and accuracy of the analysis compared to NLP. Another technical limitation is related to the web scraping technique; in fact, the users' reviews are crucial for the authors' system. To guarantee timeliness and reliable reviews, the system has to look automatically in websites, which confront the authors with the limitations of the web scraping like the permanent changing of website structure and scraping restrictions.

The modeling of business processes in public universities is established using BPMN in accordance with official regulations. The set of BPMN models constitute a powerful repository not only for business process execution but also for further optimization. Governance generally aims to reduce budgetary wastes, and the authors' recommendation system demonstrates a technical and methodological approach enabling this feature.

The adopted techno-functional approach enabled the authors to bring information system governance from a highly abstract level to a practical implementation where the theoretical best practices and guidelines are transformed to a tangible application.

The refined process structure tree (RPST), the hierarchy of non-overlapping single-entry single-exit (SESE) regions of a process model, has been utilized for better comprehension and more efficient analysis of business process models. Existing RPST methods, based on the triconnected components of edges, fail to identify a certain type of SESE region. The purpose of this paper is to introduce an alternative method for generating a complete RPST utilizing rather simple techniques.

The proposed method first focuses on the SESE regions of bonds and rigids, from the innermost ones to the outermost ones, utilizing dominance and post-dominance relations. Then, any SESE region of a series nested in a bond or a rigid is identified with a depth-first search variation. Two-phase algorithms and their completeness proofs, a software tool incorporating visualization of stepwise outcomes, and the experimental results of the proposed method are provided.

The proposed method utilizes simple techniques that allow their straightforward implementation. Visualization of stepwise outcomes helps process analysts to understand the proposed method and the SESE regions. Experiments with 604 SAP reference models demonstrated the limitation of the existing RPST methods. The proposed method, however, completely identified all types of SESE regions, defined with nodes, in less computation time than with the old methods.

Each triconnected component of the undirected version of a process model is associated with a pair of boundary nodes without discriminating between the entry and the exit. Here, each non-atomic SESE region is associated with two distinct entry and exit nodes from the original model in the form of a directed graph. By specifying the properties of SESE regions in more comprehensible ways, this paper facilitates a deeper understanding of SESE regions rather than relying on the resulting RPST.

The purpose of this paper is to examine the thought processes of financial auditors in order to offer additional information on factors affecting their decision behavior.

Using the psychology concept of cerebral dominance, two different instruments are used to measure the thinking styles of 20 auditors, at different stages of management. Prior research has indicated that “whole‐brain” thinkers (who do not exhibit dominance in either left‐ or right‐brain) may make better decisions, and thus, better managers.

The results of this study show partners in public accounting firms usually exhibiting a whole‐brain thinking style, while lower levels of management (staff auditors and managers) usually exhibit left‐brain thinking styles.

The findings have implications for training, education, communication, managerial styles, as well as the individual's position within the firm.

In today’s uncertain business environment, Industry 4.0 is regarded as a viable strategic plan for addressing a wide range of manufacturing-related challenges. However, it appears that its level of adoption varies across many countries. In the case of a developing economy like India, practitioners are still in the early stages of implementation. The implementation of Industry 4.0 appears to be complex, and it must be investigated holistically in order to gain a better understanding of it. Therefore, an attempt has been made to examine the Industry 4.0 implementation for the Indian manufacturing organization in a detailed way by analyzing the complexities of relevant variables.

SAP-LAP (situation-actor-process and learning-action-performance) and an efficient interpretive ranking process (e-IRP) were used to analyze the various variables influencing Industry 4.0 implementation. The variables were identified, as per SAP-LAP, through a thorough review of the literature and based on the perspectives of various experts. The e-IRP has been used to prioritize the selected elements (i.e. actors with respect to processes and actions with respect to performance) of SAP-LAP.

This study ranked five stakeholders according to their priority in Industry 4.0 implementation: government policymakers, industry associations, research and academic institutions, manufacturers and customers. In addition, the study also prioritized important actions that need to be taken by these stakeholders.

The results of this study would be useful in identifying and managing the various actors and actions related to Industry 4.0 implementation. Accordingly, their prioritized sequence would be useful to the practitioners in preparing the well-defined and comprehensive strategic roadmap for Industry 4.0.

This study has adopted qualitative and quantitative approaches for identifying and prioritizing different variables of Industry 4.0 implementation. This, in turn, helps the stakeholder to comprehend the concept of Industry 4.0 in a much simpler way.

This paper aims to explore the relationships between website quality – through consumer-generated media stimuli-, emotions and consumer-brand engagement in online environments.

Two independent studies are conducted to examine these relationships. Study 1, based on a sample of 366 respondents, uses a structural equation modelling approach to test the research hypotheses. Study 2, based on 1,454 online consumer reviews, uses text-mining technique to examine further the relationship between emotions and consumer-brand engagement.

The findings show that all the consumer-generated media stimuli are positively related to the dimensions of emotions. However, only pleasure and arousal are positively related to the three variables of consumer-brand engagement. The findings also show cognitive processing as the strongest dimension of consumer-brand engagement providing positive sentiments towards brands.

The findings provide marketers with an understanding of how valid, useful and relevant content (i.e. information/content) creates a greater emotional connection and drive consumer-brand engagement. Marketers should be aware that consumer-generated media stimuli influence consumers’ emotions and their reaction.

This study is one of the firsts to adapt and apply the S-O-R framework in explaining online consumer-brand engagement. This study also adds to the brand engagement literature as the first study that combines PLS-SEM approach with text-mining analysis to provide a better understanding of these relationships.

The need to address energy management as a significant innovation in the smart grid is emphasized to enable a more effective penetration of renewable energy to achieve energy savings and CO₂ emission reductions. The purpose of this study is to propose a holistic, flexible decision framework for energy management in a smart grid.

According to the situation actor process−learning action performance (SAP−LAP) model, the variables have been identified after a comprehensive analysis of the literature and consideration of the opinions of domain experts. However, the importance of each SAP−LAP variable is not the same in real practice. Hence, focus on these variables should be given based on their importance, and to measure this importance, an interpretive ranking process based ranking method is used in this study. This helps to allocate proportionate resource to each SAP−LAP variable to make a better decision for the energy management of the smart grid.

This study ranked five actors based on their priorities for energy management in a smart grid: top management, generator and retailor, consumers, government policy and regulation and technology vendors. Furthermore, actions are also prioritized with respect to performance.

The SAP−LAP model conveys information about the state of energy management in India to actors who may proceed or manage the flow of electricity. Additionally, this study aids in detecting vulnerabilities in the current energy generation, transmission and distribution technique. The synthesis of SAP results in LAP, which assists in recommending improvement actions learned from the current situation, actors and processes.

The SAP−LAP model is a revolutionary approach for examining the current state of energy management in a unified framework that can guide decision-making in conflicting situations, significantly the contradictory nature of India’s renewable energy and power sectors.

The present chapter addresses a topic that is of growing interest – namely, the exploration of alternative item response theory (IRT) models for noncognitive assessment. Previous research in the assessment of trait emotional intelligence (or “trait emotional self-efficacy”) has been limited to traditional psychometric techniques (e.g., classical test theory) under the notion of a dominance response processes describing the relationship between individuals' latent characteristics and individuals' response selection. The present study, presents the first unfolding IRT modeling effort in the general field of emotional intelligence (EI). We applied the Generalized Graded Unfolding Model (GGUM) in order to evaluate the response process and the item properties on the short form of the trait emotional intelligence questionnaire (TEIQue-SF). A sample of 866 participants completed the English version of the TEIQue-SF. Results suggests that the GGUM has an adequate fit to the data. Furthermore, inspection of the test information and standard error functions revealed that the TEIQue-SF is accurate for low and middle scores on the construct; however several items had low discrimination parameters. Implications for the benefits of unfolding models in the assessment of trait EI are discussed.