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A literature review revealed that in recent times, many companies have attempted organization‐wide change management through the philosophy and principles of Lean Thinking (LT). Although some organizations have transformed and reaped significant benefits in this endeavour, many organizations have failed in this attempt. One of the reasons can be attributed to the fact that not many organizations are attempting to “assess the organizational readiness” before implementing/adapting LT. This paper aims to address this issue.

Hence in this paper, an attempt has made to address this problem by presenting a hypothetical case study of an Indian organization to comprehensively assess organizational readiness of the case organisation using a graph theoretic approach (GTA), which has the ability to integrate and model multiple inter‐related factors.

From the obtained results, it was found that the case organization is not fully ready to embrace LT. It needs to work on different factors under the categories of suppliers, customers, etc. in addition to employees, organisation and top management for smooth and successful adaptation.

According to the authors' knowledge, no paper exists either in the literature of organizational analysis or in the field of LT literature that demonstrates the application of GTA, specifically for assessing the readiness of an organization in adapting LT. Furthermore, various factors which need to be considered were identified apart from modelling them by incorporating the relationship/dependency that exists between these factors, which is unique.

Agility and sustainability are different manufacturing paradigms. Ideally, companies should merge the two concepts so as to enhance competitive advantage. Agility, which has evolved from lean manufacturing, is the ability of an enterprise to respond quickly to a wide range of customer demands. On the other hand sustainability is a condition in which a company optimizes economic, social and environmental factors by taking into account indirect and long-term consequences. Merging the two concepts could result in holistically improving the system, by fulfilling performance without depleting available resources. Thus, identifying and simultaneously improving two areas with common goals could lead to developing a successful and an emerging enterprise. The paper aims to discuss these issues.

The authors identify agility-sustainability criteria which complement each other from amongst a set of differentiating criteria. The conceptual model is built by integrating five enablers with 25 criteria and 75 attributes. The combined criteria are modeled using graph theory which considers interdependencies and contributing factors on the organization. Within each enabler, the authors investigate the interdependencies between criteria and focus further on those that have potential to improve overall score. The methodology was applied in a manufacturing organization that operates on ad hoc basis depending on projects’ availability.

The model determines a range of values for extreme scenarios under theoretical and practical situations, along with the current level of business. The scenarios are tested for assessing performance by identifying the gaps in the weaker areas.

Approach can serve as a managerial tool for monitoring performance of the organization along agility and sustainability dimensions. Further, government entities can use the approach in devising policy for improving economies by considering holistic approach rather than only environmental aspect. Biased and conflicting opinions of experts might deter chances for comprehensive and consistent decision.

The study integrates a framework for modeling and performance evaluation for a system that incorporates agility and sustainability characteristics. The study will enable practicing managers and decision makers to identify suitable characteristics that would simultaneously improve an organization’s agile performance by considering aspects of sustainability.

Easily employable quantitative supply chain complexity (SCC) measures considering the significant dimensions of complexity as well as the drivers that represent those dimensions are limited in the literature. The purpose of this paper is to propose an integrated interpretive structural modeling (ISM) and a graph-theoretic approach to quantify SCC by a single numerical index considering the interdependence and the inheritance of the SCC drivers.

In total, 18 SCC drivers identified from the literature are clustered according to the significant dimensions of complexity. The interdependencies established through ISM and inheritance values of SCC drivers are mapped into a Variable Permanent Matrix (VPM). The permanent function of this VPM is then computed and the resulting single numerical index is the measure of SCC.

A scale is proposed by computing the minimum and maximum threshold values of SCC with the help of expert opinions of the Indian automotive industry. The complexity of commercial and passenger vehicle sectors within the automotive industry is measured and compared using the proposed scale. From the results, it is identified that the number of suppliers, increase in spare-parts due to shortened product life-cycle and demand uncertainties increase the SCC of the passenger vehicle sector, while number of parts, products and processes, variety of products and process and unreliability of suppliers increase the complexity of the commercial vehicle sector. The result indicates that various SCC drivers have a different impact on determining the SCC level of these two sectors.

The authors propose an integrated method that can be readily applied to measure and quantify SCC considering the significant dimensions of complexity as well as the interdependence and the inheritance of the SCC drivers that contribute to those dimensions. This index further helps to compare the complexity of the supply chain which varies between industries.

The generality of the genetic search in the light of proper coding schemes, together with its non‐gradient‐based search, has made it popular for many discrete problems including structural optimization. However, the required computational effort increases as the cardinality of the search space and the number of design variables increase. Memetic algorithms are formal attempts to reduce such a drawback for real‐world problems incorporating some kind of problem‐specific information. This paper aims to address this issue.

In this paper both Lamarckian and Baldwinian approaches for meme evolution are implemented using the power of graph theory in topology assessment. For this purpose, the concept of load path connectivity in frame bracing layouts is introduced and utilized by the proposed graph theoretical algorithms. As an additional search refinement tool, a dynamic mutation band control is recommended. In each case, the results are studied via a set of ultimate design family rather than one pseudo optimum. The method is further tested using a number of steel frame examples and its efficiency is compared with conventional genetic search.

Here, the problem of bracing layout optimization in steel frames is studied utilizing a number of topological guidelines.

The method of this paper attempts to reduce the computational effort for optimal design of real‐world problems incorporating some kind of problem‐specific information.

Risk factors related delay hinder the schedule performance of most construction projects in the world. It is a critical challenge to realize the advantages of prefabricated construction projects (PCPs) under the negative effect of schedule delay. This paper aims to propose an exhaustive list of risk factors impeding the progress of PCPs and evaluate the collected risk factors based on the cause–effect relations. The ultimate goal is to improve the understanding of the complex relations among various risk factors related delay in PCPs, and also offer managers a reference on aspect of schedule risk management.

This paper proposes a hybrid method of GT–DEMATEL–ISM, that is combing grounded theory, DEMATEL (decision-making trial and evaluation laboratory) and ISM (Interpretative Structural Modeling), to collect, evaluate and structure risk factors related delay for PCPs. The research procedure of this methodology is divided into three stages systematically involving qualitative and quantitative analysis. In the first stage, GT is utilized to implement qualitative analysis to collect the risk factors leading to schedule delay in PCPs. While, the quantitative analysis is to analyze and evaluate the collected risk factors based on the cause–effect relations in the next two stages evaluation by the DEMATEL focuses on quantifying the priority and intensity of the relations between factors. Additionally, ISM is employed to construct the hierarchical structure and graphically represent the pairwise relations between factors.

The outcome of qualitative investigation by grounded theory proposes a theoretical framework of risk factors related delay for PCPs. The framework contains three levels of category, namely, core category, main category and initial category and provides a list of risk factors related delay. Following this finding, evaluation results by the DEMATEL classify factors into cause and effect groups and determine 11 critical delay risk factors. Meanwhile, the findings show that risks referring to organizational management issue foremost impact the progress of PCPs. Furthermore, a systemic multilevel hierarchical structure model is visually constructed by ISM to present the pairwise linkages of critical factors. The model provides the risk transmission chains to map the spread path of delay impact in the system.

The contribution of the study involves twofold issues. Methodologically, this research proposes a hybrid method GT–DEMATEL–ISM used to identify and analyze factors for a complex system. It is also applicable to other fields facing similar problems that require collecting, evaluating and structuring certain elements as a whole in a comprehensive perspective. The theoretical contribution is to fill the relevant research gap of the existing body of knowledge. To the best knowledge of the authors, this paper is the first attempt to integrate qualitative and quantitative research for risk analysis related delay and take the insight into the whole process of PCPs covering off-site manufacture and on-site construction. Furthermore, the analysis of findings provided both a micro view focusing on individual risk factor and a managerial view from a systematic level. The findings also contribute the effective information to improve the risk management related schedule delay in PCPs.

This paper seeks to lay the computational and mathematical foundations for a “postmodern cybernetics” based on ancient Kabbalah. This new Kabbalistic cybernetics is introduced to act as an unifying science addressing simultaneously, in a common language and framework the triple nature of human, psychological, social, economic, financial, political, cultural systems and their present multi‐faceted crises and conflicts: cognitive objective level of attaining knowledge; subjective emotional level and physical action and behavioral level.

Feedback, hierarchical control and other system and control theoretic features in the Tree of Life (TL) of Kabbalah were identified. These were used to develop a general system theoretic framework of a new type to address human and societal system dynamics, evolution, interaction and feedback control by simultaneously taking into account their triple nature.

The postmodern cybernetics of the TL introduced here as a general system framework, exhibits feedback control with internal model principle, hierarchical control, system multi‐valued logic, category theory pullback and pushout mechanisms, advanced knowledge engineering to aggregate, learn, evolve and solve problems and crises in an integrated way.

“Kabbalistic postmodern cybernetics” proposed here for human and societal systems is the unified scientific framework to solve problems that led to or are just related to economic, financial, political, cultural, societal and human crises and conflicts by addressing their triple intertwined human nature.

Computational foundations for a postmodern cybernetics based on Kabbalah are introduced, where the cognitive, emotional and behavioral and physical action facets of human systems are dealt with in a unified integrated framework to address global problems and crises.

The authors present a model that incorporates stochastic interest rates to value equity‐linked life insurance contracts. The model generalizes some previous pricing results of Arne and Persson [1994] that are based on deterministic interest rates. The article also proposes and compares a design for a new equity‐linked product with the periodical premium contract of Brennan and Schwartz [1976]. The advantages of the proposed prod‐uct are its simplicity in pricing and its ease of hedging, by using either by long positions in the linked mutual fund or by European call options on the same fund.

This research aims to explore the research data ethics governance framework and collaborative network to optimize research data ethics governance practices, to balance the relationship between data development and utilization, open sharing, data security and to reduce the ethical risks that may arise from data sharing and utilization.

This study explores the framework and collaborative network of research data ethics policies by using the UK as an example. 78 policies from the UK government, university, research institution, funding agency, publisher, database, library and third-party organization are obtained. Adopting grounded theory (GT) and social network analysis (SNA), Nvivo12 is used to analyze these samples and summarize the research data ethics governance framework. Ucinet and Netdraw are used to reveal collaborative networks in policy.

Results indicate that the framework covers governance context, subject and measure. The content of governance context contains context description and data ethics issues analysis. Governance subject consists of defining subjects and facilitating their collaboration. Governance measure includes governance guidance and ethics governance initiatives in the data lifecycle. The collaborative network indicates that research institution plays a central role in ethics governance. The core of the governance content are ethics governance initiatives, governance guidance and governance context description.

This research provides new insights for policy analysis by combining GT and SNA methods. Research data ethics and its governance are conceptualized to complete data governance and research ethics theory.

A research data ethics governance framework and collaborative network are revealed, and actionable guidance for addressing essential aspects of research data ethics and multiple subjects to confer their functions in collaborative governance is provided.

This study analyzes policy text using qualitative and quantitative methods, ensuring fine-grained content profiling and improving policy research. A typical research data ethics governance framework is revealed. Various stakeholders' roles and priorities in collaborative governance are explored. These contribute to improving governance policies and governance levels in both theory and practice.

The state-of-the-art methods designed for overlapping community detection are limited by their high execution time as in CPM or the need to provide some parameters like the number of communities in Bigclam and Nise_sph, which is a nontrivial information. Hence, there is a need to develop the accuracy that represents the primordial goal, where the actual state-of-the-art methods do not succeed to achieve high correspondence with the ground truth for many instances of networks. The paper aims to discuss this issue.

The authors offer a new method that explore the union of all maximum spanning trees (UMST) and models the strength of links between nodes. Also, each node in the UMST is linked with its most similar neighbor. From this model, the authors extract local community for each node, and then they combine the produced communities according to their number of shared nodes.

The experiments on eight real-world data sets and four sets of artificial networks show that the proposed method achieves obvious improvements over four state-of-the-art (BigClam, OSLOM, Demon, SE, DMST and ST) methods in terms of the F-score and ONMI for the networks with ground truth (Amazon, Youtube, LiveJournal and Orkut). Also, for the other networks, it provides communities with a good overlapping modularity.

In this paper, the authors investigate the UMST for the overlapping community detection.

General theories have been criticized for their inability to explore the mechanics of more specific domain knowledge and understand how, when and where general theory applies to and extends domain knowledge in supply chain management (SCM). Middle-range theorizing (MRT) is a potential solution to this limitation. This paper aims to assist researchers in understanding the relationship between MRT and general theorizing (GT) and connecting MRT research findings to general theory.

This research provides a structured literature review of 518 articles, from eight journals in logistics, SCM and operations management. Theoretically based articles are analyzed by primary domain and SCM context.

There are frameworks for conducting MRT; however, the literature does not sufficiently assist researchers in understanding how middle-range (MR) theory should relate to general theory. Findings include a better understanding of underserved areas in SCM, guideline frameworks for understanding when to apply MRT, when to apply GT and how MRT knowledge can be connected to SCM domain knowledge.

This study provides a timely and appropriate compilation of theory research in SCM, including significant implications for both theory and practice, by helping to articulate the evolving philosophy of science in SCM.