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This paper aims to introduce a joint DEMATEL and NK methodology to develop a process model for introducing and implementing relational supply chain practices for low-carbon supply chains. Using this process model as a guide, insights into specific practices and how to implement these relational practices to achieve competitive advantage across organizations are introduced.

Low-carbon cooperation practices framework based on the relational view is developed. A methodology based on DEMATEL and the NK model is used to construct a sequential process model for introducing and implementing these relational practices. Empirical data from three manufacturing organizations in China are utilized to validate the model.

Initial results provide a sequence of relational practices for guiding those organizations and their suppliers for healthy and low-carbon development. Interdependencies between relational practices are analyzed and evaluated from four aspects. Insights into the broader application of the methodology and initial results from both a research and managerial perspective are presented, especially with consideration of the China, an emerging economy, context.

The methodology remains relatively abstract in nature, yet the tool can provide very useful interpretations and information for both researchers and practitioners.

This paper stipulates that in addition to internal operational practices, the relational practices between buyer and supplier may be equally important to achieve a low-carbon outcome, especially in supply chain setting. This paper also shows that not only the relational practice itself but also the implementation sequence of the relational practices can relate to performance. According to the authors’ initial results, organizations in this study should first develop product development cooperation, then exchange carbon knowledge and implement effective governance and last build a trust relationship with its suppliers for low-carbon cooperation.

This is one of the few approaches that directly evaluates and identifies the interdependencies among relational practices and to construct a process model for introducing and implementing low-carbon supply chain cooperation. It is also the first time that the NK model has been integrated with DEMATEL. Focusing on Chinese supply chain carbon emissions concerns is also a unique perspective.

Relationship management evolves with dynamic and complex environments of megaprojects. However, studies on the longitudinal measurement of relationship management performance for each stakeholder in dynamic and complex project environments are lacking. The purpose of this research is to propose an NK-network evolution model to evaluate stakeholder performance on relationship management in the development of megaprojects.

The model input includes the stakeholder-associated issues and stakeholders' relational strategies, the co-effects of which determine the internal effects of relationship management in megaprojects. The model processing simulates the stakeholder performance of relationship management under the dynamic and complex nature of megaprojects. The NK model shows the dynamic stakeholder interactions on relationship management, whereas the network model presents the complex stakeholder structures of the relationships between stakeholders and relevant issues. The model output is the evolution graph to reveal the weak stakeholder performance on relationship management in the timeline of the project duration.

The research finding reveals that all stakeholders experience the plunge of stakeholder performance of relationship management at the decision-making moment of the planning stage. Construction, environmental and pressure groups may experience the hardship of relationship management at the start of the construction stage. The government is likely to suffer difficulties in relationship management in the late construction stage. Local industry groups would face challenges in relationship management in the middle of the construction stage and handover stage.

The research provides a useful approach to measuring weak moments of relationship management for each stakeholder in various project phases, considering the dynamic and complex environments of megaprojects. The proposed model extends the current knowledge body on how to make project stakeholder analysis by modelling dynamic and complex environments of megaprojects, with bridging the knowledge domains of evolution modeling techniques and network methods.

The objective of this study is to model and analyze the exploration‐exploitation dynamics of March's model of mutual learning in a complex environment. By enhancing the above mentioned model, the paper seeks to propose a new agent‐based model of mutual learning within an organization.

The paper replicates March's model of simulating learning within an organization using an agent‐based simulation approach, and extends it by modelling the problem space as a fitness landscape using Kauffman's NK model technique.

It was found that it is impossible to find a right balance between exploration and exploitation using the communication structure of March's model.

The proposed model could help create a virtual laboratory for experimenting organizations' behavior in a complex co‐evolving environment. This virtual laboratory may be used in the future to support the decision‐making process of managers and policy makers.

Designing the external environment as a fitness landscape helps in discovering what effect the environmental complexity has on the emerging balance between exploration and exploitation. It is the first study to design the environment of a model which analyzes the mutual learning between an organization and its members as a complex non‐linear space.

This theoretical paper presents, extends and integrates a number of systems and evolutionary concepts, to demonstrate their relevance to manufacturing strategy formulation. Specifically it concentrates on fitness landscape theory as an approach for visually mapping the strategic options a manufacturing firm could pursue. It examines how this theory relates to manufacturing competitiveness and strategy and proposes a definition and model of manufacturing fitness. In accordance with fitness landscape theory, a complex systems perspective is adopted to view manufacturing firms. It is argued that manufacturing firms are a specific type of complex system – a complex adaptive system – and that by developing and applying fitness landscape theory it is possible to create models to better understand and visualise how to search and select various combinations of capabilities.

Innovation is essential for business growth that cannot be created by financial investment alone but with intellectual capital (IC). IC management is critical for the organization, yet many firms do not have proper strategies. The purpose of this paper is to present an effective planning model that enables organizations to raise their innovation capability through strategic IC management.

Two R & D groups in an information and communication technology organization are examined with an IC-based complex system model (wiNK model). The model includes a descriptive part that determines the current IC state of the group and a prescriptive part that identifies the IC strategies for optimal innovation performance.

This paper demonstrated that the wiNK model is an easy-to-use prescriptive tool using IC to optimize innovation performance.

The IC state of an organization is dynamic and changing. Regular IC examinations are necessary to track its changes.

This IC-based model can be applied individually without benchmarking with other organizations. The IC location map can be documented as an organization DNA profile for the organization. The tracking of the continuous and dynamic changes is beneficial to the organization and its stakeholders. It can be served as both planning and evaluation tools.

This study offers a systemic approach to the interdisciplinary study of organizational behavior and innovation with a pioneering use of an IC framework. It contributes to the field of innovation management with a new attempt of its kind to integrate management research and mathematical simulation model.

This paper aims to evaluate the effect of knowledge overlap, search width and problem complexity on the quality of problem-solving in teams that use the majority rule to aggregate heterogeneous knowledge of the team members.

The paper uses agent-based simulations to model iterative problem-solving by teams. The simulation results are analyzed using linear regressions to show the interactions among the variables in the model.

We find that knowledge overlap, search width and problem complexity interact to jointly impact the optimal solution in the iterative problem-solving process of teams using majority rule decisions. Interestingly, we find that more complex problems require less knowledge overlap. Search width and knowledge overlap act as substitutes, weakening each other’s performance effects.

The results suggest that team performance in iterative problem-solving depends on interactions among knowledge overlap, search width and problem complexity which need to be jointly examined to reflect realistic team dynamics.

The findings suggest that team formation and the choice of a search strategy should be aligned with problem complexity.

This paper contributes to the literature on problem-solving in teams. It is the first attempt to use agent-based simulations to model complex problem-solving in teams. The results have both theoretical and practical significance.

Availability of accurate quantity of materials, at correct place and at right time is extremely critical for increasing production effectiveness of any manufacturing organization. This can be achieved through employing an appropriate material handling equipment (MHE) capable of performing the desired operation. Therefore, choosing a right MHE from the available options is a key concern for the success, growth and competitiveness of a manufacturing organization. The purpose of this paper is to describe the design and development of an expert system based on quality function deployment (QFD) methodology in Visual Basic 6.0 for selecting the most appropriate industrial truck which is a commonly practiced MHE in any manufacturing organization.

A QFD-based approach is adopted to incorporate customers’ needs into the evaluation criteria on the basis of which industrial truck selection is carried out. The applicability of the developed expert system in solving industrial truck selection problems is demonstrated using two illustrative examples.

While applying this QFD-based model, CPCD 80x manufactured by Heli is recognized as the most suitable forklift truck for transporting unitized loads within a manufacturing unit with some spatial constraints, and for loading/unloading packages/boxes/cartons and place them at the desired locations in a manufacturing unit, ETV 216 manufactured by Jungheinrich evolves out as the most suitable reach truck.

Till date, numerous research articles have been published suggesting the applications of various mathematical models, multi-criteria decision-making methods and knowledge-based systems for solving MHE selection problems, and it is intriguing to note that none of the previously adopted methods has proposed a systematic procedure for selection of the evaluation criteria and interrelated the needs of customers with the technical specifications of MHEs while identifying the best alternative for performing a specified operation. These issues can be addressed through application of this developed QFD-based expert system, which can translate customers’ needs into organizational functions that are implementable in the decision-making/selection procedure.

The purpose of this paper is to update existing Kauffmann’s NK model to evaluate the manufacturing fitness of strategic business capabilities. The updated model is tested in a digital manufacturing (DM) setting to investigate the sequence for developing cumulative capabilities that can yield the maximum payoff.

The authors develop a grey–DEMATEL–NK fitness model and show its application, through a case study, to a DM firm in India.

The grey–DEMATEL–NK model helps evaluate multiple manufacturing capabilities and indicates that quality–flexibility–cost–delivery is the sequence that yields the maximum manufacturing fitness (competitive payoff) for a DM firm. This sequence helps the firm reorganise its internal business processes and is different from that used to develop cumulative capabilities in a traditional manufacturing setting (quality–delivery–flexibility–cost).

This study presents a pilot model for computing the cumulative capabilities payoff and prescribes a sequence for developing cumulative capabilities within a DM context.

The primary purpose of this paper is to investigate the sources of the business cycle fluctuations in Vietnam. To this end, the author develops a small open economy New Keynesian dynamic stochastic general equilibrium (SOE-NK-DSGE) model. Accordingly, this model includes various features, such as habit consumption, staggered price, price indexation, incomplete exchange-rate pass-through (ERPT), the failures of the law of one price (LOOP) and the uncovered interest rate parity. It is then estimated by using the Bayesian technique and Vietnamese data 1999Q1–2017Q1. Based on the estimated model, this paper analyzes the sources of the business cycle fluctuations in this emerging economy. Indeed, this research paper is the first attempt at developing and estimating the SOE-NK-DSGE model with the Bayesian technique for Vietnam.

A SOE-NK-DSGE model—Bayesian estimation.

This paper analyzes the sources of the business cycle fluctuations in Vietnam.

This research paper is the first attempt at developing and estimating the SOE-NK-DSGE model with the Bayesian technique for Vietnam.

This study aims to assess nutrition knowledge (NK) and willingness to seek nutritional counseling (WSNC) and their predictors among university students in Lebanon.

A cross-sectional design was used to enroll students from two large private universities in Lebanon. Data were collected by a standardized questionnaire. NK scores on general and specific nutrition areas were computed. The predictors of NK and WSNC were determined by multivariable logistic regression analyses.

A total of 370 students were included, among which 68% had good general nutritional knowledge, which appears to be associated with being a pharmacy student (adjusted OR (aOR) = 4.26 [95% confidence interval (CI) 1.55; 11.7]), and having a dietitian as a reference for nutritional information (aOR = 8.84 [95% CI 1.94; 40.3]). However, 64% of participants had a high specific nutritional knowledge score, which was related to either attending a school of arts and sciences or being a pharmacy student (aOR = 10.8 [95% CI 4.08; 28.5]). Most students (80%) had the will to seek nutritional counseling, which was positively associated with being a female (aOR = 2.01 [95% CI 1.10; 3.67]) and a pharmacy student (aOR = 2.62 [95% CI 1.15; 5.95]). The general nutritional knowledge score was significantly associated with the WSNC (aOR = 2.10 [95% CI 1.04; 4.25]).

Higher nutritional knowledge and WSNC were found among students enrolled in health-related fields. These results underline how important nutrition education is as a strategy for inspiring college students to adopt healthy lifestyles.